CN115436051A - Hydraulic support pressure abnormity identification method - Google Patents
Hydraulic support pressure abnormity identification method Download PDFInfo
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- CN115436051A CN115436051A CN202211087444.4A CN202211087444A CN115436051A CN 115436051 A CN115436051 A CN 115436051A CN 202211087444 A CN202211087444 A CN 202211087444A CN 115436051 A CN115436051 A CN 115436051A
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
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- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses a hydraulic support pressure abnormity identification method, which comprises the steps of obtaining support pressure and drawing a support pressure change curve; according to the action cycle period of the bracket, dividing the pressure change curve of the bracket into a plurality of pressure change curves taking the action cycle period of the bracket as a unit, and extracting the time sequence characteristics of the pressure change curves; identifying a fluctuation section of a pressure change curve after the safety valve of the bracket is opened, and determining a pressure peak value of the fluctuation section as the opening pressure of the safety valve of the bracket; combining the time sequence characteristics and the opening pressure of the bracket safety valve to study and judge the opening fault of the bracket safety valve; and (4) combining the time sequence characteristics to study and judge the abnormal condition of the pressure of the bracket. The method has the advantages that the abnormal type of the support pressure can be automatically identified without adding an additional sensor, wherein the abnormal type comprises the opening fault of the safety valve, the support leakage, the support virtual top, the sensor fault and the like, so that the labor cost is reduced, and a foundation is provided for accurately judging the pressure relief threshold of the safety valve.
Description
Technical Field
The invention relates to the field of automatic analysis of coal face data, in particular to a hydraulic support pressure abnormity identification method.
Background
The intelligent work of the fully mechanized mining equipment on the coal face depends on identifying each process in the production operation process, and the process identification based on the data of the equipment work process is the basis for realizing the intelligence of the fully mechanized mining equipment. At present, the informatization level in the coal mining process of a coal mine has a certain foundation, and a part of production data with incomplete data quality is formed, but due to the lack of an analysis method for the data, the data cannot be fully mined, and more effective decision data is provided for the coal mining process.
The hydraulic support pressure in the fully mechanized mining complete equipment is a key parameter for guaranteeing a fully mechanized mining working face of a coal mine, a safety valve of the support pressure is opened to cause a fault in actual work due to various reasons, and the problems of support virtual roof, support leakage and the like are often hidden behind the abnormal support pressure. In the existing comprehensive intelligent management, after the support pressure is transmitted back to a background monitoring system, a field operator can check real-time pressure data through a system monitoring interface, and meanwhile, an alarm prompt can be sent out when the pressure data exceeds a set limit value. However, in actual work, it is found that the support pressure data change in real time, and the support pressure which does not exceed the set limit value may still be abnormal, and often an operator needs to comprehensively judge and identify abnormal conditions by combining the support pressure at a certain moment with the support pressure in a previous period, the pressure of a nearby support and the coal mining process stage. Although the support pressure abnormity can be identified by the traditional manual observation mode, the identification timeliness and the automation degree are both insufficient, the workload is large, the dependence on the manual experience is large, and the method is contrary to the coal mining intelligent target.
Disclosure of Invention
The invention aims to provide a hydraulic support pressure abnormity identification method.
In order to achieve the purpose, the invention adopts the following technical scheme:
the hydraulic support pressure abnormity identification method comprises the following steps:
s1, obtaining support pressure and drawing a support pressure change curve;
s2, according to the action cycle period of the support, dividing the pressure change curve of the support into a plurality of pressure change curves taking the action cycle period of the support as a unit, and extracting the time sequence characteristics of the pressure change curves;
s3, identifying a fluctuation section of a pressure change curve after the opening of the support safety valve, and determining a pressure peak value of the fluctuation section as the opening pressure of the support safety valve;
s4, combining the time sequence characteristics and the opening pressure of the bracket safety valve, and studying and judging the opening fault of the bracket safety valve;
and S5, researching and judging the abnormal pressure condition of the support by combining the time sequence characteristics.
