阅读说明：本技术 一种基于不同工况的采掘设备传感器数据自适应采集方法 (Mining equipment sensor data self-adaptive acquisition method based on different working conditions ) 是由 贾有生 鲍文亮 刘国鹏 王光肇 王以超 唐会成 侯林 靳明智 康永玲 李焕丽 许 于 2020-06-05 设计创作，主要内容包括：本发明涉及一种基于不同工况的采掘设备传感器数据自适应采集方法,提出一种依据数据波动大小量化分析结果,实时调整采样周期的自适应采集方法,具体为设备工作时传感器数据变化急剧,则加大采集频次；设备在待机状态时数据变化缓慢则减小采样频次,在保证有价值数据不丢失前提下,尽量减少无用数据采集量,实现了在不同工况下依据数据变化度动态调整采样周期。可大幅提高资源利用率,提升工作效率,对于实现设备智能控制、故障诊断及预测具有很大作用。(The invention relates to a self-adaptive acquisition method of sensor data of mining equipment based on different working conditions, and provides a self-adaptive acquisition method for adjusting a sampling period in real time according to a data fluctuation quantitative analysis result, in particular to a method for increasing the acquisition frequency when the sensor data changes sharply when the equipment works; when the device is in a standby state, the sampling frequency is reduced if the data change is slow, the amount of collected useless data is reduced as much as possible on the premise of ensuring that valuable data are not lost, and the sampling period is dynamically adjusted according to the data change degree under different working conditions. The resource utilization rate can be greatly improved, the working efficiency is improved, and the intelligent control, fault diagnosis and prediction of equipment are realized.)

1. A self-adaptive data acquisition method for mining equipment sensors based on different working conditions is characterized by comprising the following steps:

calculating the average data variation in a first preset time interval and the average data value in a second preset time interval aiming at any sensor data in the mining equipment sensor data collected in real time;

determining the data change degree of the corresponding sensor data according to the average data change quantity and the average data value obtained by calculation; the data change degree represents the change intensity of the acquired data;

and comparing the calculated data change degree with a preset reference value, and adjusting the data sampling period and the operating parameters according to the comparison result.

2. The self-adaptive data acquisition method for the mining equipment sensor based on different working conditions as claimed in claim 1, wherein the average data variation is the variation of two adjacent data quantities acquired within a preset first time interval, the absolute data difference values of each two adjacent points are respectively calculated for a plurality of data acquired within the preset first time interval, and the average value of all the absolute data difference values of the data acquired within the first time interval is calculated to serve as the average data variation; the formula is expressed as:

（1）

wherein D is₁-D_kIs the data collected within a preset first time interval.

3. The adaptive data acquisition method for the mining equipment sensor based on different working conditions as claimed in claim 2, characterized in that the average data value is an average value of all data acquired within a preset second time interval; the formula is expressed as:

wherein D is₁-D_pPresetting data collected in a second time interval, wherein P is more than or equal to K, and the duration of the preset second time interval is more than or equal to the duration of the preset first time interval; the time starting point and the time ending point of the preset first time interval are contained in the time period of the preset second time interval.

4. The self-adaptive data acquisition method for the mining equipment sensor based on different working conditions as claimed in claim 3, wherein the formula of the data change degree is as follows:

（3）。

5. the self-adaptive data acquisition method of the mining equipment sensor based on different working conditions as claimed in claim 4, wherein the calculated data change degree is compared with a preset reference value, and the data sampling period is adjusted according to the comparison result, comprising the steps of:

presetting a reference value and a reference period: the reference value and the reference period are analyzed according to data collected by the sensor, and the data change degree and the sampling period value calculated when the sensor operates in the most normal state are determined;

if the calculated data change degree is less than or equal to 90% of the reference value, determining the sampling period as a 110% reference period value;

if the calculated data change degree is less than or equal to 80% of the reference value, determining the sampling period as a 125% reference period value;

on the contrary, if the calculated data change degree is larger than or equal to the 110% reference value, the sampling period is determined to be a 90% reference period value;

if the calculated data change degree is larger than or equal to the 125% reference value, determining the sampling period as an 80% reference period value;

the sampling periods are respectively set with an upper limit value T_maxAnd a lower limit value T_minAnd when the sampling period is adjusted to the upper limit value or the lower limit value, the data acquisition is carried out by keeping the sampling period of the upper limit value or the lower limit value.

