阅读说明：本技术 用于传感器异常的诊断方法、装置、电子设备和存储介质 (Diagnostic method and device for sensor abnormality, electronic device, and storage medium ) 是由 宋岩磊 褚玉刚 孙建玲 于 2020-11-27 设计创作，主要内容包括：本发明属于传感器校核技术领域,具体公开了一种用于传感器异常的诊断方法、装置、电子设备和存储介质,其中,所述方法包括：S1：获取直供供热系统中各传感器采集到的实时传感器数据；S2：基于直供供热系统的逻辑拓扑网络建立的校核公式,判断所述实时传感器数据是否满足所述校核公式；S3：若不满足,则诊断所述实时传感器数据对应的传感器异常；S4：输出所述直供供热系统中传感器异常的位置。本发明将传感器采集的数据输入建立的守恒校核公式中进行检查,根据数据是否满足该公式来输出异常数据对应传感器的信息,以便于维修人员可以快速确认异常传感器的位置,提高现场检修的效率。(The invention belongs to the technical field of sensor checking, and particularly discloses a method and a device for diagnosing sensor abnormity, electronic equipment and a storage medium, wherein the method comprises the following steps: s1: acquiring real-time sensor data acquired by each sensor in the direct heating system; s2: judging whether the real-time sensor data meets a check formula or not based on the check formula established by a logic topology network of the direct supply heating system; s3: if not, diagnosing sensor abnormity corresponding to the real-time sensor data; s4: and outputting the abnormal position of the sensor in the direct heating system. The invention inputs the data collected by the sensor into the established conservation check formula for checking, and outputs the information of the sensor corresponding to the abnormal data according to whether the data meets the formula, so that maintenance personnel can quickly confirm the position of the abnormal sensor, and the field maintenance efficiency is improved.)

1. A method of diagnosing sensor anomalies in a direct-fed heating system, comprising:

s1: acquiring real-time sensor data acquired by each sensor in the direct heating system;

s2: judging whether the real-time sensor data meets a check formula or not based on the check formula established by a logic topology network of the direct supply heating system;

s3: if not, diagnosing sensor abnormity corresponding to the real-time sensor data;

s4: and outputting the abnormal position of the sensor in the direct heating system.

2. The method for diagnosing abnormality of a sensor in a direct-supply heating system according to claim 1, wherein the step S1 includes: and acquiring real-time boiler hot water flow and real-time branch hot water flow which are acquired by a flow sensor in the direct heating system.

3. A method of diagnosing sensor abnormalities in a direct-supply heating system according to claim 2, characterized in that said check formula includes: a mass conservation check formula;

the step S2 specifically includes:

the method comprises the steps of judging whether the real-time boiler hot water flow and the real-time branch hot water flow meet a mass conservation check formula based on the mass conservation check formula established by a logic topology network of a direct supply heating system, wherein the mass conservation check formula specifically comprises a first calculation formula:

in the formula: g_b,iDenotes the boiler Hot Water flow rate, G, of number i_T,jDenotes the branch hot water flow, numbered j, and ε 1 is the known first experimental deviation.

4. The method for diagnosing abnormality of a sensor in a direct-supply heating system according to claim 1, wherein the step S1 includes:

obtaining the flow of boiler hot water collected by a flow sensor in a direct supply heating system;

and acquiring the boiler outlet water temperature, the boiler return water temperature and the boiler branch heating load which are acquired by a temperature sensor in the direct heating system.

