阅读说明：本技术 冷头效率计算指标、定量描述冷头效率的方法、及冷头效率监测方法 (Cold head efficiency calculation index, method for quantitatively describing cold head efficiency and cold head efficiency monitoring method ) 是由 金伟 张文渊 于宁 温晓宇 于 2018-01-19 设计创作，主要内容包括：本发明公开一种定量描述冷头效率的方法,通过为冷头效率定义计算指标,实现了将冷头效率量化。同时本发明还提供了利用定义的计算指标计算冷头效率值和对冷头效率进行监测的方法和系统,实现了对冷头效率的定量分析,并能基于定量分析的结果实现当冷头效率降低到一定程度之后,及时提醒用户准备冷头备件,并及时更换冷头,解决了现有技术中需要维修工程师根据液氦压力数据进行冷头效率定性估计、导致效率不高、容易带来损失的问题。(The invention discloses a method for quantitatively describing cold head efficiency, which realizes the quantification of the cold head efficiency by defining a calculation index for the cold head efficiency. Meanwhile, the invention also provides a method and a system for calculating the cold head efficiency value and monitoring the cold head efficiency by using the defined calculation index, so that the quantitative analysis of the cold head efficiency is realized, and the user can be timely reminded to prepare a cold head spare part and replace the cold head in time after the cold head efficiency is reduced to a certain degree based on the quantitative analysis result, thereby solving the problems that in the prior art, a maintenance engineer needs to perform qualitative estimation on the cold head efficiency according to the liquid helium pressure data, the efficiency is low and the loss is easy to bring.)

1. The index for calculating the cold head efficiency is characterized by comprising

A dominant independent variable, the dominant independent variable being a time feature extracted based on liquid helium pressure data; and

a dependent variable, the dependent variable being a cold head efficiency value;

the dependent variable is set to be bounded, and the value range of the leading independent variable has an upper limit and a lower limit;

the dependent variable changes along with the dominant independent variable are characterized by monotonous trend towards an upper limit or a lower limit.

2. The calculated indicator of claim 1, wherein the extracted temporal characteristic is a fall time of liquid helium pressure or a cycle time of liquid helium pressure.

3. The calculated index of claim 2, wherein the dependent variable has an upper limit of one and a lower limit of zero; and is

When the drop time or the cycle time of the input liquid helium pressure approaches zero, the output cold head efficiency approaches one;

when the input falling time or cycle time approaches infinity, the output cold head efficiency approaches zero;

the output cold head efficiency monotonically decreases with the increase of the numerical value of the fall time or cycle time of the input liquid helium pressure in the interval of 0, 1.

4. The calculation index according to any one of claims 1 to 3, further comprising

An additional independent variable for adjusting only the magnitude of the output value of the dependent variable.

5. The calculated indicator of any one of claims 1 to 3, wherein the calculated indicator is implemented by a sigmoid function.

6. The calculation index according to claim 1, wherein the calculation index is realized by the following model

E ═ a × exp (-b × T + c))/(d + E × exp (-f × T + g))), E is a cold head efficiency calculation index, T is a fall time of the liquid helium pressure, and a, b, c, d, E, f, and g are parameters to be solved; or

The calculation index is realized by the following model

E ═ exp (a × T + b)/(1+ exp (a × T + b)), where E is an index for calculating cold head efficiency, T is a fall time of liquid helium pressure, and a, b are parameters to be found.

7. The method for quantitatively describing the cold head efficiency is characterized by being realized by the following steps:

extracting time characteristics of liquid helium pressure data;

mapping the extracted time characteristics into a cold head efficiency value;

wherein the mapping comprises: the mapped cold head efficiency value is set to have an upper limit and a lower limit within a value range of the time characteristic, and the cold head efficiency value is set to monotonically trend toward the upper limit or the lower limit with changes of the time characteristic.

8. The method of claim 7, wherein the time characteristic of extraction is a fall time of liquid helium pressure or a cycle time of liquid helium pressure;

the mapping further comprises:

when the drop time or the cycle time of the input liquid helium pressure approaches zero, the output cold head efficiency approaches one;

when the input falling time or cycle time approaches infinity, the output cold head efficiency approaches zero;

the output cold head efficiency monotonically decreases with the increase of the numerical value of the fall time or cycle time of the input liquid helium pressure in the interval of 0, 1.

9. The method of claim 8, wherein said mapping the extracted temporal features to cold head efficiency values is implemented to include:

selecting or defining a specific mapping function basic model, wherein the mapping function basic model comprises a leading independent variable and a dependent variable;

setting the leading independent variable of the mapping function basic model as a time characteristic extracted based on liquid helium pressure data, and setting the dependent variable of the mapping function basic model as a cold head efficiency value;

acquiring historical data of a cold head for analysis, and determining an input sample set;

and obtaining parameters to be solved of the mapping function basic model in a curve fitting mode according to the input sample set, and generating the determined function model for calculating the cold head efficiency value.

10. The method of claim 9, wherein the obtaining historical data of a cold head for analysis, determining the set of input samples comprises:

acquiring full life cycle historical data of the cold head;

and respectively acquiring a first boundary sample, a second boundary sample and a random input sample according to the full life cycle historical data and the property met by the function.

11. The method of claim 8, wherein the mapping function base model is

E ═ a × exp (-b × T + c))/(d + E × exp (-f × T + g))), E is a cold head efficiency calculation index, T is a fall time of the liquid helium pressure, and a, b, c, d, E, f, and g are parameters to be solved; or

Is composed of

E ═ exp (a × T + b)/(1+ exp (a × T + b)), where E is an index for calculating cold head efficiency, T is a fall time of liquid helium pressure, and a, b are parameters to be found.

12. The method of claim 8, wherein the mapping function base model is chosen as a sigmoid function;

the mapping function base model is defined to further include an additional independent variable for adjusting only the magnitude of the output value of the dependent variable.

13. The monitoring method of the cold head efficiency is characterized by comprising the following steps:

acquiring and storing liquid helium pressure threshold values corresponding to the turning on and turning off of the heater respectively;

calculating the falling time of the liquid helium pressure according to the real-time liquid helium pressure information and the liquid helium pressure threshold value;

storing the falling time of the liquid helium pressure and a time stamp corresponding to the falling time;

and in response to a user request, drawing a curve of the liquid helium pressure descending time along with the time change by taking the time stamp as an X axis and the descending time as a Y axis, and displaying the curve to the user.

14. The method of claim 13, wherein calculating the fall time of the liquid helium pressure based on the real-time liquid helium pressure value and the liquid helium pressure threshold value comprises:

continuously acquiring the latest real-time liquid helium pressure value, comparing the latest real-time liquid helium pressure value with the liquid helium pressure threshold value for closing the heater until the current real-time liquid helium pressure value is greater than or equal to the liquid helium pressure threshold value for closing the heater, and recording the occurrence time T1 of the current real-time liquid helium pressure value;

continuously acquiring the latest real-time liquid helium pressure value, comparing the latest real-time liquid helium pressure value with the liquid helium pressure threshold value for opening the heater until the current real-time liquid helium pressure value is less than or equal to the liquid helium pressure threshold value for opening the heater, and recording the occurrence time T2 of the current real-time liquid helium pressure value;

the falling time of the liquid helium pressure is calculated according to the recorded occurrence times T1 and T2.