6. The self-adaptive data acquisition method for the mining equipment sensor based on different working conditions according to claim 5, characterized in that the adjusted sampling period is compared with a preset sampling period threshold, and if the adjusted sampling period is smaller than the sampling period threshold, data is acquired according to a new sampling period and corresponding calculation is performed; and if the sampling period is larger than or equal to the preset sampling period threshold, acquiring data according to a new sampling period, and correspondingly calculating according to a new data quantity, namely the new data quantity corresponding to the sampling period threshold.

Technical Field

The invention relates to the technical field of coal mine intellectualization, in particular to a method for adaptively acquiring data of a sensor of excavating equipment based on different working conditions.

Background

Currently, coal is still the most important energy source in China. The automation and the intellectualization of coal mining equipment are important conditions for guaranteeing the high-efficiency safe mining of coal, the mining equipment is the coal mining equipment at the forefront end of the underground coal mine, the working surface has poor environmental conditions and severe working conditions, the equipment is difficult to maintain and repair, the normal production of the coal mine is ensured, the service lives of the equipment and parts are prolonged, and the system fault diagnosis and fault prediction level are improved. The existing mining equipment is provided with a large amount of sensors, and data acquisition adopts an equidistant mode, so that the data volume is usually increased rapidly, but useful data is not much, and if a method of simply increasing the sampling interval is adopted, the useful data is lost and the information volume is not complete. A large amount of data occupies too much storage space or communication resources, and makes subsequent data processing and calculation complicated. The development of equipment intellectualization is severely restricted.

Disclosure of Invention

Aiming at the defects of the existing acquisition method, the invention provides a self-adaptive acquisition method for the data of the mining equipment sensor based on different working conditions.

The technical scheme adopted by the invention for solving the technical problems is as follows: a self-adaptive data acquisition method of a mining equipment sensor based on different working conditions is constructed, and comprises the following steps:

calculating the average data variation in a first preset time interval and the average data value in a second preset time interval aiming at any sensor data in the mining equipment sensor data collected in real time;

determining the data change degree of the corresponding sensor data according to the average data change quantity and the average data value obtained by calculation; the data change degree represents the change intensity of the acquired data;

and comparing the calculated data change degree with a preset reference value, and adjusting the data sampling period and the operating parameters according to the comparison result.

The average data variation is the variation of two adjacent data quantities acquired in a preset first time interval, the absolute data difference values of every two adjacent points are respectively calculated for a plurality of data acquired in the preset first time interval, and the average value of all the absolute data difference values of the data acquired in the first time interval is calculated to serve as the average data variation; the formula is expressed as:

（1）

wherein D is₁-D_kIs the data collected within a preset first time interval.

Wherein the average data value is an average value of all data acquired within a preset second time interval; the formula is expressed as:

（2）

wherein D is₁-D_pThe data collected in the second time interval is preset, P is larger than or equal to K, and the preset second time interval duration is larger than or equal to the preset first time interval duration. The time starting point and the time ending point of the preset first time interval are contained in the time period of the preset second time interval.

Wherein, the formula of the data change degree is expressed as:

（3）

the step of comparing the calculated data change degree with a preset reference value and adjusting the data sampling period according to the comparison result comprises the following steps:

presetting a reference value and a reference period; the reference value and the reference period are analyzed according to data collected by the sensor, and the data change degree and the sampling period value calculated when the sensor operates in the most normal state are determined;

if the calculated data change degree is less than or equal to 90% of the reference value, determining the sampling period as a 110% reference period value;

if the calculated data change degree is less than or equal to 80% of the reference value, determining the sampling period as a 125% reference period value;

on the contrary, if the calculated data change degree is larger than or equal to the 110% reference value, the sampling period is determined to be a 90% reference period value;

if the calculated data change degree is larger than or equal to the 125% reference value, determining the sampling period as an 80% reference period value;

the sampling periods are respectively set with an upper limit value T_maxAnd a lower limit value T_minAnd when the sampling period is adjusted to the upper limit value or the lower limit value, the data acquisition is carried out by keeping the sampling period of the upper limit value or the lower limit value.