5. The method for diagnosing abnormality of a sensor in a direct-supply heating system according to claim 4, wherein the check formula includes: an energy conservation check formula;

the step S2 specifically includes:

the method comprises the following steps of establishing a boiler output calculation formula based on the physical structure of the boiler, determining the boiler output of each boiler by using the hot water flow of the boiler, the outlet water temperature of the boiler and the return water temperature of the boiler, wherein the boiler output calculation formula specifically comprises a second calculation formula:

in the formula: q_outIndicating boiler output, G_bRepresents the boiler flow rate, m³H; ρ represents the density of circulating water in kg/m³；c_pThe constant pressure specific heat capacity of water is 4190J/(kg DEG C.), t_b,sThe temperature of boiler effluent, DEG C, t_b,rThe return water temperature of the boiler is expressed in DEG C;

the method comprises the steps of judging whether the boiler output and the boiler branch heating load meet a first energy conservation check formula based on the first energy conservation check formula established by a logic topology network of a direct supply heating system, wherein the first energy conservation check formula specifically comprises a third calculation formula:

in the formula: q_out,iDenotes the boiler output, Q, of number i_T,jDenotes the heating load of branch numbered j, Q_aTo make up the water for the system,. epsilon.2 is the known second experimental deviation.

6. The method for diagnosing abnormality of a sensor in a direct-supply heating system according to any one of claims 1 to 5, wherein the step S1 includes:

acquiring a boiler fuel calorific value acquired by a gas flowmeter in a direct supply heating system;

and acquiring the boiler flue gas heat value acquired by a flue gas sensor in the direct heating system.

7. The method for diagnosing the abnormality of the sensor in the direct-supply heating system according to claim 6, wherein the step S2 specifically includes:

and judging whether the boiler fuel heat value, the boiler flue gas heat value and the boiler output force meet a second energy conservation check formula established based on the physical structure of the boiler, wherein the second energy conservation check formula specifically comprises a fourth calculation formula:

in the formula: q_fuelExpressed as the heat value of the boiler fuel, Q_outExpressed as boiler output, Q_gasExpressed as the boiler flue gas heating value, ε 3 is the known third experimental deviation value.

8. A diagnostic device for sensor abnormality in a direct-heating system, characterized by comprising:

the data acquisition module is configured to acquire real-time sensor data acquired by each sensor in the direct heating system;

the data checking module is configured to judge whether the real-time sensor data meets a checking formula or not based on the checking formula established by a logic topology network of the direct heat supply system;

the data diagnosis module is configured to diagnose sensor abnormity corresponding to the real-time sensor data if the real-time sensor data does not meet the preset data;

an abnormality output module configured to output a position of a sensor abnormality in the direct heat supply system.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 7 are implemented when the computer program is executed by the processor.

10. A storage medium storing a computer program, characterized in that the computer program realizes the steps of the method according to any one of claims 1 to 7 when executed by a processor.

Technical Field

The present invention relates to the field of sensor calibration technologies, and in particular, to a method and an apparatus for diagnosing sensor abnormality, an electronic device, and a storage medium.

Background

In the refrigeration air-conditioning system, the sensor is used as a device for acquiring the running state of the system, which is a key basis and basis for ensuring the reliable and stable running of the system, and the higher the automation level is, the greater the dependence degree on the sensor is. Along with the operation of the system, the probability of the problems of failure, failure or degradation and the like of the sensor along with the deterioration of time and working environment is higher and higher, so that the adjustment performance and reliability of the system are reduced, and even the system cannot work normally in severe cases. Diagnosing and correcting the sensors in the system are necessary work for ensuring the accuracy of the sensors and are also the basis for realizing the normal operation of the system.

In an energy system, such as a direct heating system, there are many sensors in management of energy equipment, and whether these sensors are abnormal or not and need to be checked or not is very heavy for actual maintenance work. Therefore, how to quickly find out the sensor which may have an abnormality in the system, so as to facilitate checking and maintenance, is a technical problem faced by the current technicians.

Disclosure of Invention

The invention provides a method and a device for diagnosing sensor abnormity, electronic equipment and a storage medium, which are used for solving the problem of how to quickly diagnose the abnormal sensor in an energy system so as to facilitate maintenance.

In a first aspect, the present invention provides a method for diagnosing sensor abnormality in a direct heating system, comprising: s1: acquiring real-time sensor data acquired by each sensor in the direct heating system; s2: judging whether the real-time sensor data meets a check formula or not based on the check formula established by a logic topology network of the direct supply heating system; s3: if not, diagnosing sensor abnormity corresponding to the real-time sensor data; s4: and outputting the abnormal position of the sensor in the direct heating system.

