Leakage diagnosis system and method for hydraulic support

Abstract

The invention provides a leakage diagnosis system and method for a hydraulic support, and belongs to the technical field of coal mine equipment monitoring and diagnosis, and the system comprises a data collection module which constructs a sensor network, monitors and collects the working data of the hydraulic support in real time, and carries out the initial processing of the working data of the hydraulic support; the leakage diagnosis module is used for analyzing the initially processed working data of the hydraulic support and carrying out leakage diagnosis in combination with a preset method; the leakage positioning module is used for determining a leakage position based on a preset sensor network and the working data of the hydraulic support; the leakage analysis module is used for determining the fault type of the hydraulic support based on the leakage diagnosis result and in combination with the leakage position; and the fault early warning module is used for generating a fault early warning report based on the fault type of the hydraulic support and sending the fault early warning report to the control end, and important technical support is provided for intelligent operation and maintenance of coal mine equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine equipment monitoring and diagnosis, and in particular to a leakage diagnosis system and method for a hydraulic support. Background Art

[0002] In current coal mining, hydraulic supports are key equipment to ensure mining safety and production efficiency, and their performance is directly related to the stability and operating efficiency of the mine. However, due to factors such as component wear and complex environment during long-term operation, hydraulic supports often leak, resulting in a decrease in support capacity or even shutdown for maintenance.

[0003] Existing technical solutions usually determine leakage through simple pressure monitoring or regular maintenance, but their diagnostic accuracy is low, the response is delayed, and it is difficult to locate the leakage point in time, resulting in high maintenance costs and low operating efficiency. Based on the shortcomings of the above technical solutions, there is an urgent need for a system that can monitor the performance of hydraulic supports in real time, accurately diagnose leakage problems and quickly locate faults, so as to improve equipment operation efficiency and reduce safety hazards.

[0004] Therefore, the present invention provides a leakage diagnosis system and method for a hydraulic support. Summary of the invention

[0005] The present invention provides a performance analysis method for a hydraulic support for a coal mine, which is used to monitor, diagnose, locate and analyze the leakage problem of the hydraulic support in real time, build a full-process automated diagnosis system, identify the leakage location and fault type, provide timely warnings, greatly improve the diagnosis efficiency and maintenance response speed, significantly reduce the operation risk and maintenance cost, and provide important technical support for the intelligent operation and maintenance of coal mine equipment.

[0006] The present invention provides a leakage diagnosis system for a hydraulic support, comprising: Data acquisition module: build a sensor network to monitor and collect the working data of the hydraulic support in real time, and then perform initial processing on the working data of the hydraulic support; Leakage diagnosis module: analyzes the working data of the hydraulic support that has been initially processed, and performs leakage diagnosis in combination with preset methods; Leak location module: determines the leak location based on the preset sensor network and the working data of the hydraulic support; Leakage analysis module: Determine the fault type of the hydraulic support based on the leakage diagnosis results and the leakage location; Fault warning module: Generates a fault warning report based on the fault type of the hydraulic support and sends it to the control end.

[0007] The present invention provides a leakage diagnosis system for a hydraulic support, a data acquisition module, comprising: Node determination unit: analyzes the hydraulic support and the environment where the hydraulic support is located respectively, and determines a number of sensor nodes based on the analysis results; Network construction unit: constructs a sensor network based on sensor nodes and preset network protocols; Data processing unit: monitors and collects the working data of the hydraulic support in real time based on the sensor network, and performs initial processing on the collected working data of the hydraulic support.