Technical Field

The invention relates to the technical field of medical equipment management, in particular to a method and a system for calculating cold head efficiency of nuclear magnetic resonance equipment, and an electronic device or a product carrying the system.

Background

The cold head is a core component in the nuclear magnetic resonance superconducting magnet, and once the working efficiency of the cold head is reduced, the pressure of liquid helium fluctuates abnormally, so that the liquid helium leaks and even quenches. Therefore, the working efficiency of the cold head directly influences the working state of the nuclear magnetic resonance equipment, and the attention to the working efficiency of the cold head has great application value. However, in the prior art, a maintenance engineer usually estimates the cold head efficiency qualitatively according to the liquid helium pressure data (i.e. the maintenance engineer judges by personal experience), and determines whether the cold head needs to be replaced, and generally the cold head needs to be replaced after the liquid helium pressure fluctuates abnormally and even loses a certain amount. In this way, the estimation is performed according to the liquid helium pressure data, and when the cold head efficiency is found to be in problem, the abnormal fluctuation of the liquid helium pressure is also serious, so the efficiency is low, and the hospital is generally caused great loss.

Therefore, there is a need in the art to provide a more effective and timely solution that can obtain the working efficiency of the cold head in advance before the pressure of the liquid helium fluctuates abnormally so as to provide early warning, so as to avoid the loss caused and improve the accuracy of monitoring the working efficiency of the cold head.

Disclosure of Invention

According to one aspect of the invention, a method for quantitatively describing cold head efficiency is provided, and quantification of the cold head efficiency is realized by defining a calculation index for the cold head efficiency. Meanwhile, the invention also provides a method and a system for calculating the cold head efficiency value and monitoring the cold head efficiency by using the defined calculation index, so that the quantitative analysis of the cold head efficiency is realized, and the user can be timely reminded to prepare a cold head spare part and replace the cold head in time after the cold head efficiency is reduced to a certain degree based on the quantitative analysis result, thereby solving the problems that in the prior art, a maintenance engineer needs to perform qualitative estimation on the cold head efficiency according to the liquid helium pressure data, the efficiency is low and the loss is easy to bring.

The cold head efficiency calculation index provided by the invention is defined as a function taking time characteristics extracted based on liquid helium pressure data as a leading independent variable, wherein a dependent variable of the function has an upper limit and a lower limit in a value range of the leading independent variable, and the dependent variable of the function monotonically tends to the upper limit or the lower limit along with the change of the leading independent variable. Since the cold head efficiency generally reflects on the liquid helium pressure value, for example, when the cold head efficiency is reduced, the liquid helium pressure may not be effectively controlled, and the change of the liquid helium pressure has a periodic characteristic, therefore, the time characteristic of the liquid helium pressure can effectively reflect the change situation of the liquid helium pressure, and by associating the time characteristic of the liquid helium pressure with the cold head efficiency and mapping the cold head efficiency value through the time characteristic, the quantification of the cold head efficiency can be realized, the realization is simple, the situation of the cold head efficiency can be effectively reflected, and the reference value is very high.

In some embodiments, the extracted time characteristic is a fall time of the liquid helium pressure or a cycle time of the liquid helium pressure, wherein, in particular embodiments, the defined function may be specifically set to have the following characteristics: when the input fall time or cycle time approaches zero, the output cold head efficiency approaches one; when the input falling time or cycle time approaches infinity, the output cold head efficiency approaches zero; the function decreases monotonically in the middle. The liquid helium pressure data has the characteristic of periodic variation, under the ideal condition, the time characteristic of the liquid helium pressure in each period should be kept basically unchanged, but under the actual condition, along with the loss of the cold head, the characteristic can be changed, the cold head efficiency is reflected through the function of the liquid helium pressure reduction time or the period time, and the change of the cold head efficiency can be accurately quantified.

In a preferred embodiment, the function may be implemented as:

E＝a*exp(-b*(T+c))/(d+e*exp(-f*(T+g)))，

wherein E is a cold head efficiency calculation index, T is the falling time of the liquid helium pressure, and a, b, c, d, E, f and g are parameters to be solved. Based on the defined function characteristics, the specifically selected mapping function has countless implementation examples in mathematics, and the function has more adjustable parameters, so that the parameters are easy to select to obtain very high fitting accuracy.

In some embodiments, the configured mapping function further includes an additional argument, where the additional argument has an adjusting effect on the output result of the function, and does not affect the characteristic of the function, i.e. is only used for adjusting the magnitude of the output value of the dependent variable, and for example, in the above function formula, the additional argument may be added to the function in the following two ways: mode one is E ═ a × exp (-b · (h1 × T + h2 × x + c))/(d + E × exp (-f · (h1 × T + h2 × x + g))) and mode two is E ═ h1 · (a × exp (-b (T + c))/(d + E × exp (-f (T + g))) + h2 × x. In this way, according to the requirement, a secondary factor (for example, the secondary factor x in the given example, where x may be any characteristic, such as the cold head temperature, etc.) affecting the cold head efficiency may be added to adjust the output value of the function, that is, the cold head efficiency value, and the additional independent variable is only used to adjust the magnitude of the fixed value taken by the dependent variable, and the characteristic of the function is not affected, that is, the characteristic of the function is only represented by the dominant independent variable, so that the output cold head efficiency may be more in line with the actual situation, that is, the result of index representation may be more accurate by adjusting the additional independent variable.

The method for quantitatively describing the cold head efficiency is realized by the following steps:

extracting time characteristics of liquid helium pressure data, and mapping the extracted time characteristics into cold head efficiency through a function;

the mapped cold head efficiency value has an upper limit and a lower limit in a value range of the time characteristic, and the change of the cold head efficiency value along with the time characteristic monotonously tends to the upper limit or the lower limit. Therefore, quantitative description of the cold head efficiency can be realized by extracting the time characteristics of the liquid helium pressure data, and the quantitative description method is very accurate because the cold head efficiency is generally reflected on the liquid helium pressure value in practical application.

In some embodiments, wherein the time characteristic of the extraction is a fall time of the liquid helium pressure or a cycle time of the liquid helium pressure. In a particular implementation, the mapping function may be implemented as an S-type function, which may be, for example, a logistic function, a Gompertz function, an error function, or the like. Because the change of the liquid helium pressure has the periodic characteristic, the calculation is simple by taking the falling time or the periodic time as the time characteristic, and the mapping function can be realized by selecting a common S-shaped function model according to the function characteristic, so the realization is simple.

In some embodiments, the determined mapping function is specific to satisfying the following properties: when the input fall time or cycle time approaches zero, the output cold head efficiency approaches one; when the input falling time or cycle time approaches infinity, the output cold head efficiency approaches zero; the function decreases monotonically in the middle. Therefore, the mapping function can be determined through the function characteristics, the quantized value of the cold head efficiency can be calculated by using the pressure drop time or the cycle time of the liquid helium, the actual situation is met, and the quantized result is accurate.

In some embodiments, the function is generated by: defining a mapping function initial model according to the properties satisfied by the function; acquiring historical data for analysis, and determining an input sample set; and obtaining parameters to be solved of the initial model in a curve fitting mode according to the input sample set to generate a determined function model. The input sample set is determined through the historical data and the function characteristics, the obtained samples are more in line with the actual situation, so that the fitted parameters to be solved are more accurate, the determined function model is more accurate, the cold head efficiency value calculated by the calculation index is more in line with the actual situation, and the utilization value of the calculation index is high.