In a second aspect, the present invention provides a diagnosis apparatus for abnormality of a sensor in a direct heating system, including: the data acquisition module is configured to acquire real-time sensor data acquired by each sensor in the direct heating system; the data checking module is configured to judge whether the real-time sensor data meets a checking formula or not based on the checking formula established by a logic topology network of the direct heat supply system; the data diagnosis module is configured to diagnose sensor abnormity corresponding to the real-time sensor data if the real-time sensor data does not meet the preset data; an abnormality output module configured to output a position of a sensor abnormality in the direct heat supply system.

In a third aspect, the present invention provides an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to the first aspect when executing the computer program.

In a fourth aspect, the present invention provides a storage medium storing a computer program which, when executed by a processor, performs the steps of the method according to the first aspect.

Compared with the prior art, the invention has the beneficial effects that: the invention utilizes the physical conservation law, such as the energy conservation law, the mass conservation law and the like, to establish a corresponding checking formula according to the logic topology network structure of the direct-supply heating system, then correspondingly inputs the sensor data acquired by the sensor in the direct-supply heating system in real time into the checking formula for checking, judges whether the real-time data meets the checking formula, and if not, judges that the sensor generating the data possibly has a fault, thereby outputting the information of the corresponding sensor, so that maintenance personnel can quickly confirm the position of the abnormal sensor, and the field maintenance efficiency is improved.

Drawings

In order to more clearly illustrate the embodiments or the prior art solutions of the present invention, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.

Fig. 1 is a flowchart of a method for diagnosing an abnormality of a sensor in a direct heating system according to an embodiment;

fig. 2 is a schematic structural diagram of a device for diagnosing sensor abnormality in a direct heating system according to an embodiment;

fig. 3 is a schematic structural diagram of an electronic device according to this embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following embodiments and accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, a flowchart of a method for diagnosing an abnormality of a sensor in a direct heating system according to this embodiment is shown.

As shown in fig. 1, the method for diagnosing the abnormality of the sensor in the direct heating system includes the following steps:

s1: acquiring real-time sensor data acquired by each sensor in the direct heating system;

s2: judging whether the real-time sensor data meets a check formula or not based on the check formula established by a logic topology network of the direct supply heating system;

s3: if not, diagnosing sensor abnormity corresponding to the real-time sensor data;

s4: and outputting the abnormal position of the sensor in the direct heating system.

In the diagnosis method, the data acquired by each sensor in the direct supply heating system (hereinafter also referred to as the system) is input into a pre-established check formula, and the check formula is established based on the logic topological network and the conservation law of the direct supply heating system, so that if the sensor is not abnormal, the acquired data of the sensor accords with the check formula; on the contrary, if the sensor has a fault, the acquired data cannot meet the check formula, so that the real-time sensor data which is not full of the check formula can be quickly determined, the corresponding sensor is determined, and the quick diagnosis of the abnormity of the sensor in the direct-supply heating system is realized.

In particular, the number and types of sensors arranged in the direct heating system are very large, and the sensors include a temperature sensor, a flow sensor, a gas flow meter, a flue gas sensor and the like. It should be understood that the purpose of arranging the sensors in the direct supply heating system is to monitor and manage the operation of the system so as to ensure the efficiency of the operation of the system.

In one example, when the sensors in the direct heating system include flow sensors, the number of the flow sensors is one or more, and each of the flow sensors is disposed at least at a position for detecting a flow rate of the boiler hot water and at a position for detecting a flow rate of the branch hot water. Thus, the step S1 may specifically include:

step S111: and acquiring real-time boiler hot water flow and real-time branch hot water flow which are acquired by a flow sensor in the direct heating system.