Comparing the adjusted sampling period with a preset sampling period threshold, and if the adjusted sampling period is smaller than the sampling period threshold, acquiring data according to a new sampling period and performing corresponding calculation; and if the sampling period is larger than or equal to the preset sampling period threshold, acquiring data according to a new sampling period, and correspondingly calculating according to a new data quantity (the sampling period threshold corresponds to the new data quantity).

Different from the prior art, the invention provides a self-adaptive acquisition method for adjusting the sampling period in real time according to the quantitative analysis result of data fluctuation, and particularly provides a self-adaptive acquisition method for adjusting the sampling period in real time based on the self-adaptive acquisition method for sensor data of mining equipment under different working conditions, wherein the acquisition frequency is increased when the sensor data change sharply during the operation of the equipment; when the device is in a standby state, the sampling frequency is reduced if the data change is slow, the amount of collected useless data is reduced as much as possible on the premise of ensuring that valuable data are not lost, and the sampling period is dynamically adjusted according to the data change degree under different working conditions. The resource utilization rate can be greatly improved, the working efficiency is improved, and the intelligent control, fault diagnosis and prediction of equipment are realized.

Drawings

The invention will be further described with reference to the accompanying drawings and examples, in which:

fig. 1 is a flow chart of data change degree calculation and sampling period adjustment of a mining equipment sensor data adaptive acquisition method based on different working conditions.

Fig. 2 is a sampling period dynamic adaptive rectification flowchart in the mining equipment sensor data adaptive acquisition method based on different working conditions provided by the invention.

Fig. 3 is a schematic diagram of the change of the sampling period adjusted along with the change of data in the mining equipment sensor data adaptive acquisition method based on different working conditions.

Detailed Description

For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

The underground working condition of the coal mine is severe, and the working time variation of the mining equipment is too many due to the mine geological condition, the performance of the equipment, the proficiency of operators and the like, so that the working state of the working equipment cannot be determined in advance, and the data sampling period cannot be planned according to different time periods. The existing data acquisition methods are not flexible enough in function, have no expansibility and can not meet the data acquisition requirements of mining equipment. The invention provides a method: the data processing and analyzing method is applicable to any mining equipment and is more flexible.

Referring to fig. 1 and fig. 2, fig. 1 is a flow chart of data change degree calculation and sampling period adjustment of a mining equipment sensor data adaptive acquisition method based on different working conditions, and fig. 2 is a flow chart of sampling period dynamic adaptive rectification, the method including the steps of:

s110: in the mining equipment sensor data collected in real time, the average data variation in a first preset time interval and the average data value in a second preset time interval are calculated aiming at any one sensor data.

S120: determining the data change degree of the corresponding sensor data according to the average data change quantity and the average data value obtained by calculation; wherein the degree of data change characterizes the severity of the change in the acquired data.

S130: and comparing the calculated data change degree with a preset reference value, and adjusting the data sampling period and the operating parameters according to the comparison result.

The average data variation is the variation of two adjacent data quantities acquired in a preset first time interval, the absolute data difference values of every two adjacent points are respectively calculated for a plurality of data acquired in the preset first time interval, and the average value of all the absolute data difference values of the data acquired in the first time interval is calculated to serve as the average data variation; the formula is expressed as:

（1）

wherein D is₁-D_kIs the data collected within a preset first time interval.

Wherein the average data value is an average value of all data acquired within a preset second time interval; the formula is expressed as:

（2）

wherein D is₁-D_pThe data collected in the second time interval is preset, P is larger than or equal to K, and the preset second time interval duration is larger than or equal to the preset first time interval duration. The time starting point and the time ending point of the preset first time interval are contained in the time period of the preset second time interval.