In some embodiments, obtaining historical data for analysis and determining the set of input samples comprises: acquiring full life cycle historical data of the cold head; acquiring a first boundary sample according to the full life cycle historical data and the property met by the function; acquiring a second boundary sample according to the full life cycle historical data and the property met by the function; and acquiring a random input sample according to the full life cycle historical data and the property satisfied by the function. According to the historical data and the function characteristics, two boundary values are simultaneously obtained to serve as samples, the intermediate random samples are obtained, the distribution of the sample set can be more uniform, and the parameter values to be calculated through the sample set are more accurate.

In some embodiments, the defined mapping function initial model is:

E＝a*exp(-b*(T+c))/(d+e*exp(-f*(T+g)))，

wherein E is a cold head efficiency calculation index, T is the falling time of the liquid helium pressure, and a, b, c, d, E, f and g are parameters to be solved. The function model has the characteristic of more adjustable parameters, and the parameters are easy to select so as to obtain very high fitting precision.

In some embodiments, the initial model of the mapping function is defined as E ═ exp (a × T + b)/(1+ exp (a × T + b)),

wherein E is a cold head efficiency calculation index, T is the falling time of the liquid helium pressure, and a and b are parameters to be solved. The function model has the characteristic of few parameters, can be fitted by needing fewer sampling points, has a simple formula and definite parameter meaning, and if the parameter a is used for controlling the descending rate of the curve and the parameter b is used for horizontally translating the curve.

The method for calculating the cold head efficiency comprises the following steps:

acquiring and storing liquid helium pressure threshold values corresponding to the turning on and turning off of the heater respectively;

calculating the falling time of the liquid helium pressure according to the real-time liquid helium pressure information and the liquid helium pressure threshold value;

generating cold head efficiency according to the drop time of the liquid helium pressure and the calculation index;

wherein the calculation index is the cold head efficiency calculation index or the function.

Because the liquid helium pressure threshold values corresponding to the turning on and off of the heater respectively correspond to the threshold values at which the liquid helium pressure ends to drop and the threshold values at which the liquid helium pressure begins to drop, when the real-time liquid helium pressure value reaches the two threshold values, it is indicated that the liquid helium pressure ends to drop and begins to drop respectively, the occurrence time at this time is obtained, and the drop time of the liquid helium pressure in the drop period can be obtained, so that the corresponding value of the cold head efficiency in the drop period can be calculated according to the mapping function in the previously defined calculation index, and the quantification of the cold head efficiency is realized.

In some embodiments, calculating the fall time of the liquid helium pressure from the real-time liquid helium pressure value and the liquid helium pressure threshold value comprises:

continuously acquiring the latest real-time liquid helium pressure value, comparing the latest real-time liquid helium pressure value with the liquid helium pressure threshold value for closing the heater until the current real-time liquid helium pressure value is greater than or equal to the liquid helium pressure threshold value for closing the heater, and recording the occurrence time T1 of the current real-time liquid helium pressure value;

continuously acquiring the latest real-time liquid helium pressure value, comparing the latest real-time liquid helium pressure value with the liquid helium pressure threshold value for opening the heater until the current real-time liquid helium pressure value is less than or equal to the liquid helium pressure threshold value for opening the heater, and recording the occurrence time T2 of the current real-time liquid helium pressure value;

the falling time of the liquid helium pressure is calculated according to the recorded occurrence times T1 and T2. The latest real-time liquid helium pressure value obtained continuously is compared with the threshold value for closing the heater, the time when the real-time liquid helium pressure begins to drop is found out, then the latest real-time liquid helium pressure value obtained next is compared with the threshold value for opening the heater, the time when the real-time liquid helium pressure finishes dropping is found out, the difference between the two times is obtained, the dropping time of the liquid helium pressure can be obtained, the calculation is simple, the physical law is met, and the result is accurate.

The invention provides a method for monitoring cold head efficiency, which comprises the following steps:

acquiring and storing liquid helium pressure threshold values corresponding to the turning on and turning off of the heater respectively;

calculating the pressure drop time of the liquid helium according to the real-time liquid helium pressure information and the liquid helium pressure threshold value, and storing the real-time liquid helium pressure information and the liquid helium pressure drop time;

generating cold head efficiency data according to the falling time of the liquid helium pressure and the calculation index for storage;

generating a drawing curve according to the stored data information and outputting the drawing curve;

wherein the calculation index is the cold head efficiency calculation index or the function,

and drawing a curve which is one or the combination of more than two of a cold head efficiency curve, a cold head efficiency annual average line, a cold head efficiency monthly average line, a cold head efficiency week average line, a real-time liquid helium pressure curve and a liquid helium pressure drop time curve.

Through the liquid helium pressure value storage that will acquire in real time, and the liquid helium pressure decline time that will calculate and cold head efficiency value storage, can be according to user's demand, with time and corresponding element (like liquid helium pressure, liquid helium pressure decline time, cold head efficiency) as the coordinate axis, draw corresponding curve output and show, make the user can see the situation of change of liquid helium pressure and cold head efficiency directly perceivedly, in order to carry out corresponding processing according to the situation of change, the result is simple directly perceived easily, and can realize real-time supervision, it is very swift and convenient, improve the monitoring efficiency to cold head efficiency.

The invention provides another method for monitoring the efficiency of the cold head, which comprises the following steps:

setting early warning strategy storage;

acquiring and storing liquid helium pressure threshold values corresponding to the turning on and turning off of the heater respectively;

calculating the falling time of the liquid helium pressure according to the real-time liquid helium pressure information and the liquid helium pressure threshold value;

generating cold head efficiency according to the reduction time of the liquid helium pressure and the calculation index, and generating cold head efficiency alarm information according to the early warning strategy and the cold head efficiency to output;

wherein the calculation index is the cold head efficiency calculation index or the function.

Through setting up the early warning tactics, can carry out the early warning according to the demand and remind cold head efficiency, better satisfying user's demand improves user monitoring efficiency to in time remind when reaching the early warning condition conveniently, avoid bigger loss.

In some embodiments, the early warning strategies include a fixed threshold warning strategy and a mean-shift warning strategy. The fixed threshold value alarm strategy can realize the direct early warning according to the set threshold value condition, the mean value fluctuation alarm strategy can realize the early warning through the parallel comparison with the mean value in the same period, the two early warning strategies are simple to realize and have higher conformity with the actual life cycle of the cold head, therefore, the early warning reminding under the two strategies is met, and the reference value is higher.

In some embodiments, wherein the another monitoring method further comprises: and storing the real-time liquid helium pressure information, the liquid helium pressure reduction time and the generated cold head efficiency data, and generating and outputting a drawing curve according to the stored information, wherein the drawing curve is one or the combination of more than two of a cold head efficiency curve, a cold head efficiency annual average line, a cold head efficiency monthly average line, a cold head efficiency week average line, a real-time liquid helium pressure curve and a liquid helium pressure reduction time curve. The early warning strategy is combined with the output display of the drawn curve, different requirements of different users can be met, and user experience is improved.