Furthermore, a logical network of a hot water link of the direct-supply heating system can be established by utilizing the actual topological structure of the direct-supply heating system. Thus, following the above example, the check formula may specifically include: the mass conservation checking formula, and thus the step S2 may specifically include:

step S211: and judging whether the real-time boiler hot water flow and the real-time branch hot water flow meet the mass conservation check formula or not based on a mass conservation check formula established by a logic topology network of the direct supply heating system.

Specifically, the mass conservation check formula specifically includes a first calculation formula:

wherein, in the above formula: g_b,iDenotes the boiler Hot Water flow rate, G, of number i_T,jAnd j represents the branch hot water flow rate with the number j, i and j are positive integers, and epsilon 1 is a known first experimental deviation value.

In practice, the boiler hot water flow rate of each boiler and the hot water flow rate of each branch should be equal, but the error of the flow sensor is considered, so that an error may exist according to the mass conservation law and the real-time flow data acquired by the sensor. Therefore, the first experimental error value is obtained by performing an experiment based on actual data in the case of calibration, based on the error range of the flow sensor itself. It should be understood that the first experimental error value may be an error range, or may be a specific error value, depending on the actual accuracy requirement for the field; in addition, the accuracy ranges of different flow sensors may also be different, so that the first experiment deviation value of a specific experiment may also be different, but as long as the flow sensor has a deviation in the acquired real-time flow data due to a fault according to the above first calculation formula under the determined first experiment deviation value, the first calculation formula may not be satisfied, so as to determine that the corresponding flow sensor may have an abnormality,

in addition, because the direct heat supply system comprises a plurality of boilers, each boiler corresponds to one or more water supply branches, when the real-time data acquired by the flow sensor is determined to not meet the mass conservation check formula according to the first calculation formula, only the flow sensor in the system can be determined to be abnormal, but the specific one cannot be determined. In this case, it is possible to check the real-time flow rate data of each boiler by regarding each boiler in the direct heating system as an independent system, and further determine that the upstream and downstream flow rate sensors of that boiler are abnormal, by continuing to use the above first calculation formula.

For example, the step S3 may specifically include:

step S311: if not, judging whether the real-time boiler hot water flow and the real-time branch hot water flow of each boiler in the direct heating system meet the mass conservation check formula or not;

step S312: and diagnosing the abnormality of the flow sensors corresponding to the real-time boiler hot water flow and the real-time branch hot water flow which do not meet the mass conservation check formula.

When the real-time boiler hot water flow and the real-time branch hot water flow which do not meet the mass conservation check formula are diagnosed, the flow sensor information corresponding to the real-time boiler hot water flow and the real-time branch hot water flow is only required to be output, for example, the corresponding flow sensor number or label information. That is, in step S4, outputting the abnormal position of the sensor specifically includes outputting the flow sensor information corresponding to the real-time boiler hot water flow and the real-time branch hot water flow which do not satisfy the mass conservation check formula.

In another example, in an example immediately above, when the sensors in the direct heating system further include temperature sensors, the number of the temperature sensors is one or more, and each of the temperature sensors is disposed at least at a position for detecting a boiler outlet water temperature, a boiler return water temperature, and a boiler branch heating amount. Thus, the step S1 may specifically include:

step S121: obtaining the flow of boiler hot water collected by a flow sensor in a direct supply heating system;

step S122: and acquiring the boiler outlet water temperature, the boiler return water temperature and the boiler branch heating load which are acquired by a temperature sensor in the direct heating system.

Furthermore, by utilizing the actual topological structure of the direct supply heating system, a logic network of the fuel gas, hot water and water replenishing links can be established. Thus, following the above example, the check formula may specifically include: a first energy conservation check formula. Specifically, the step S2 may include:

step S221: determining the boiler output of each boiler by using the boiler hot water flow, the boiler outlet water temperature and the boiler return water temperature based on a boiler output calculation formula established by the physical structure of the boiler;

step S222: and judging whether the boiler output and the boiler branch heating load meet the energy conservation check formula or not based on a first energy conservation check formula established by a logic topology network of the direct supply heating system.

