Mine gas extraction pipeline on-line monitoring and fault diagnosis system and method

Abstract

The invention discloses a mine gas extraction pipeline on-line monitoring and fault diagnosis system which comprises a gas extraction pipeline on-line monitoring system which is connected with an extraction pipeline data analysis and fault diagnosis system. The gas extraction pipeline on-line monitoring system and the extraction pipeline data analysis and fault diagnosis system are both connected with the extraction pipeline visualization system, the system can accurately position the fault area and the fault type of the extraction pipeline, the problems that the gas extraction pipeline is too long, and the fault position is difficult to find manually are solved, and the working efficiency is improved. The invention further discloses an online monitoring and fault diagnosis method for the mine gas extraction pipeline. The method comprises the steps that 1, monitoring points are arranged, and the extraction pipeline monitoring units are arranged to collect data; 2, analyzing a fault extraction pipeline and a fault type according to the data; step 3, displaying and sending out early warning through an extraction pipeline visualization system; according to the method, the fault position and the fault type of the extraction pipeline are rapidly positioned, and the mine gas extraction capacity is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal seam gas control, and specifically relates to an online monitoring and fault diagnosis system for a mine gas extraction pipeline. The present invention also relates to an online monitoring and fault diagnosis method for a mine gas extraction pipeline using the above system. Background Art

[0002] Mine gas extraction is the main means of preventing and controlling gas disasters in high-gas and coal-gas outburst mines. Usually, gas is extracted from coal seams or goafs through negative pressure, and discharged from the mine through gas extraction pipelines at all levels. During the gas extraction process, leakage or blockage of the gas extraction pipeline directly affects the size of the gas extraction negative pressure, thereby affecting the gas extraction effect. Therefore, timely judgment of the fault location of the gas extraction pipeline is of great significance to improving the gas extraction effect. The existing method is to manually find the fault location, but the length of the mine gas extraction pipeline is very long. When the extraction pipeline fails, it is very difficult to manually find the fault point, which is time-consuming and laborious, resulting in untimely fault handling and affecting the mine gas extraction effect.

[0003] Therefore, there is an urgent need to develop an online monitoring and fault diagnosis system and method for mine gas extraction pipelines, to monitor the extraction conditions in various areas of the extraction pipeline in real time during the gas extraction process, to quickly locate the pipeline fault area, and to determine the type of pipeline fault to ensure the normal operation of the mine gas extraction system. Summary of the invention

[0004] The first object of the present invention is to provide an online monitoring and fault diagnosis system for mine gas extraction pipelines, which solves the problem that the gas extraction pipeline is too long and it is difficult to manually find the fault location.

[0005] The second object of the present invention is to provide a method for online monitoring and fault diagnosis of mine gas extraction pipelines.

[0006] The first technical solution adopted by the present invention is an online monitoring and fault diagnosis system for mine gas extraction pipelines, including an online monitoring system for gas extraction pipelines, the online monitoring system for gas extraction pipelines is connected to a extraction pipeline data analysis and fault diagnosis system, and both the online monitoring system for gas extraction pipelines and the extraction pipeline data analysis and fault diagnosis system are connected to a extraction pipeline visualization system.

[0007] The first technical solution of the present invention is also characterized in that the gas extraction pipeline online monitoring system includes a number of extraction pipeline monitoring units, the extraction pipeline monitoring units are specifically multi-parameter sensors, the extraction pipeline data analysis and fault diagnosis system includes an extraction pipeline fault area diagnosis module and an extraction pipeline fault type diagnosis module, and the extraction pipeline visualization system includes an extraction pipeline three-dimensional modeling module, an extraction pipeline fault visualization module, and an extraction pipeline fault early warning module.

[0008] The second technical solution adopted by the present invention is a method for online monitoring and fault diagnosis of mine gas extraction pipelines, using the above-mentioned online monitoring and fault diagnosis system for mine gas extraction pipelines, and the specific steps are as follows:

[0009] Step 1: several monitoring points are arranged at intervals on the mine gas extraction pipeline, and each monitoring point is numbered. A extraction pipeline monitoring unit is set at each detection point of the extraction pipeline to perform real-time monitoring, and a historical data set is formed according to the monitoring results;

[0010] Step 2: Analyze the historical data set of step 1 through the extraction pipeline fault area diagnosis module, analyze the abnormal conditions of each monitoring point, find out the abnormal monitoring point, determine the faulty extraction pipeline corresponding to the abnormal monitoring point, and determine the fault type of the faulty extraction pipeline through the extraction pipeline fault type diagnosis module;

[0011] Step 3: Display the location and fault type of the faulty extraction pipeline in step 2 through the extraction pipeline visualization system, and issue an early warning.