In addition, the invention also provides a cold head efficiency monitoring system which comprises an information acquisition module and a system platform, wherein the information acquisition module is used for acquiring the liquid helium pressure threshold value and the real-time liquid helium pressure information and outputting the information to the system platform; the system platform comprises a calculation index configuration module, a storage module and a control module, wherein the calculation index configuration module is used for configuring the cold head efficiency calculation index and storing the cold head efficiency calculation index into the storage module; the index parameter determining module is used for acquiring an input sample set according to historical data, calculating indexes according to the input sample set and the configured cold head efficiency, and generating and outputting a parameter value to be obtained; the cold head efficiency calculation module is used for generating cold head efficiency according to the liquid helium pressure threshold value, the real-time liquid helium pressure information, the calculation index and the generated parameter value to be solved; wherein the calculation index is the cold head efficiency calculation index or the function. The system can realize automatic analysis and calculation of cold head efficiency, data acquisition and calculation of liquid helium pressure reduction time are all obtained by automatic analysis and calculation of the system, a user does not need to carry out any manual processing, only index functions meeting characteristics need to be configured according to requirements, the analysis efficiency of cold head working conditions is improved, manual errors are reduced, the calculation and analysis of the cold head efficiency of multiple devices can be realized, and the processing efficiency is very high.

In some embodiments, the system further comprises a user interaction module for receiving an external input, generating an early warning configuration information store according to the external input; the system platform also comprises an early warning module which is used for generating and outputting an alarm message according to the generated cold head efficiency and the stored early warning configuration information. Therefore, the user can set the early warning condition according to the requirement, the system alarms according to the early warning condition after calculating the cold head efficiency, the noise of the alarm message is reduced, and only the alarm message meeting the requirements of the user is provided, so that the reference value of the early warning message is high, and the user experience and the processing efficiency are greatly improved.

In some embodiments, the system further comprises a display module, and the system platform further comprises a curve drawing module for acquiring the stored data information according to the request to generate a drawn curve output; the display module is used for displaying the alarm message and drawing a curve; and drawing a curve which is one or the combination of more than two of a cold head efficiency curve, a cold head efficiency annual average line, a cold head efficiency monthly average line, a cold head efficiency week average line, a real-time liquid helium pressure curve and a liquid helium pressure drop time curve. By means of displaying alarm information and/or displaying a drawing curve, a user can check calculation and analysis results conveniently, so that corresponding treatment measures can be taken timely based on specific conditions of cold head efficiency, and loss is reduced.

Drawings

FIG. 1 is a flow diagram of a method for determining a function in a computational index according to one embodiment of the invention;

FIG. 2 is a flowchart of a method for determining a sample set of inputs according to one embodiment of the present invention;

FIG. 3 is a flow chart of a method of calculating cold head efficiency according to one embodiment of the present invention;

FIG. 4 is a flowchart of a method of monitoring cold head efficiency according to an embodiment of the present invention;

FIG. 5 is a flow chart of a method of monitoring cold head efficiency according to another embodiment of the present invention;

FIG. 6 is a schematic diagram of a frame structure of a cold head efficiency monitoring system according to an embodiment of the present invention;

fig. 7 is a schematic structural diagram of a frame of a cold head efficiency monitoring system according to another embodiment of the present invention.

Detailed Description

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

The invention realizes the quantification of the efficiency of the cold head by newly defining the cold head efficiency calculation index for the cold head, wherein the provided cold head efficiency calculation index represents the working capacity of the cold head. Since the change of the liquid helium pressure data has a periodic characteristic, the cold head efficiency is mainly characterized by extracting the time characteristic of the liquid helium pressure data in practical implementation, and particularly, the cold head efficiency can be configured to be mainly represented by the reduction rate or the change period of the liquid helium pressure, and based on this, the cold head efficiency calculation index can be defined as a function of the reduction time (unit may be, for example, hour) or the cycle time (i.e., the time required for the liquid helium pressure to pass through one change period), namely, a function for mapping the reduction time or the cycle time of the liquid helium pressure to the value of the cold head efficiency. The function may be configured to take the time characteristic of the extracted liquid helium pressure data as a dominant independent variable, the dependent variable of the function changes with the change of the dominant independent variable when the time characteristic changes, and the dependent variable is bounded, that is, the dependent variable includes an upper limit and a lower limit, so that the function has a characteristic that the dependent variable respectively tends to a fixed real value at both ends with the change of the dominant independent variable in a value range and the dependent variable shows a middle monotonic change with the change of the dominant independent variable. Preferably, the function may be implemented by an S-type function, such as a logistic function, Gompertz function, error function, etc., or by other functions that conform to this property. In a specific implementation, the function may be implemented, for example, with the following features: when the pressure drop time or the cycle time of the input liquid helium approaches 0, the output cold head efficiency approaches 1; when the pressure drop time or the cycle time of the input liquid helium approaches infinity, the output cold head efficiency approaches 0; the function decreases monotonically in the middle. Thus, the function can be implemented by selecting any mapping value as a monotonically decreasing function within the interval [0,1 ].

After the cold head efficiency calculation index is defined, the cold head efficiency can be quantized by determining an initial model of a mapping function and a parameter of a function to be solved and generating a value of the parameter to be solved through training. Fig. 1 shows a method for determining a function model, and as shown in fig. 1, taking an example that an extracted time feature is a drop time of liquid helium pressure and a function parameter to be solved is calculated by curve fitting based on historical data, the method includes the following steps:

step S101: and selecting a mapping function according to the function characteristics of the calculation indexes.

After the characteristics of the mapping function used for calculating the index are determined, the basic model of the mapping function can be clarified according to the characteristics and the mathematical knowledge, that is, a specific mapping function basic model is selected or defined. In view of the above-mentioned features, there are many choices in mathematics, and the embodiments of the present invention are not exhaustive, and in a preferred embodiment of the present invention, a basic mapping function model determined may be, for example, as follows:

E＝a*exp(-b*(T+c))/(d+e*exp(-f*(T+g)))

wherein T represents the pressure drop time of the liquid helium, the unit is hour, E represents the cold head efficiency, and a, b, c, d, E, f and g are all function parameters to be solved.

Step S102: and acquiring historical data for analysis, and determining an input sample set.

According to the embodiment of the invention, the function parameter to be solved is solved in a curve fitting mode, so that certain points (T, E) can be fixed to serve as input values of a curve fitting algorithm according to observation of historical values, and then the function parameter to be solved is obtained through the curve fitting algorithm. The process of fixing the value points according to the observation of the historical values is a process of determining an input sample set, and the input sample set can be determined by combining the analysis of the historical data and the experience of a device engineer. Fig. 2 shows a process of determining an input sample set according to an embodiment, taking the determined input sample set as five fixed value points such as (3,0.98), (6,0.9), (12,0.7), (24,0.2), (48,0.01), as shown in fig. 2, the method includes the following steps:

step S1021: and acquiring the full life cycle historical data of the cold head.

Firstly, collecting and storing full life cycle data of one or more cold heads of the same type, wherein the full life cycle data refers to: all liquid helium pressure values during the period from the cold head installation to the replacement at the end of life are a plot of liquid helium pressure versus time. The collecting of the full life cycle data of the cold head may be, for example, acquiring corresponding data from all manufacturers or/and providing corresponding data by different maintenance engineers, or acquiring corresponding data from a network through a page grabber to perform big data analysis, or analyzing the data from device log files applied to different devices by the cold head through a feature matching algorithm.