Specifically, the boiler output calculation formula specifically includes a second calculation formula:

in the formula: q_outIndicating boiler output, G_bRepresents the boiler flow rate, m³H; ρ represents the density of circulating water in kg/m³；c_pThe constant pressure specific heat capacity of water is 4190J/(kg DEG C.), t_b,sThe temperature of boiler effluent, DEG C, t_b,rThe return water temperature of the boiler is expressed in DEG C.

The first calculation formula shows that the boiler output can be calculated after the boiler flow, the boiler outlet water temperature and the boiler return water temperature are collected. In addition, according to the second calculation formula, whether the temperature sensor in the system is abnormal or not cannot be judged, and when the flow sensor is not abnormal, the abnormal temperature sensor needs to be checked, and the check is continued by using the third calculation formula.

Specifically, the first energy conservation check formula specifically includes a third calculation formula:

in the formula: q_out,iDenotes the boiler output, Q, of number i_T,jDenotes the heating load of branch numbered j, Q_aTo make up the water for the system,. epsilon.2 is the known second experimental deviation.

The system water supplement amount can be directly collected by a flowmeter (such as a water meter) arranged on a water supplement pipe without calculation. Thus, compared to the above example, the present example may also check the temperature sensor in the system if the flow sensor is accurate.

It should be understood that when determining whether a temperature sensor is malfunctioning based on the above third calculation formula, the failure range is intelligently determined and cannot be specifically located to a specific sensor.

The second experimental deviation value in this example is the same as the first experimental deviation value, and for example, the boiler output and the amount of make-up water (i.e., the amount of make-up energy) in the system should be equal to the amount of energy in the branch heating output of the system using the law of conservation of energy. In consideration of errors existing in the temperature sensor and inevitable objective loss in the actual environment, the temperature sensor is calibrated in advance, then an experiment is carried out in the system, the boiler output minus the heat of the water supply branch is calculated, and then the boiler output is divided by the boiler output, so that a standard deviation value or deviation range is calculated and used as the second experiment deviation value.

According to the method, whether the temperature sensor where the network structure of the boiler and the water supply branch is located is abnormal or not can be detected.

In yet another example, immediately above, when the sensors in the direct heating system include a gas flow meter provided at a position for a calorific value of fuel of the boiler and a flue gas sensor provided at a position for detecting a calorific value of flue gas of the boiler, the number of the gas flow meter and the flue gas sensor is one or more. Thus, the step S1 may specifically include:

step S131: acquiring a boiler fuel calorific value acquired by a gas flowmeter in a direct supply heating system;

step S132: and acquiring the boiler flue gas heat value acquired by a flue gas sensor in the direct heating system.

Furthermore, a logical network of the fuel gas and flue gas links can be established by utilizing the actual topological structure of the direct supply heating system. Thus, following the above example, the check formula may specifically include: a second mass conservation check formula. The step S2 may specifically include:

step S231: and judging whether the heat value of the boiler fuel, the heat value of the boiler flue gas and the boiler output force meet the second energy conservation check formula or not based on a second energy conservation check formula established on the basis of the physical structure of the boiler.

Specifically, the second energy conservation check formula specifically includes a fourth calculation formula:

in the formula: q_fuelExpressed as the gross calorific value of the boiler fuel, Q_outExpressed as boiler output, Q_gasExpressed as the total heat value of the boiler flue gas, epsilon 3 is a known third experimental deviation value.

Specifically, the total heating value of the boiler fuel can be obtained by collecting flow data through a gas flow meter (e.g., a gas meter) and then multiplying the flow data by the heating value of the fuel. In addition, the total heat value of the boiler flue gas is obtained by collecting flow data by a flue gas flowmeter, collecting the temperature of the flue gas by a flue gas temperature sensor, calculating the heat value of the flue gas by the temperature of the flue gas, and multiplying the heat value of the flue gas by the heat value of the flue gas. Since the calculation and acquisition of the above parameters are conventional in the art, they are not described in detail here.