According to the method, a data analysis method for automatically identifying the pressure abnormity of the support is established, the opening pressure value of the safety valve of the support is calculated according to pressure time sequence data of the support in a large number of pressure cycle resistance increasing sections, and the starting and stopping time of the pressure overrun period caused by the failure of the safety valve of the support is extracted; according to the analysis of the shape of the pressure curve of the support at the resistance increasing section in each pressure cycle, the starting and ending time of abnormal reduction of the support pressure is extracted, so that the purposes of automatic identification of the support pressure abnormality and providing analysis basis for troubleshooting of potential safety hazards behind the support pressure abnormality are achieved.
Further, in the step S2, the rack operation cycle period includes rack descending, rack moving, rack lifting and pushing.
Further, in the step S2, the method for extracting the time series feature includes: calculating a differential value of the support pressure between adjacent time sequences, and splitting the pressure change curve into a series of monotonous sections; and further screening and combining the change amplitude and the duration of the monotonous section, extracting each ascending section and each descending section in the monotonous section, and counting the time length and the amplitude of the ascending section, the time length and the amplitude of the descending section, the time length of the fluctuation section and the start-stop time of each support action.
Furthermore, the fluctuation section refers to a plurality of frequently alternating ascending sections and descending sections, and a plurality of monotone sections have short duration and small pressure change amplitude.
Further, in the step S3, the identifying of the support pressure fluctuation section after the opening of the support safety valve includes screening out a pressure change curve fluctuation section representing the support safety valve after the opening of the support safety valve in the pressure change curve according to the start-stop time of the support action.
Further, in the S4 step, the judging of the opening fault of the safety valve of the bracket includes: screening the ascending section of the current pressure change curve, comparing the pressure peak value of the ascending section with the opening pressure of the support safety valve in the last pressure change curve, and if the pressure peak value of the ascending section does not decrease after exceeding the opening pressure of the support safety valve in the last pressure change curve, judging that the support safety valve in the corresponding time period of the ascending section is in failure.
Further, in the step S5, the determining of the abnormal situation of the stent pressure includes: if a descending section with larger pressure drop amplitude and larger pressure drop speed appears after the ascending section of the current pressure change curve reaches a pressure peak value, judging that the support pressure in a corresponding time period of the descending section abnormally descends; and if the support pressure is abnormally reduced continuously in a plurality of continuous support action cycle periods or the same support action cycle period, judging that the support pressure leakage is abnormal.
The method has the advantages that the abnormal type of the support pressure can be automatically identified without adding an additional sensor only by depending on the existing pressure data and the action cycle state of the support, wherein the abnormal type comprises the opening fault of the safety valve, the support leakage, the support virtual top, the sensor fault and the like, so that the labor cost is reduced, a basis is provided for accurately judging the pressure relief threshold value of the safety valve, and the safety risk caused by the fact that the pressure relief threshold value of the safety valve is privately modified on an operation site is reduced; meanwhile, related equipment faults can be found in time, key warning information is provided, the number of times of accidental shutdown maintenance is reduced, the safety level of coal mine safety production is improved, and the fully mechanized mining efficiency is improved.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
FIG. 2 is a diagram of an example of raw data in the method of the present invention.
FIG. 3 is an example of abnormal pressure variation curve when the opening of the safety valve of the bracket is abnormal in the method of the present invention.
FIG. 4 is an abnormal example of the pressure variation curve when the pressure of the stent leaks in the method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
As shown in fig. 1, the method for identifying the pressure abnormality of the hydraulic support according to the present invention includes the following steps:
first, the stent pressure is obtained as raw data, and as shown in fig. 2, a stent pressure variation curve can be constructed. And dividing the pressure of the support into a plurality of pressure change curves in the action cycle period of the support according to the action cycle period of the support.
Generally, a rack movement cycle comprises four basic rack movements, namely, a column descending movement, a column lifting movement and a pushing movement, and information such as the starting and ending time of each rack movement cycle, the execution time of each movement in each rack movement cycle, the moving movement and the pushing movement stroke can be obtained through the prior art.