Step S1022: and acquiring a first boundary sample according to the full life cycle historical data and the function characteristics.

The liquid helium pressure drop time T immediately after the cold head is installed is obtained according to the collected full life cycle data, and the specific implementation manner may be that the average drop time of one week of the newly installed cold head (that is, the average drop time of one week from the day of cold head installation) is calculated, the average drop time of one week of the new installation is used as the liquid helium pressure drop time of the newly installed cold head, for example, the average drop time of one week of the newly installed cold head is analyzed to be three hours, it indicates that the newly installed cold head requires three hours to reduce the liquid helium pressure from the upper limit threshold to the lower limit threshold, that is, the liquid helium pressure drop time T of the newly installed cold head is three hours, since the efficiency of the newly installed cold head is the best, the value of the cold head efficiency corresponding to the liquid helium pressure drop time at this time may be defined to be close to 1 according to the functional characteristic of the defined index, that is, that the mapping interval is [0,1], for example, defined as 0.98, then the first example of the boundary can be determined as a fixed value point (3,0.98), where 3 is the fall time of the liquid helium pressure and 0.98 is a value indicative of the efficiency of the cold head just installed. In a specific implementation, the calculation time period of the average falling time can be freely selected according to requirements or cold head characteristics, for example, for a cold head with a break-in period, a period of time, such as one month, is required to pass, and after the falling time is stable each time, the liquid helium pressure falling time of a newly installed cold head within a certain period is acquired and the average falling time is calculated.

The liquid helium pressure decrease time may be calculated by comparing the real-time liquid helium pressure value with an upper threshold and a lower threshold of the liquid helium pressure, when the real-time liquid helium pressure value is not less than the upper threshold, taking the occurrence time of the current liquid helium pressure value as the time when the liquid helium pressure starts to decrease, then comparing the real-time liquid helium pressure value with the lower threshold, when the real-time liquid helium pressure value is not higher than the lower threshold, taking the occurrence time of the current liquid helium pressure value as the time when the liquid helium pressure stops decreasing, and then calculating the difference between the time when the liquid helium pressure stops decreasing and the time when the liquid helium pressure starts to decrease, so as to obtain the decrease time of the liquid helium pressure. Since it is indicated that the liquid helium pressure tends to decrease later when the liquid helium pressure is at or above the upper threshold value, and it is indicated that the liquid helium pressure tends to increase later when the liquid helium pressure is at or below the lower threshold value, the time period between the two is the decreasing time of the liquid helium pressure. And after the current descending time is calculated, continuously judging the real-time liquid helium pressure, namely judging whether the real-time liquid helium pressure is not less than an upper limit threshold value or not, recording the occurrence time until the real-time liquid helium pressure which is greater than or equal to the upper limit threshold value is detected, judging whether the real-time liquid helium pressure is not greater than a lower limit threshold value or not until the real-time liquid helium pressure which is less than or equal to the lower limit threshold value is detected, and recording the occurrence time, thereby obtaining the descending time of the liquid helium pressure of another round. According to the method for calculating the liquid helium pressure reduction time, the real-time liquid helium pressure value is compared with the upper limit threshold value to find the liquid helium pressure generation time about to show the descending trend, and then the new real-time liquid helium pressure value is compared with the lower limit threshold value to find the liquid helium pressure generation time about to show the descending trend.

Step S1023: and acquiring a second boundary sample according to the full life cycle historical data and the function characteristics.

Acquiring the pressure drop time T of the liquid helium before cold head replacement according to the collected full life cycle data, for example calculating the average of the time to fall of the liquid helium pressure the day before the replacement based on the collected full life cycle data, for example, analysis of the cold head prior to replacement (i.e., the cold head to be replaced) may take 48 hours to lower the liquid helium pressure from the upper threshold to the lower threshold, the liquid helium pressure drop time T for the old cold head to be replaced may be set to 48 hours, because the efficiency of the cold head to be replaced is the worst, the value of the cold head efficiency corresponding to the liquid helium pressure reduction time at the moment can be defined to be close to 0 according to the function characteristics of the defined index, e.g., defined as 0.01, from which a second sample of the boundary can be determined as a fixed value point (48,0.01), where 48 is the fall time of the liquid helium pressure and 0.01 is an indication of the efficiency of the coldhead to be replaced.

Step S1024: and acquiring random samples according to the full life cycle historical data.

In the life cycle of the cold head between the first boundary sample and the second boundary sample, a plurality of samples can be randomly selected, for example, three points are randomly selected, the time for reducing the liquid helium pressure of the three points, namely the time for reducing the liquid helium pressure from the upper limit threshold to the lower limit threshold, is calculated according to the historical data of the full life cycle, the cold head efficiency corresponding to the three points is empirically estimated, and the corresponding characteristic values are determined, so that three random samples are obtained. Taking the random selection of three points according to the average distribution of the liquid helium pressure drop time as an example, in the selected random samples, the liquid helium pressure drop time can be respectively specified to be 6 hours, 12 hours and 24 hours, and the characteristic values of the cold head efficiency of the three points are respectively defined to be 0.9, 0.7 and 0.2 according to the characteristic that the function is monotonically decreased in the middle, so that the three samples in the middle can be obtained to be fixed value points (6,0.9), (12,0.7) and (24, 0.2).

Step S103: and generating function parameters to be solved by a curve fitting mode according to the input sample set, and training a function model.

After the five fixed value points obtained as the input sample set are obtained, the function parameter to be obtained is calculated by curve fitting, specifically, the five fixed value points obtained are used as the input value points of the curve fitting algorithm, so as to obtain the output values of the function parameter to be obtained, where a is 0.6819, b is 0.155, c is 0.8541, d is 0.06271, e is 0.6632, f is 0.1688, and g is 1.281. After the function parameters are determined, a trained function model, namely a function formula with the determined parameters to be solved, is obtained. The cold head efficiency value can then be calculated and monitored in real time according to the function model in which the parameters to be solved are determined.

It should be noted that a, b, c, d, e, f, and g are all to-be-solved function parameters, and the to-be-solved parameters of the functions are different according to different selected function formulas, so that the embodiment of the present invention is not considered as a limitation on the function formulas and the to-be-solved function parameters, and all the implementation schemes that a function formula is selected based on the above function characteristics and the to-be-solved function parameter calculation method provided by the embodiment of the present invention is used to calculate the function parameters to obtain a specific function model are considered as technical schemes based on the present invention, and all the implementation schemes are within the protection scope of the present invention. After the function model is trained by the method, the liquid helium pressure drop time can be input according to the determined function formula and function parameters, and the cold head efficiency corresponding to the corresponding drop time is obtained, so that the quantification of the cold head efficiency is realized.