[0012] The second technical solution of the present invention is also characterized in that the data set in step 1 includes extraction concentration, extraction flow rate, extraction temperature, and extraction negative pressure data;

[0013] The specific process of numbering each monitoring point in step 1 is as follows:

[0014] Several monitoring points are arranged at intervals on the mine gas extraction pipeline, and each monitoring point is numbered in the order of distance from the pumping station, specifically:

[0015] I=(1,2,3,...,i-1,i)

[0016] Among them, I represents the set of all monitoring points, and i represents the i-th monitoring point.

[0017] The specific process of step 2 is as follows:

[0018] Step 2.1, preprocessing the historical data sets collected by each sampling pipeline monitoring unit at each monitoring point in step 1;

[0019] Step 2.2, select the historical data of the i-th monitoring point and randomly select part of the historical data as sample subsets multiple times to build a series of isolated trees, and then train each monitoring point separately, repeat this step, and form a total of i series of isolated trees;

[0020] Step 2.3: Continue to collect real-time data from each monitoring point through the extraction pipeline monitoring unit and perform data testing, specifically:

[0021] The real-time data of each monitoring point is tested separately. The real-time data of the i-th monitoring point traverses each isolated tree of the i-th series to determine whether the corresponding i-th monitoring point has abnormal extraction. If the i-th monitoring point is abnormal, first determine the faulty extraction pipeline corresponding to the i-th abnormal monitoring point, and then determine the fault type of the faulty extraction pipeline. If the i-th monitoring point is normal, continue monitoring and repeat the above steps 2.1 to 2.3.

[0022] The specific process of determining the faulty extraction pipeline corresponding to the i-th abnormal monitoring point in step 2.3 is as follows:

[0023] If the i-th monitoring point is an abnormal monitoring point, and the previous monitoring point i-1 adjacent to it is a normal monitoring point, it indicates that the extraction pipeline between the monitoring point i-1 and the monitoring point i is faulty, that is, the extraction pipeline between the monitoring point i-1 and the monitoring point i is a faulty extraction pipeline.

[0024] The specific process of determining the fault type of the faulty extraction pipeline in step 2.3 is as follows:

[0025] Step 2.3.1: Calculate the flow data (Q i , Q i-1 ), gas concentration data (C i , C i-1 )) to analyze and calculate the daily average flow of monitoring point i and monitoring point i-1 Average concentration

[0026] Step 2.3.2: Compare and analyze the daily average flow of monitoring point i and monitoring point i-1 and like This indicates that the extraction pipeline between monitoring point i and monitoring point i-1 is blocked. and If the difference percentage is less than 10%, continue to analyze its average concentration;

[0027] Step 2.3.3: Compare and analyze the average concentrations of monitoring point i and monitoring point i-1 and like This indicates that there is a gas leakage fault in the extraction pipeline between monitoring point i and monitoring point i-1.

[0028] The beneficial effects of the present invention are:

[0029] The online monitoring and fault diagnosis system for mine gas extraction pipelines of the present invention monitors each position of the extraction pipeline in real time through an extraction pipeline monitoring unit, and judges the extraction through an extraction pipeline fault area diagnosis module, accurately locates the extraction pipeline fault area and fault type, and solves the problem that the gas extraction pipeline is too long and it is difficult to find the fault location manually.

[0030] The method for online monitoring and fault diagnosis of mine gas extraction pipelines of the present invention can quickly locate the fault area of ​​the extraction pipeline based on the data collected by each extraction pipeline monitoring unit of the extraction pipeline, and accurately determine the fault type of the extraction pipeline. It is efficient and accurate, and provides accurate data support for mine gas extraction pipeline fault detection and prevention, which is beneficial to improving the mine gas extraction capacity. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a structural schematic diagram of the mine gas extraction pipeline online monitoring and fault diagnosis system of the present invention;

[0032] Figure 2 It is a flow chart of the method for online monitoring and fault diagnosis of mine gas extraction pipelines of the present invention. DETAILED DESCRIPTION

[0033] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] The first technical solution provided by the present invention is an online monitoring and fault diagnosis system for mine gas extraction pipelines, such as Figure 1 As shown, it includes a gas extraction pipeline online monitoring system, the gas extraction pipeline online monitoring system is connected to the extraction pipeline data analysis and fault diagnosis system, and the gas extraction pipeline online monitoring system and the extraction pipeline data analysis and fault diagnosis system are both connected to the extraction pipeline visualization system.