And secondly, extracting the time sequence characteristics of the pressure change curve in the action cycle period of the bracket. The specific method comprises the following steps: the pressure change curve in the stent action cycle period is divided into a series of monotonous sections by calculating the difference value of the stent pressure data in the adjacent time sequence, and the divided monotonous sections are further subjected to operations such as screening and combination based on the information such as the change amplitude, the duration and the like of the monotonous sections, so that the ascending section and the descending section in the pressure change curve in the stent action cycle period are finally extracted. And then, counting each ascending section and each descending section to obtain characteristics such as ascending section time length, ascending section amplitude, descending section time length, descending section amplitude, fluctuation section time length and the like. Wherein the fluctuation sections are ascending sections and descending sections which are frequently alternated, and wherein the duration of each monotone section is short, and the pressure change amplitude is not large and is basically equivalent.
According to the information of the execution time, the frame moving and the pushing stroke of each action in each support action cycle, a characteristic section representing the up-and-down fluctuation of the support pressure after the safety valve is opened can be identified from the pressure change curve, the pressure peak value of the characteristic section is counted and used as the safety valve opening pressure in the support action process, and the pressure peak value is stored in a safety valve opening pressure setting table.
Then, the time sequence characteristic of the pressure change curve in the bracket action cycle period and the safety valve opening pressure corresponding to the bracket action process are combined to carry out the research and judgment of the safety valve opening fault, and the method specifically comprises the following steps:
and screening a rising section of a pressure change curve of the support in the current support action cycle, comparing a pressure peak value of the rising section with the opening pressure of a support safety valve in the last support action cycle of the support, if the pressure peak value of the rising section does not fall after exceeding the opening pressure of the support safety valve in the last support action cycle, judging the opening fault of the support safety valve in the corresponding period of the rising section, namely the failure abnormity of the support safety valve occurs, and recording the opening fault information of the support safety valve into a support safety valve opening fault study and judgment table. As shown in fig. 3, the black box represents an example of the abnormal pressure change curve when the safety valve of the bracket is opened.
Meanwhile, based on the time sequence characteristics of the pressure change curve in the action cycle period of the support, the abnormal pressure reduction condition of the support is researched, judged and analyzed, and the method specifically comprises the following steps:
if the ascending section of the pressure change curve in the current support action cycle of the support reaches a pressure peak value, and a descending section with larger pressure drop amplitude and larger pressure drop speed appears, judging that the support pressure in the corresponding time period of the descending section abnormally drops; if the pressure of the support is reduced abnormally continuously in a plurality of continuous support action cycle periods or in the same support action cycle period, judging that the pressure of the support is leaked abnormally, and recording an analysis result into a support leakage study and judgment table. As shown in fig. 4, black boxes show examples of the pressure variation curve abnormality when the pressure leakage of the bracket fails.
Claims (7)
1. The hydraulic support pressure abnormity identification method is characterized by comprising the following steps:
s1, obtaining support pressure and drawing a support pressure change curve;
s2, according to the action cycle period of the support, dividing the pressure change curve of the support into a plurality of pressure change curves taking the action cycle period of the support as a unit, and extracting the time sequence characteristics of the pressure change curves;
s3, identifying a fluctuation section of a pressure change curve after the safety valve of the support is opened, and determining a pressure peak value of the fluctuation section as the opening pressure of the safety valve of the support;
s4, combining the time sequence characteristics and the opening pressure of the bracket safety valve, and studying and judging the opening fault of the bracket safety valve;
and S5, judging the abnormal condition of the pressure of the support by combining the time sequence characteristics.
2. The method for identifying abnormality of position sensor of coal mining machine according to claim 1, characterized in that: and S2, in the support action cycle period, the support falls, moves, lifts and pushes away the slide.
3. The abnormality recognition method for the position sensor of the coal mining machine according to claim 1, characterized in that: in the step S2, the method for extracting the timing characteristics includes: calculating a differential value of the support pressure between adjacent time sequences, and splitting the pressure change curve into a series of monotonous sections; and further screening and combining the change amplitude and the duration of the monotonous section, extracting each ascending section and each descending section in the monotonous section, and counting the time length and the amplitude of the ascending section, the time length and the amplitude of the descending section, the time length of the fluctuation section and the start-stop time of each support action.
4. The method for identifying abnormality of position sensor of coal mining machine according to claim 3, characterized in that: the fluctuation section is a plurality of frequently alternating ascending sections and descending sections, and a plurality of monotone sections have short duration and small pressure change amplitude.