The embodiment of the invention mainly takes the time characteristic as the falling time of the liquid helium pressure as an example, and describes a function determination method of the calculation index of the cold head efficiency, the method is also suitable for other time characteristics of the liquid helium pressure, such as cycle time, when the time characteristic changes, in the process of determining a function model, only the value points of other time characteristics are required to be obtained based on historical data when an input sample set is determined, the process of determining the input sample set is not changed, namely two boundary samples and a plurality of random samples are determined, and the determination mode of the value points is that the time characteristic numerical value of the corresponding sample characteristic is found firstly, then according to the determined function characteristic, a proper cold head efficiency output value is allocated to the sample according to experience, and the difference is that the extracted time characteristic is different, while the method of extracting the time characteristic numerical value is detailed below, in the process of determining the function model, it is only necessary to be able to obtain historical data, and it is not concerned how to obtain these time characteristic values. For example, in another embodiment, the function initial model may be set to E ═ exp (a × T + b)/(1+ exp (a × T + b)), where E is the index of cold head efficiency calculation and T is the time of fall or cycle time of the liquid helium pressure, and then the first boundary sample (0,1), the second boundary sample (48,0.01), and the random input samples (1,1), (12,0.8) are obtained by referring to the above implementation procedure, so that the values of the function parameters a ═ 0.5212 and b ═ 7.64 can be obtained by curve fitting, and then the cold head efficiency value can be calculated using the determined function model parameters. Since the function model of E ═ exp (a × T + b)/(1+ exp (a × T + b)) has the characteristic of few parameters, fewer sampling points are required to fit the parameters to be calculated. And the formula of the function model is simple, the meaning of the parameter is definite, for example, a is used for controlling the descending rate of the curve, b is used for translating the curve left and right, therefore, when the parameter to be solved is obtained, the sampling process can be omitted, the parameter value to be solved is manually adjusted according to the meaning of the parameter, namely, the parameter value to be solved is directly configured according to the meaning of the parameter, and the method can be effectively applied to the situation that the sampling point is not well given, and is simpler to realize.

In addition, it should be understood by those skilled in the art that the embodiment of the present invention is described by taking the main independent variable of the function as the time characteristic of the extracted liquid helium pressure as an example, in other modifications, additional independent variables may be added according to requirements to adjust the upper and lower limit values of the function, for example, a variable of the cold head temperature is added, and the cold head temperature variable and the time characteristic function of the liquid helium pressure according to the above characteristics are summed or subtracted to obtain a final cold head efficiency value; for another example, an additional argument of the liquid helium level is added, weight coefficients are assigned to the liquid helium level argument and the time characteristic function of the liquid helium pressure that meets the above-described characteristics, respectively, and a smaller weight coefficient is assigned to the liquid helium level argument, and the product of the liquid helium level argument and the weight coefficient and the product of the time characteristic function of the liquid helium pressure that meets the above-described characteristics and the weight coefficient are summed or subtracted to obtain a cold head efficiency value or the like. For example, the added additional argument is labeled x, and in the function formula of the above embodiment, the additional argument can be added to the function in the following two ways, so as to obtain a new function model as follows: mode one is E ═ a × exp (-b · (h1 × T + h2 × x + c))/(d + E × exp (-f · (h1 × T + h2 × x + g))) and mode two is E ═ h1 · (a × exp (-b (T + c))/(d + E × exp (-f (T + g))) + h2 × x. In this way, the characteristics of the obtained function are not changed, and still are changed correspondingly based on the dominant independent variable, and the influence of the additional independent variable on the function is only to adjust the magnitude of the output value of the function curve, and does not influence the change characteristics of the function.

After the calculation index of the cold head efficiency is determined, the cold head efficiency can be calculated and monitored through the determined function formula. Fig. 3 shows a method for calculating the cold head efficiency according to an embodiment, taking the calculation through the pressure drop time of the extraction liquid helium by using the above-defined function formula as an example, as shown in fig. 3, the method comprises the following steps:

step S301: and acquiring a liquid helium pressure threshold value and storing.

And a data acquisition box is arranged on the nuclear magnetic resonance equipment, and a log file of the equipment is acquired through the data acquisition box and uploaded to a cloud server. The cloud server analyzes the uploaded log file, reads liquid helium pressure threshold values respectively corresponding to heaters to be turned on and turned off from the log, for example, by setting keywords corresponding to the liquid helium pressure thresholds to be turned on and turned off, and analyzes information corresponding to the keywords from the log file in a keyword matching manner, so that the information is acquired and stored in the liquid helium pressure threshold values to be turned on and turned off, for example, a database record in the following format:

device ID

Closing heater pressure threshold

Opening a heater pressure threshold

The liquid helium pressure threshold of the heater is closed corresponding to the value of the liquid helium pressure beginning to drop, and the liquid helium pressure threshold of the heater is opened corresponding to the value of the liquid helium pressure ending to drop, so that the drop time of the liquid helium pressure can be determined by collecting the two values. In other embodiments, a sensor can be mounted on the device, and the sensor value can be directly read to obtain the liquid helium pressure threshold corresponding to the heater being turned on and off respectively.

Step S302: and acquiring real-time liquid helium pressure data information.

The liquid helium pressure data information at least comprises a real-time liquid helium pressure value and occurrence time thereof, and the real-time liquid helium pressure value and the occurrence time thereof of each device are obtained by analyzing a log file acquired by the information acquisition box through a keyword corresponding to the set liquid helium pressure value (for example, through a feature matching algorithm). The real-time acquisition can be realized by the prior art, and is not described herein again. In other embodiments, a sensor may be disposed on the device to acquire the real-time liquid helium pressure value and the occurrence time of the device. The obtained real-time liquid helium pressure values of each piece of equipment may be directly sent to step S303 for further processing, or may generate data records including the liquid helium pressure values and the occurrence times corresponding to the liquid helium pressure values according to the obtained real-time liquid helium pressure values, and store the data records, for example, database records in the following format:

device ID

Time of occurrence

Liquid helium pressure value

After storage, the determination of step S303 is achieved by traversing the stored real-time liquid helium pressure values.

Step S303: and calculating the falling time of the liquid helium pressure according to the real-time liquid helium pressure data information and the liquid helium pressure threshold value.

Taking the real-time liquid helium pressure value obtained in step S302 as an example and stored in the database, in this step, the following judgment is performed on the liquid helium pressure value stored in the obtained database:

the first step is as follows: reading the next latest liquid helium pressure value from the database, comparing the read liquid helium pressure value with a liquid helium pressure threshold value corresponding to the heater closing, and if the read liquid helium pressure value is greater than or equal to the value, recording the corresponding occurrence time T1 of the data in the database, thereby obtaining the time when the liquid helium pressure starts to drop (because the liquid helium pressure threshold value of the heater closing corresponds to the value when the liquid helium pressure starts to drop, if the real-time liquid helium pressure value is not less than the threshold value, it is indicated that the liquid helium pressure is about to drop, therefore, the occurrence time at this time can be used as the time when the liquid helium pressure starts to drop), and entering the first step; if the pressure value is less than the preset value, repeating the step (new liquid helium pressure data are inserted into the database every minute), namely acquiring the next latest liquid helium pressure value and comparing the latest liquid helium pressure value with a liquid helium pressure threshold value corresponding to the heater closing;

the second step is that: reading the next latest liquid helium pressure value from the database, comparing the read liquid helium pressure value with a liquid helium pressure threshold value corresponding to the heater being turned on, if the read liquid helium pressure value is smaller than or equal to the read liquid helium pressure threshold value, recording the corresponding occurrence time T2 of the data in the database, thereby obtaining the time when the liquid helium pressure finishes descending (because the liquid helium pressure threshold value of the heater being turned on corresponds to the value when the liquid helium pressure finishes descending, if the real-time liquid helium pressure value is not higher than the threshold value, it is indicated that the liquid helium pressure is about to stop descending, therefore, the occurrence time at this time can be used as the finish descending time of the liquid helium pressure), and entering the third step; if so, repeat this step.