[0035] The gas extraction pipeline online monitoring system includes several extraction pipeline monitoring units, which are specifically multi-parameter sensors. The extraction pipeline data analysis and fault diagnosis system includes an extraction pipeline fault area diagnosis module and an extraction pipeline fault type diagnosis module. The extraction pipeline visualization system includes an extraction pipeline three-dimensional modeling module, an extraction pipeline fault visualization module, and an extraction pipeline fault early warning module.

[0036] Among them, the extraction pipeline monitoring unit is used to collect gas extraction related parameters of each monitoring point of the mine gas extraction pipeline in real time, including flow, concentration, negative pressure, temperature, etc., and convert the collected electrical signals into digital signals and transmit them to the extraction pipeline data analysis and fault diagnosis system.

[0037] The drainage pipeline fault area diagnosis module can analyze the data collected from each monitoring point of the underground gas extraction pipeline, and then determine the operating status of each area of ​​the extraction pipeline in real time, and accurately locate the fault area of ​​the extraction pipeline; the drainage pipeline fault type diagnosis module can conduct a detailed analysis of the monitoring abnormal point and its upper monitoring point data, and accurately determine the fault type of the area.

[0038] The extraction pipeline three-dimensional modeling module can build a three-dimensional visualization model of the entire mine gas extraction pipeline system based on the actual layout of the mine extraction pipeline and the installation status of the gas extraction pipeline online monitoring system; the extraction pipeline fault visualization module can display the monitoring results of the gas extraction pipeline online monitoring system in real time, and perform three-dimensional animation display of the extraction pipeline fault area and fault type diagnosed by the extraction pipeline data analysis and fault diagnosis system; the extraction pipeline fault warning module can issue warnings for extraction pipeline faults.

[0039] Through the extraction pipeline monitoring unit, multi-parameter sensors are arranged at various positions of the extraction pipeline for real-time monitoring. The extraction pipeline fault area diagnosis module is used to determine the operating status of each area of ​​the extraction pipeline, and the extraction pipeline fault area and fault type are accurately located. No matter how long the gas extraction pipe is, the fault can be discovered and found in time. Finally, the extraction pipeline fault visualization module is used to display the extraction pipeline fault area and fault type through a three-dimensional animation, which can easily find the extraction pipeline fault area and fault type, effectively solving the problem of long gas extraction pipelines and difficulty in manually finding the fault location.

[0040] The second technical solution provided by the present invention is a method for online monitoring and fault diagnosis of mine gas extraction pipelines, using the above-mentioned online monitoring and fault diagnosis system for mine gas extraction pipelines, such as Figure 2 As shown, the specific steps are as follows:

[0041] Step 1: several monitoring points are arranged at intervals on the mine gas extraction pipeline, and each monitoring point is numbered. A extraction pipeline monitoring unit is arranged at each detection point of the extraction pipeline to perform real-time monitoring, and a historical data set is formed according to the monitoring results;

[0042] The data set in step 1 includes the extraction concentration, extraction flow, extraction temperature, and extraction negative pressure data;

[0043] The specific process of numbering each monitoring point in step 1 is as follows:

[0044] Several monitoring points are arranged at intervals on the mine gas extraction pipeline, and each monitoring point is numbered in the order of distance from the pumping station, specifically:

[0045] I=(1,2,3,...,i-1,i)

[0046] Among them, I represents the set of all monitoring points, and i represents the i-th monitoring point.

[0047] Step 2: Analyze the historical data set of step 1 through the extraction pipeline fault area diagnosis module, analyze the abnormal conditions of each monitoring point, find out the abnormal monitoring point, determine the faulty extraction pipeline corresponding to the abnormal monitoring point, and determine the fault type of the faulty extraction pipeline through the extraction pipeline fault type diagnosis module;

[0048] The specific process of step 2 is as follows:

[0049] Step 2.1, preprocessing the historical data sets collected by each sampling pipeline monitoring unit at each monitoring point in step 1;

[0050] Step 2.2, select the historical data of the i-th monitoring point and randomly select part of the historical data as sample subsets multiple times to build a series of isolated trees, and then train each monitoring point separately, repeat this step, and form a total of i series of isolated trees;

[0051] Step 2.3: Continue to collect real-time data from each monitoring point through the extraction pipeline monitoring unit and perform data testing, specifically:

[0052] The real-time data of each monitoring point is tested separately. The real-time data of the i-th monitoring point traverses each isolated tree of the i-th series to determine whether the corresponding i-th monitoring point has abnormal extraction. If the i-th monitoring point is abnormal, first determine the faulty extraction pipeline corresponding to the i-th abnormal monitoring point, and then determine the fault type of the faulty extraction pipeline. If the i-th monitoring point is normal, continue monitoring and repeat the above steps 2.1 to 2.3.