[0008] The present invention provides a leakage diagnosis system for a hydraulic support, a node determination unit, comprising: System determination subunit: Conduct structural analysis on the hydraulic support to determine several key systems of the hydraulic support; Signal acquisition subunit: Determine the number of sensors to be deployed for each key system based on the preset system-sensor data table, and deploy corresponding sensors in each key system to monitor and collect change signals of the key system; Data acquisition subunit: deploying preset sensors in the environment where the hydraulic support is located and collecting environmental data; Data analysis subunit: Analyzes the change signals and environmental data of each key system based on preset analysis methods; Location determination subunit: determines several key locations of each key system based on the analysis results; Node determination subunit: determines a number of initial nodes of each key part of each key system based on a preset system-part-node data table; Node analysis subunit: Analyze all initial nodes and determine several central nodes.

[0009] The present invention provides a leakage diagnosis system for a hydraulic support, a data processing unit, comprising: Preliminary analysis subunit: perform preliminary analysis on the working data of the hydraulic support and determine the real-time node status value of each node; Abnormal judgment subunit: judges whether an abnormality occurs in a node based on the node status value of each node and a preset node status threshold; Abnormal sending subunit: if an abnormality occurs, the corresponding node is determined as an abnormal node, and the data of the abnormal node is transmitted to the central node, and the data of nodes other than the abnormal node is transmitted to the central node; The data sent to the central node is determined as the working data of the hydraulic support that has been initially processed.

[0010] The present invention provides a leakage diagnosis system for a hydraulic support, a preliminary analysis subunit, comprising: Data extraction block: pre-processes the working data of the hydraulic support and extracts the node status related data of each sensor node based on the preset data extraction method; Status acquisition block: Determines the real-time node status value of each sensor node based on the node status related data of each sensor node: ;in, is the real-time node status value of the i-th sensor node, is the weight of the jth sensor under the i-th sensor node, is the real-time monitoring value of the jth sensor under the i-th sensor node, is the preset reference value of the jth sensor under the i-th sensor node, The number of sensors deployed for the i-th sensor node, is the error correction factor of the real-time monitoring value of the jth sensor under the i-th sensor node, is the standard deviation of the historical monitoring value of the jth sensor under the i-th sensor node, is the preset time correction factor.

[0011] The present invention provides a leakage diagnosis system for a hydraulic support, and a leakage diagnosis module, comprising: Preprocessing unit: performs noise filtering and data smoothing on the initially processed hydraulic support working data, and normalizes different types of sensor data; Attribute acquisition unit: performs attribute analysis on the hydraulic support, and then determines the attributes of the hydraulic support; A method determination unit: determines a leakage diagnosis method based on the properties of the hydraulic support and a preset property-diagnosis method; Range determination unit: obtain the working mechanism of the hydraulic support, establish a mathematical model of the hydraulic system in combination with the leakage diagnosis method, and then determine the standard working parameter range of the hydraulic support; Result determination unit: obtains historical data of the hydraulic support, and constructs a data-driven leakage diagnosis model through a preset algorithm and a standard working parameter range of the hydraulic support, and then outputs the leakage diagnosis result.

[0012] The invention provides a leakage diagnosis system and a leakage diagnosis method for a hydraulic support, which include: a pressure flow analysis method, a pressure difference analysis method, a temperature change analysis method and a vibration mode analysis method.

[0013] The present invention provides a leakage diagnosis method for a hydraulic support, comprising: Step 1: Build a sensor network to monitor and collect the working data of the hydraulic support in real time, and then perform initial processing on the working data of the hydraulic support; Step 2: Analyze the working data of the hydraulic support that has been initially processed, and perform leakage diagnosis in combination with the preset method; Step 3: Determine the leakage location based on the preset sensor network and the working data of the hydraulic support; Step 4: Determine the fault type of the hydraulic support based on the leakage diagnosis result and the leakage location; Step 5: Generate a fault warning report based on the fault type of the hydraulic support and send it to the control end.

[0014] Compared with the prior art, the present invention has the following beneficial effects: By real-time monitoring, diagnosis, positioning and analysis of hydraulic support leakage problems, a full-process automated diagnosis system was built to identify leakage locations and fault types, provide timely warnings, greatly improve diagnostic efficiency and maintenance response speed, significantly reduce operating risks and maintenance costs, and provide important technical support for the intelligent operation and maintenance of coal mine equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a structural schematic diagram of a leakage diagnosis system for a hydraulic support provided in an embodiment of the present invention.