The third step: the falling time T2 to T1 (in hours) is calculated from the occurrence times T1 and T2 recorded in the first step and the second step, and step S304 is performed.

Since the liquid helium pressure is periodically changed based on time, namely, the liquid helium pressure is cyclically changed from high to low and from low to high, the highest value point and the lowest value point of the liquid helium pressure are found by cyclically comparing the real-time liquid helium pressure value with the threshold value, and the occurrence time T1 of the adjacent highest value point is subtracted from the occurrence time T2 of the lowest value point, so that the falling time in a change period can be obtained.

Step S304: and calculating the index according to the pressure drop time of the liquid helium and the cold head efficiency to generate the cold head efficiency.

After the falling time is calculated in step S303, the cold head efficiency of the current equipment may be calculated through the above determined calculation index function, specifically, the current cold head efficiency E of the current equipment may be calculated by substituting the falling time T and the above determined parameters into a function formula of the calculation index. The calculated cold head efficiency may then be output or/and stored, wherein the stored data structure may be a table including the occurrence time T2 and the cold head efficiency, for example as shown in the following table:

device ID

Time

Efficiency of cold head

After the current coldhead efficiency is stored, the process may return to step S303 to continue to determine the latest real-time liquid helium pressure data.

The cold head efficiency of the plant is then calculated quantitatively by the method illustrated in fig. 3, using the calculation indices defined above. In other embodiments, the cycle time of the liquid helium pressure may be extracted to calculate the cold head efficiency by using the determined function, wherein the specific calculation method is substantially the same as the method shown in fig. 3, except that when the calculation is performed by using the cycle time of the liquid helium pressure, the cycle time of the liquid helium pressure is calculated according to the real-time liquid helium pressure value and the liquid helium pressure threshold value in step S303. Since the liquid helium pressure is periodically changed, the maximum point and the minimum point of the liquid helium pressure can be found by comparing the real-time liquid helium pressure value with the liquid helium pressure threshold value in step S303, and therefore, when the cycle time of the liquid helium pressure is calculated, the occurrence time T11 of the first maximum point of the liquid helium pressure can be found first, then the real-time liquid helium pressure value is continuously compared with the threshold value for closing the heater, the occurrence time T12 of the adjacent second maximum point is found, and the cycle time can be obtained by using T12-T11; the method can also be realized by firstly finding the occurrence time T21 of the first lowest value point of the liquid helium pressure, then continuously comparing the real-time liquid helium pressure value with the threshold value of the opening heater, finding the occurrence time T22 of the adjacent second lowest value point, and obtaining a period time from T22 to T21. After the cycle time is calculated, the cycle time is used for calculating the cold head efficiency like the cold head efficiency is calculated by using the falling time.

After the cold head efficiency of the equipment is calculated, analysis and judgment can be carried out according to the calculated quantified cold head efficiency, so that the cold head efficiency of the equipment can be monitored. Fig. 4 schematically shows a method for monitoring cold head efficiency according to another embodiment of the present invention, as shown in fig. 4, the method further includes the following steps based on the method for calculating cold head efficiency shown in fig. 3:

step S305: and drawing a curve according to the stored cold head efficiency data and outputting the curve.

And drawing a curve according to the time and cold head efficiency data records of each device stored in the database to generate and output a cold head efficiency curve, wherein the cold head efficiency curve can be specifically drawn by taking the time T2 as a horizontal axis and the cold head efficiency as a vertical axis. The drawn curve may be only a cold head efficiency curve, or may include a cold head efficiency curve, an annual average line of cold head efficiency, a monthly average line of cold head efficiency, a weekly average line of cold head efficiency, and a liquid helium pressure curve, and the specific drawn and output curve may be determined according to a request or setting of a user. The average line of the cold head efficiency may be drawn by using time as an X axis and an average value of the cold head efficiency as a Y axis, for example, a month average line of the cold head efficiency is drawn by using a month as an X axis and an average value of the cold head efficiency of each month as a Y axis, the average value of the cold head efficiency of each month may be obtained by averaging cold head efficiency data records in the month, similarly, an year average line of the cold head efficiency is drawn by using a year as an X axis and an average value of the cold head efficiency of each year as a Y axis, and the average value of the cold head efficiency of each year is obtained by averaging cold head efficiency data records in the year, and a week average line of the cold head efficiency is drawn by using a week as an X axis and an average value of the cold head efficiency of each week as a Y axis. The condition of generating the liquid helium pressure curve may be, for example, that when the user wants to further know the specific liquid helium pressure condition in a time period in which the cold head efficiency value is relatively low after obtaining the information of the cold head efficiency, the user requests to obtain the liquid helium pressure data in the time period from the database, and the occurrence time of the liquid helium pressure value is taken as an X axis, and the corresponding liquid helium pressure value is taken as a Y axis to draw the liquid helium pressure curve for output.

The efficiency condition of the cold head can be visually shown through the efficiency curve: under normal conditions, the curve fluctuates around 1, and when the cold head is abnormal, the efficiency curve has a remarkable descending trend. Therefore, a user can visually see the abnormal and fluctuating conditions of the cold head efficiency according to the efficiency curve, and the condition of the equipment can be analyzed and judged more objectively and conveniently, so that greater loss is avoided.

In other embodiments, the cold head efficiency may not be calculated, but the falling time of the liquid helium pressure is calculated only in steps S301 to S303, a timestamp corresponding to the falling time and the falling time of the liquid helium pressure is stored, and then a curve of the change of the falling time of the liquid helium pressure with time is drawn by using the timestamp as an X axis and the falling time as a Y axis according to a user request and displayed to the user.

Since the liquid helium pressure may not be effectively controlled after the cold head efficiency is reduced, whether the cold head efficiency is reduced to a certain degree, for example, below a cycle average line, a month average line, or a year average line, may be determined by detecting the cold head efficiency calculation index, and an early warning may be given when the cold head efficiency is reduced to a certain degree. Fig. 5 schematically shows a method for monitoring cold head efficiency in another embodiment of the present invention, where after the cold head efficiency is calculated, the method in this embodiment performs early warning by using data of the cold head efficiency, specifically including the following steps:

step S501: and setting an early warning strategy, and generating and storing early warning configuration information.

In order to implement reminding or early warning of the condition of the cold head efficiency according to the requirement of a user, the embodiment of the invention also provides a step of setting an early warning strategy, in the step, the user can set the early warning strategy according to the requirement or the actual condition of the equipment, the setting of the early warning strategy can be, for example, a mode of carrying out user input or user selection on a user interface, so that the background server can generate early warning configuration information for storage according to input information after receiving the input or selection of the user, and the early warning strategy can be as follows:

a single threshold, such as 0.5, is preset or set by the user;

and secondly, the user can choose to give an early warning in the unit of week, month or year, and the average value of the week, month and year is compared with the average value of the week, month and year on the day after the week, month and year.

Step S502: and acquiring a liquid helium pressure threshold value and storing.

This step is the same as the implementation of step S301, and reference may be made to the above description.

Step S503: and acquiring real-time liquid helium pressure information.

This step is the same as the implementation of S302, and reference may be made to the foregoing description.

Step S504: and calculating the falling time of the liquid helium pressure according to the real-time liquid helium pressure information and the liquid helium pressure threshold value.