[0053] The specific process of determining the faulty extraction pipeline corresponding to the i-th abnormal monitoring point in step 2.3 is as follows:

[0054] If the i-th monitoring point is an abnormal monitoring point, and the previous monitoring point i-1 adjacent to it is a normal monitoring point, it indicates that the extraction pipeline between the monitoring point i-1 and the monitoring point i is faulty, that is, the extraction pipeline between the monitoring point i-1 and the monitoring point i is a faulty extraction pipeline.

[0055] The specific process of determining the fault type of the faulty extraction pipeline in step 2.3 is as follows:

[0056] Step 2.3.1: Calculate the flow data (Q i , Q i-1 ), gas concentration data (C i , C i-1 )) to analyze and calculate the daily average flow of monitoring point i and monitoring point i-1 Average concentration

[0057] Step 2.3.2: Compare and analyze the daily average flow of monitoring point i and monitoring point i-1 and like This indicates that the extraction pipeline between monitoring point i and monitoring point i-1 is blocked. and If the difference percentage is less than 10%, continue to analyze its average concentration.

[0058] Step 2.3.3: Compare and analyze the average concentrations of monitoring point i and monitoring point i-1 and like This indicates that there is a gas leakage fault in the extraction pipeline between monitoring point i and monitoring point i-1.

[0059] Step 3: Display the location and fault type of the faulty extraction pipeline in step 2 through the extraction pipeline visualization system, and issue an early warning.

[0060] Through the above method, the operating status of the extraction pipeline can be accurately judged according to the data collected by each extraction pipeline monitoring unit of the extraction pipeline, and the scope of the extraction pipeline fault area can be quickly located, and the fault type of the extraction pipeline can be accurately judged, which is efficient and accurate, and provides accurate data support for the troubleshooting and prevention of mine gas extraction pipeline faults, which is beneficial to improving the mine gas extraction capacity. At the same time, it provides technical support for the mine gas extraction pipeline online monitoring and fault diagnosis system of the present invention, and can ensure the safe and efficient operation of the mine gas extraction pipeline online monitoring and fault diagnosis system.

[0061] The present invention provides an online monitoring and fault diagnosis system for mine gas extraction pipelines, and the specific embodiments are as follows:

[0062] Example 1

[0063] The invention discloses an online monitoring and fault diagnosis system for a mine gas extraction pipeline, comprising an online monitoring system for a gas extraction pipeline, wherein the online monitoring system for the gas extraction pipeline is connected to a data analysis and fault diagnosis system for an extraction pipeline, and both the online monitoring system for the gas extraction pipeline and the data analysis and fault diagnosis system for the extraction pipeline are connected to a visualization system for the extraction pipeline.

[0064] Example 2

[0065] The mine gas extraction pipeline online monitoring and fault diagnosis system includes a gas extraction pipeline online monitoring system, which is connected to the extraction pipeline data analysis and fault diagnosis system, and both the gas extraction pipeline online monitoring system and the extraction pipeline data analysis and fault diagnosis system are connected to the extraction pipeline visualization system.

[0066] The gas extraction pipeline online monitoring system includes several extraction pipeline monitoring units, which are specifically multi-parameter sensors. The extraction pipeline data analysis and fault diagnosis system includes an extraction pipeline fault area diagnosis module and a extraction pipeline fault type diagnosis module.

[0067] Example 3

[0068] The mine gas extraction pipeline online monitoring and fault diagnosis system includes a gas extraction pipeline online monitoring system, which is connected to the extraction pipeline data analysis and fault diagnosis system, and both the gas extraction pipeline online monitoring system and the extraction pipeline data analysis and fault diagnosis system are connected to the extraction pipeline visualization system.

[0069] The gas extraction pipeline online monitoring system includes several extraction pipeline monitoring units, which are specifically multi-parameter sensors. The extraction pipeline data analysis and fault diagnosis system includes an extraction pipeline fault area diagnosis module and an extraction pipeline fault type diagnosis module. The extraction pipeline visualization system includes an extraction pipeline three-dimensional modeling module, an extraction pipeline fault visualization module, and an extraction pipeline fault early warning module.

Claims

1. The mine gas extraction pipeline online monitoring and fault diagnosis system is characterized by: It comprises a gas extraction pipeline online monitoring system, which is connected to an extraction pipeline data analysis and fault diagnosis system, and both the gas extraction pipeline online monitoring system and the extraction pipeline data analysis and fault diagnosis system are connected to an extraction pipeline visualization system.