The third experimental deviation value is the same as the first experimental deviation value and the experimental deviation value in determination principle, is calibrated in advance for the sensor related to the fourth calculation formula, and is then used for performing experiments in a system to calculate a standard deviation value or a deviation range as the third experimental deviation value. Since the determination principles of the first, second and third experimental deviation values are the same, they are not described herein again.

It should be understood that, in practice, the flow sensor in the system may be detected by using the above example of the first calculation formula; the flow sensor and the temperature sensor in the system can also be detected by combining the examples of the first calculation formula, the second calculation formula and the third calculation formula; or, the abnormal conditions of the sensors in the system are sequentially checked by combining the first calculation formula, the second calculation formula, the third calculation formula and the fourth calculation formula at the same time.

For example, in an application scenario, in a first step, under the condition that the accuracy of each branch flow sensor is ensured, the accuracy of each boiler flow sensor is checked in real time according to an example of a first calculation formula; secondly, for each running boiler, the return water temperature of the hot water is the same and is equal to the total return water temperature of the hot water, and under the condition that the accuracy of the total return water temperature sensor is ensured, for example, a second calculation formula, the accuracy of the water supply temperature sensor of each boiler is checked in real time according to the same return water temperature of the hot water; thirdly, checking the accuracy of the boiler water supply temperature sensor in real time according to a third calculation formula on the basis of ensuring the accuracy of the hot water flow and the accuracy of the return water temperature sensor; and fourthly, checking the accuracy of the boiler flue gas according to the first calculation formula under the condition that the flow of the gas meter is accurate. Specifically, when the real-time data of a certain sensor is found not to satisfy the conservation equation, for example, opposite outputs of the upstream and downstream temperature sensors in the same logic topology occur, the corresponding sensor information is output by using the abnormal information of the sensor data. In practice, the maintainer can utilize the information of the sensor of output to find corresponding sensor at the scene fast and overhaul to the efficiency of overhauing has been promoted.

The principle of the sequence of checking in the above example is: (1) firstly, checking a flow sensor, and (2) checking a boiler return water temperature sensor under the condition that the flow sensor passes the check; (3) under the condition that the water supply temperature sensor and the water supply temperature sensor pass the verification, the water supply temperature sensor is verified; (4) and finally, checking the flue gas sensor (flow/temperature) under the condition that the three steps of checking are passed. The range of the abnormal sensor can be determined according to a calculation formula through the checking sequence, so that the overhauling time is shortened, and the overhauling efficiency is improved.

Further, on the basis of one general inventive concept, the following also provides an apparatus structure corresponding one-to-one to each step in the above method for diagnosing abnormality of a sensor in a direct heating system.

Fig. 2 is a schematic structural diagram of a device for diagnosing an abnormality of a sensor in a direct heating system according to this embodiment.

As shown in fig. 2, the apparatus 200 for diagnosing sensor abnormality in a direct heating system specifically includes: a data acquisition module 210 configured to acquire real-time sensor data acquired by each sensor in the direct heating system; the data checking module 220 is configured to determine whether the real-time sensor data meets a checking formula based on the checking formula established by the logic topology network of the direct heating system; a data diagnosis module 230 configured to diagnose a sensor abnormality corresponding to the real-time sensor data if the real-time sensor data does not meet the predetermined criteria; an abnormality output module 240 configured to output a location of a sensor abnormality in the direct heating system.

In some examples, the data obtaining module 210 may specifically include: the first data acquisition unit is configured to acquire real-time boiler hot water flow and real-time branch hot water flow collected by a flow sensor in the direct heating system.

In some examples, the data checking module 220 may specifically include: the first checking unit is configured to determine whether the real-time boiler hot water flow and the real-time branch hot water flow satisfy a mass conservation checking formula based on the mass conservation checking formula established by the logic topology network of the direct heating system, and the mass conservation checking formula specifically includes a first calculation formula:

in the formula: g_b,iDenotes the boiler Hot Water flow rate, G, of number i_T,jDenotes the branch hot water flow, numbered j, and ε 1 is the known first experimental deviation.