Wherein, the formula of the data change degree is expressed as:

（3）

the step of comparing the calculated data change degree with a preset reference value and adjusting the data sampling period according to the comparison result comprises the following steps:

presetting a reference value and a reference period; the reference value and the reference period are analyzed according to data collected by the sensor, and the data change degree and the sampling period value calculated when the sensor operates in the most normal state are determined;

if the calculated data change degree is less than or equal to 90% of the reference value, determining the sampling period as a 110% reference period value;

if the calculated data change degree is less than or equal to 80% of the reference value, determining the sampling period as a 125% reference period value;

on the contrary, if the calculated data change degree is larger than or equal to the 110% reference value, the sampling period is determined to be a 90% reference period value;

if the calculated data change degree is larger than or equal to the 125% reference value, determining the sampling period as an 80% reference period value;

the sampling periods are respectively set with an upper limit value T_maxAnd a lower limit value T_minAnd when the sampling period is adjusted to the upper limit value or the lower limit value, the data acquisition is carried out by keeping the sampling period of the upper limit value or the lower limit value.

Comparing the adjusted sampling period with a preset sampling period threshold, and if the adjusted sampling period is smaller than the sampling period threshold, acquiring data according to a new sampling period and performing corresponding calculation; and if the sampling period is larger than or equal to the preset sampling period threshold, acquiring data according to a new sampling period, and correspondingly calculating according to a new data quantity (the sampling period threshold corresponds to the new data quantity).

In the specific implementation process, if the sampling period is increased through adjustment, the data acquisition is slow when the data acquisition is performed in the adjusted sampling period, and the time for acquiring the same data is correspondingly prolonged when the average data variation and the average data value are calculated again subsequently. The solution adopted for the above situation is to set a preset sampling period threshold, and if the adjusted sampling period is greater than or equal to the sampling period threshold, the data volume is reduced, and on the premise of not influencing the calculation of the data change degree, the data volume is properly reduced, so that the problems of slow calculation and poor real-time performance caused by the increase of the data sampling period are avoided.

As previously mentioned, at T_mIn the time interval of (3), D is acquired₁-D_kTotal k data, at T_nIn the time interval of (3), D is acquired₁-D_pP data in total, and increasing the sampling period by subsequent calculation at T_mAnd T_nIn the time interval of (a), k and p data cannot be acquired. At this time, corresponding to the threshold of the sampling period, Ky and Py values are preset, i.e. new data quantity values, Ky is less than k, Py is less than p, Py is more than or equal to Ky, the calculation method is unchanged under the new condition that only the data quantity k and p and the sampling time interval T are changed_mAnd T_n。

Further, in the above step, after the adjustment of the sampling period is completed, the data value acquired after the adjustment is completed is analyzed, if a plurality of pieces of continuously acquired data are all determined as abnormal data, the next round of calculation and adjustment is performed according to the reference period and the original data amount (k, p), and if no continuous abnormal data exist, the data acquisition and calculation is performed according to the new sampling period and the new data amount (Ky, Py).

Fig. 3 is a schematic diagram of adjusting the sampling period according to the data change in the embodiment of the present invention, as shown in the drawing, the data is collected at time T1, the sampling period is small due to the rapid data change, the data change is gentle at time T2, the sampling period is large, the data change is more gentle at time T3, and the sampling period is further increased.

Different from the prior art, the invention provides a self-adaptive acquisition method for adjusting the sampling period in real time according to the quantitative analysis result of data fluctuation, and particularly provides a self-adaptive acquisition method for adjusting the sampling period in real time based on the self-adaptive acquisition method for sensor data of mining equipment under different working conditions, wherein the acquisition frequency is increased when the sensor data change sharply during the operation of the equipment; when the device is in a standby state, the sampling frequency is reduced if the data change is slow, the amount of collected useless data is reduced as much as possible on the premise of ensuring that valuable data are not lost, and the sampling period is dynamically adjusted according to the data change degree under different working conditions. The resource utilization rate can be greatly improved, the working efficiency is improved, and the intelligent control, fault diagnosis and prediction of equipment are realized.

While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.