2. The mine gas extraction pipeline online monitoring and fault diagnosis system according to claim 1 is characterized in that: The gas extraction pipeline online monitoring system includes several extraction pipeline monitoring units, and the extraction pipeline monitoring units are specifically multi-parameter sensors. The extraction pipeline data analysis and fault diagnosis system includes an extraction pipeline fault area diagnosis module and an extraction pipeline fault type diagnosis module. The extraction pipeline visualization system includes an extraction pipeline three-dimensional modeling module, an extraction pipeline fault visualization module, and an extraction pipeline fault early warning module.

3. A method for online monitoring and fault diagnosis of a mine gas extraction pipeline, characterized in that: The online monitoring and fault diagnosis system for mine gas extraction pipelines described in claim 2 above is adopted, and the specific steps are as follows: Step 1: several monitoring points are arranged at intervals on the mine gas extraction pipeline, and each monitoring point is numbered. A extraction pipeline monitoring unit is set at each detection point of the extraction pipeline to perform real-time monitoring, and a historical data set is formed according to the monitoring results; Step 2: Analyze the historical data set of step 1 through the extraction pipeline fault area diagnosis module, analyze the abnormal conditions of each monitoring point, find out the abnormal monitoring point, determine the faulty extraction pipeline corresponding to the abnormal monitoring point, and determine the fault type of the faulty extraction pipeline through the extraction pipeline fault type diagnosis module; Step 3: Display the location and fault type of the faulty extraction pipeline in step 2 through the extraction pipeline visualization system, and issue an early warning.

4. The method for online monitoring and fault diagnosis of mine gas extraction pipeline according to claim 3 is characterized in that: The data set in step 1 includes extraction concentration, extraction flow, extraction temperature, and extraction negative pressure data; The specific process of numbering each monitoring point in step 1 is as follows: Several monitoring points are arranged at intervals on the mine gas extraction pipeline, and each monitoring point is numbered in the order of distance from the pumping station, specifically: I=(1,2,3,...,i-1,i) Among them, I represents the set of all monitoring points, and i represents the i-th monitoring point.

5. The method for online monitoring and fault diagnosis of mine gas extraction pipeline according to claim 3 is characterized in that: The specific process of step 2 is as follows: Step 2.1, preprocessing the historical data sets collected by each sampling pipeline monitoring unit at each monitoring point in step 1; Step 2.2, select the historical data of the i-th monitoring point and randomly select part of the historical data as sample subsets multiple times to build a series of isolated trees, and then train each monitoring point separately, repeat this step, and form a total of i series of isolated trees; Step 2.3: Continue to collect real-time data from each monitoring point through the extraction pipeline monitoring unit and perform data testing, specifically: The real-time data of each monitoring point is tested separately. The real-time data of the i-th monitoring point traverses each isolated tree of the i-th series to determine whether the corresponding i-th monitoring point has abnormal extraction. If the i-th monitoring point is abnormal, first determine the faulty extraction pipeline corresponding to the i-th abnormal monitoring point, and then determine the fault type of the faulty extraction pipeline. If the i-th monitoring point is normal, continue monitoring and repeat the above steps 2.1 to 2.

3.

6. The method for online monitoring and fault diagnosis of mine gas extraction pipeline according to claim 3, characterized in that: The specific process of determining the faulty extraction pipeline corresponding to the i-th abnormal monitoring point described in step 2.3 is as follows: If the i-th monitoring point is an abnormal monitoring point, and the previous monitoring point i-1 adjacent to it is a normal monitoring point, it indicates that the extraction pipeline between the monitoring point i-1 and the monitoring point i is faulty, that is, the extraction pipeline between the monitoring point i-1 and the monitoring point i is a faulty extraction pipeline.

7. The method for online monitoring and fault diagnosis of mine gas extraction pipeline according to claim 3, characterized in that: The specific process of determining the fault type of the faulty extraction pipeline described in step 2.3 is as follows: Step 2.3.1: Calculate the flow data (Q i , Q i-1 ), gas concentration data (C i , C i-1 )) to analyze and calculate the daily average flow (Q i , Q i-1 ), average concentration (C i , C i-1 ); Step 2.3.2: Compare and analyze the daily average flow Q of monitoring point i and monitoring point i-1 i With Q i-1 , if Q i < i-1 , it indicates that the extraction pipeline between monitoring point i and monitoring point i-1 is blocked. If Q i With Q i-1 If the difference percentage is less than 10%, continue to analyze its average concentration;​ Step 2.3.3: Compare and analyze the average concentration C of monitoring point i and monitoring point i-1 i With C i-1 , if C i < <C i-1 , it indicates that there is a gas leakage fault in the extraction pipeline between monitoring point i and monitoring point i-1.

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