5. The abnormality recognition method for the position sensor of the coal mining machine according to claim 1, characterized in that: and S3, identifying the support pressure fluctuation section after the support safety valve is opened comprises screening out a pressure change curve fluctuation section representing the support safety valve after the support safety valve is opened in the pressure change curve according to the starting and stopping time of the support action.
6. The method for identifying abnormality of position sensor of coal mining machine according to claim 1, characterized in that: in the S4 step, study and judge support relief valve and open the trouble and include: screening the ascending section of the current pressure change curve, comparing the pressure peak value of the ascending section with the opening pressure of the support safety valve in the last pressure change curve, and if the pressure peak value of the ascending section does not decrease after exceeding the opening pressure of the support safety valve in the last pressure change curve, judging that the support safety valve in the corresponding time period of the ascending section is in failure.
7. The method for identifying abnormality of position sensor of coal mining machine according to claim 1, characterized in that: in the step S5, the step of determining the abnormal pressure condition of the stent includes: if a descending section with larger pressure drop amplitude and larger pressure drop speed appears after the ascending section of the current pressure change curve reaches a pressure peak value, judging that the support pressure in a corresponding time period of the descending section abnormally descends; and if the support pressure is abnormally reduced continuously in a plurality of continuous support action cycle periods or the same support action cycle period, judging that the support pressure leakage is abnormal.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117744010A (en) * | 2024-02-07 | 2024-03-22 | 煤炭科学研究总院有限公司 | Small data driven real-time positioning method for pressure abnormality of coal mine support |
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| CN110728003A (en) * | 2019-10-17 | 2020-01-24 | 天地科技股份有限公司 | Intelligent prediction method for pressure of hydraulic support on working face of underground coal mine |
| CN111911214A (en) * | 2020-06-24 | 2020-11-10 | 中煤科工开采研究院有限公司 | Method for monitoring working state of safety valve of hydraulic support |
| CN112052563A (en) * | 2020-08-05 | 2020-12-08 | 东北大学 | Method for determining hinge point load of hydraulic support pressing frame test based on virtual prototype technology |
| CN112302720A (en) * | 2020-09-30 | 2021-02-02 | 中煤科工开采研究院有限公司 | Method and system for judging initial supporting force and cycle end resistance of working surface hydraulic support |
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Patent Citations (4)
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| CN110728003A (en) * | 2019-10-17 | 2020-01-24 | 天地科技股份有限公司 | Intelligent prediction method for pressure of hydraulic support on working face of underground coal mine |
| CN111911214A (en) * | 2020-06-24 | 2020-11-10 | 中煤科工开采研究院有限公司 | Method for monitoring working state of safety valve of hydraulic support |
| CN112052563A (en) * | 2020-08-05 | 2020-12-08 | 东北大学 | Method for determining hinge point load of hydraulic support pressing frame test based on virtual prototype technology |
| CN112302720A (en) * | 2020-09-30 | 2021-02-02 | 中煤科工开采研究院有限公司 | Method and system for judging initial supporting force and cycle end resistance of working surface hydraulic support |
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| CN117744010A (en) * | 2024-02-07 | 2024-03-22 | 煤炭科学研究总院有限公司 | Small data driven real-time positioning method for pressure abnormality of coal mine support |
| CN117744010B (en) * | 2024-02-07 | 2024-04-30 | 煤炭科学研究总院有限公司 | Small data driven real-time positioning method for pressure abnormality of coal mine support |
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Address after: 719000 Laide building, Jianye Avenue, high tech Industrial Park, Yulin City, Shaanxi Province Applicant after: Guoneng Yulin Energy Co.,Ltd. Applicant after: Zhengzhou Hengda Intelligent Control Technology Co.,Ltd. Applicant after: BEIJING INNOVATION CENTER FOR INDUSTRIAL BIG DATA CO.,LTD. Address before: 719000 Laide building, Jianye Avenue, high tech Industrial Park, Yulin City, Shaanxi Province Applicant before: Guoneng Yulin Energy Co.,Ltd. Applicant before: HYDRAULIC & ELECTRIC CONTROL EQUIPMENT CO LTD ZHENGZHOU COAL MINING MACHINERY GROUP Co.,Ltd. Applicant before: BEIJING INNOVATION CENTER FOR INDUSTRIAL BIG DATA CO.,LTD. |
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