This step is the same as the implementation of S303, and reference may be made to the above description.

Step S505: and calculating the index according to the pressure drop time of the liquid helium and the cold head efficiency to generate the cold head efficiency.

This step is the same as the implementation of S304, and reference may be made to the above description.

Step S506: and acquiring early warning strategy configuration information, judging the generated cold head efficiency according to the early warning configuration information, and generating and outputting alarm information according to a judgment result.

After the cold head efficiency is generated, the early warning configuration information corresponding to the device can be acquired, and the generated cold head efficiency is judged according to the content of the early warning configuration information, namely which early warning strategy the early warning strategy is, the parameter value corresponding to the early warning strategy and the like. For example, when the early warning policy is the case one in the foregoing, that is, when the early warning policy is a case of setting a fixed threshold for early warning, obtaining a parameter value corresponding to the early warning policy, that is, the set threshold is, for example, 0.5, then comparing the currently generated cold head efficiency with the threshold, and if the currently generated cold head efficiency is smaller than 0.5, indicating that the cold head efficiency is in a reduced state, at this time, generating an alarm message including an equipment ID, the cold head efficiency, and the threshold to output; in other preferred embodiments, a frequency parameter may also be set for the threshold, for example, the frequency parameter is set to 3, and when the cold head efficiency obtained three times in succession is lower than the threshold, an alarm is performed, that is, an alarm information output is generated. For another example, when the early warning policy is the second case in the foregoing, that is, when the comparison is performed according to the weekly, monthly or yearly average, first, an average value of the last week, month or year of the current cold head efficiency is calculated, that is, the occurrence time T2 of the current cold head efficiency is obtained, a record of the cold head efficiency of one week, month or year around the time point is obtained according to the occurrence time, an average value is calculated, the average value is compared with an average value of the last week (when the average value is weekly), month (when the average value is monthly) or year (when the average value is yearly), and if the average value is smaller than the average value of the last week, an alarm message output is generated, where the alarm message may be an output that includes the device ID, the current cold head efficiency, the weekly average value/monthly average value/yearly average value, and the last week average value/month average value/last year average value. In the case of mean comparison, three means may be compared at the same time, or only one of the means may be compared.

In other embodiments, the embodiments of fig. 2 and fig. 3 may be combined to generate a curve output and alarm according to an early warning policy, and the embodiments of the present invention are not limited to specific implementation combinations.

The output modes of the cold head efficiency data, the cold head efficiency curve, the alarm message and the like in the embodiment of the invention can be user pages, APP clients, WeChat, mails, short messages and the like which are output to the system.

Fig. 6 also shows a cold head efficiency monitoring system according to an embodiment of the present invention, as shown in fig. 6, the cold head efficiency monitoring system according to the embodiment of the present invention includes an information acquisition module 2 and a system platform 3, the information acquisition module 2 is directly connected to the nuclear magnetic resonance device 1, and is configured to acquire a liquid helium pressure threshold value of the device and real-time liquid helium pressure information and output the acquired information to the system platform 3, and the acquisition may be implemented in a manner of acquiring a device log by using a data acquisition box or in a manner of directly acquiring corresponding data by mounting a sensor on the device. The system platform 3 comprises a calculation index configuration module 31, an index parameter determination module 32 and a cold head efficiency calculation module 33, wherein the calculation index configuration module 31 is configured to configure cold head efficiency calculation index storage, the configured calculation index is a function of liquid helium pressure drop time, and the configured function has the following characteristics: when the pressure drop time of the input liquid helium approaches to 0, the output cold head efficiency approaches to 1; when the pressure drop time of the input liquid helium approaches infinity, the output cold head efficiency approaches 0; the function decreases monotonically in the middle. The calculation index may be configured as E ═ a × exp (-b × T + c))/(d + E × exp (-f (T + g))), where T represents the liquid helium pressure drop time in hours, E represents the cold head efficiency, and a, b, c, d, E, f, and g are all parameters of the function to be calculated. The index parameter determining module 32 is configured to obtain an input sample set according to the historical data, calculate an index according to the input sample set and the configured cold head efficiency, and generate a parameter value to be calculated to be output, so that a determination model of a function can be obtained by calculating a function configured and stored in the index configuration module 31 and a parameter to be calculated obtained in the module, so as to be used for quantitative calculation of the cold head efficiency, where the implementation process of obtaining the input sample set and generating the parameter to be calculated may refer to the description in the foregoing method section. The cold head efficiency calculation module 33 is configured to generate the cold head efficiency according to the liquid helium pressure threshold value, the real-time liquid helium pressure information, the calculation index, and the generated parameter value to be obtained, where the liquid helium pressure threshold value and the real-time liquid helium pressure information are used to calculate the liquid helium pressure drop time, and the specific calculation method refers to the foregoing description. After the liquid helium pressure drop time is calculated, the liquid helium pressure drop time can be used as an input value by using a determined function model, namely, the stored calculation index and the generated parameter to be solved, and the cold head efficiency value output is calculated.

Fig. 7 shows a cold head efficiency monitoring system according to another embodiment of the present invention, which differs from the system shown in fig. 6 only in that the system according to the embodiment of the present invention further includes a user interaction module 4 for receiving an external input and generating an early warning configuration information storage according to the external input; the system platform 3 further includes an early warning module 34 for generating an alarm message output according to the generated cold head efficiency and the stored early warning configuration information. In addition, the system of the embodiment of the present invention further includes a display module 5, and the system platform further includes a curve drawing module 35, configured to obtain the stored data information according to the request, and generate a drawing curve for output; the display module 5 is used for displaying the alarm message and drawing a curve, and can be a user page, an APP client, a WeChat, an email, a short message and the like of the system. Wherein, the curve is drawn as one or the combination of more than two of a cold head efficiency curve, a cold head efficiency annual average line, a cold head efficiency monthly average line, a cold head efficiency week average line, a real-time liquid helium pressure curve and a liquid helium pressure drop time curve. The user interaction module 4 and the display module 5 may both be located on a user terminal, for example, in an APP client, or may be a user interface or a user page provided by the system platform 3. The early warning configuration information can be stored on the user terminal, the system platform 3 sends the generated cold head efficiency to the user terminal, the user terminal acquires the early warning configuration information for judgment, and the generated warning information is output to the display module 35 for display when the early warning configuration information meets the early warning condition; or the warning information may be stored in the system platform 3, that is, after the user interaction module 4 acquires the set warning information, the warning information is sent to the system platform 3 to store the warning configuration information, so that the system platform 3 directly compares the generated cold head message with the stored warning configuration information to determine whether the warning information needs to be generated and output to the display module 35. The specific implementation processes of performing the early warning and drawing the curve can refer to the description of the method part, and are not described herein again.

The system platform in the embodiment of the invention can be deployed on a special server or a cloud server, and when the system platform is deployed on the cloud server, data sharing and system sharing can be realized, and the maintenance cost is reduced. Moreover, the system on the cloud server can collect more shared data information, so that the accuracy of historical data analysis is improved, and an input sample set which is more in line with the actual situation can be obtained.

What has been described above are merely some embodiments of the present invention. It will be apparent to those skilled in the art that various changes and modifications can be made without departing from the inventive concept thereof, and these changes and modifications can be made without departing from the spirit and scope of the invention.