In some examples, the data obtaining module 210 may specifically include: the second data acquisition unit is configured to acquire the boiler hot water flow collected by the flow sensor in the direct heating system; and the third data acquisition unit is configured to acquire the boiler outlet water temperature, the boiler return water temperature and the boiler branch heating load acquired by the temperature sensor in the direct heating system.

In some examples, the check formula includes: and (4) energy conservation checking formula. Then, the data checking module 220 may specifically include: the boiler output calculation unit and the second checking unit are configured to be boiler output calculation formulas established based on physical structures of boilers, the boiler output calculation formulas of the boilers are determined by using the boiler hot water flow, the boiler outlet water temperature and the boiler return water temperature, and the boiler output calculation formulas specifically include the second calculation formulas:

in the formula: q_outIndicating boiler output, G_bRepresents the boiler flow rate, m³H; ρ represents the density of circulating water in kg/m³；c_pThe constant pressure specific heat capacity of water is 4190J/(kg DEG C.), t_b,sThe temperature of boiler effluent, DEG C, t_b,rThe return water temperature of the boiler is expressed in DEG C; furthermore, the second check unit is configured to determine whether the boiler output and the boiler branch heating load satisfy a first energy conservation check formula established based on a logical topology network of the direct heating system, the first energy conservation check formula including a third calculation formula:

in the formula: q_out,iDenotes the boiler output, Q, of number i_T,jDenotes the heating load of branch numbered j, Q_aTo make up the water for the system,. epsilon.2 is the known second experimental deviation.

In some examples, the data obtaining module 210 may specifically include: the fourth data acquisition unit is configured to acquire the heat value of the boiler fuel acquired by the gas flowmeter in the direct heating system; and the fifth data acquisition unit is configured to acquire the boiler flue gas heat value acquired by the flue gas sensor in the direct heating system.

In some examples, the data checking module 220 may specifically include: the third checking unit is configured to determine whether the boiler fuel calorific value, the boiler flue gas calorific value and the boiler output satisfy a second energy conservation checking formula established based on a physical structure of the boiler, and the second energy conservation checking formula specifically includes a fourth calculation formula:

in the formula: q_fuelExpressed as the heat value of the boiler fuel, Q_outExpressed as boiler output, Q_gasExpressed as the boiler flue gas heating value, ε 3 is the known third experimental deviation value.

In addition, referring to fig. 3, a schematic structural diagram of an electronic device provided in this embodiment is shown.

The electronic device may include a computer, a server, or a wechat computer system, for example, a direct heat supply system is networked based on a network, and then the steps in the method are implemented by using an internet of things server platform as an execution subject of the method shown in fig. 1.

As shown in fig. 3, the electronic device may include a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor when executing the computer program implements the steps of the above method for diagnosing sensor abnormality in a direct heating system.

On the hardware level, the electronic device comprises a processor and optionally an internal bus, a network interface and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.

The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus.

In particular, the processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory is used for storing execution instructions. In particular, a computer program that can be executed by executing instructions. The memory may include both memory and non-volatile storage and provides execution instructions and data to the processor.

In a possible implementation manner, the processor reads the corresponding execution instruction from the nonvolatile memory to the memory and then runs the corresponding execution instruction, and the corresponding execution instruction can also be obtained from other equipment, so as to form a diagnosis device for the sensor abnormality in the direct heating system on a logic level. The processor executes the execution instructions stored in the memory, so that the method for diagnosing the sensor abnormality in the direct heating system provided by any embodiment of the invention is realized through the executed execution instructions.

The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.

The embodiment of the present invention further provides a readable storage medium, where the readable storage medium stores an execution instruction, and when the stored execution instruction is executed by a processor of an electronic device, the electronic device can execute the method for diagnosing the abnormality of the sensor in the direct heating system provided in any embodiment of the present invention.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.

The embodiments of the present invention are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.