[0017] Figure 2 It is a flow chart of a leakage diagnosis system method for a hydraulic support provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Embodiment 1: The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, such as Figure 1 As shown, including: Data acquisition module: build a sensor network to monitor and collect the working data of the hydraulic support in real time, and then perform initial processing on the working data of the hydraulic support; Leakage diagnosis module: analyzes the working data of the hydraulic support that has been initially processed, and performs leakage diagnosis in combination with preset methods; Leak location module: determines the leak location based on the preset sensor network and the working data of the hydraulic support; Leakage analysis module: Determine the fault type of the hydraulic support based on the leakage diagnosis results and the leakage location; Fault warning module: Generates a fault warning report based on the fault type of the hydraulic support and sends it to the control end.

[0020] In this embodiment, the working data of the hydraulic support is the key parameters collected by the sensor during operation, including real-time data such as pressure, flow, temperature, vibration, displacement, etc. These data reflect the working status of the hydraulic support. For example, the sensor records the pressure data of a support cylinder of the hydraulic support as 30 MPa, and the normal range is 25-35 MPa, indicating that the support is working normally. If the pressure is detected to drop suddenly to 15 MPa, there may be a leak.

[0021] In this embodiment, the preset method is an algorithm or standard process for analysis and diagnosis set in advance in the system, usually including threshold settings, data models or logical rules. These methods are used to determine whether there is an abnormality in the system. For example: the preset method defines that when the pressure drops by more than 10%, the flow increases by 15%, and the temperature rises abnormally by 5°C, the system determines that a leak has occurred; In this embodiment, leakage diagnosis is to analyze the hydraulic system based on the collected working data and the preset method to determine whether there is a hydraulic oil leak and the severity of the leak. For example: System analysis shows that the oil pressure of a certain bracket is reduced and the flow rate is abnormally increased. Combined with the temperature increase, the diagnosis result shows that there is a moderate leak in the hydraulic pipeline.

[0022] In this embodiment, the leak location is determined by analyzing the sensor data and the system model to accurately determine the location where the leak occurs, including hydraulic cylinders, valves, pipes and other components. For example: The leak location module analysis shows that the leak point is located at the interface of the main support cylinder, and the cause may be the wear of the sealing ring.

[0023] In this embodiment, the fault type of the hydraulic support is further analyzed based on the leakage diagnosis result and the leakage location, such as seal aging, pipeline cracks, loose joints, etc. For example: the diagnosis result shows that the leakage point is located in the hydraulic valve group, and the fault type is internal leakage caused by valve core wear; In this embodiment, the fault warning report is a report automatically generated by the system, which records the fault diagnosis results, leakage location, fault type and treatment suggestions in detail, and sends it to the management or maintenance personnel. For example, the report points out that the leakage location is in the No. 2 main cylinder of the bracket, the fault type is aging of the seal, and it is recommended to shut down for maintenance; In this embodiment, the control end is the monitoring center or operation platform of the system, which is used to receive fault warning reports, monitor the status of the hydraulic support and perform remote control. For example, after receiving a leakage alarm, the control end automatically notifies the maintenance personnel and can remotely shut down the hydraulic system to prevent the accident from expanding.

[0024] The beneficial effects of the above technical solution are: through real-time monitoring, diagnosis, positioning and analysis of hydraulic support leakage problems, a full-process automated diagnosis system is built to identify leakage locations and fault types, provide timely warnings, greatly improve diagnostic efficiency and maintenance response speed, significantly reduce operating risks and maintenance costs, and provide important technical support for the intelligent operation and maintenance of coal mine equipment.

[0025] Embodiment 2: The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, comprising: Node determination unit: analyzes the hydraulic support and the environment where the hydraulic support is located respectively, and determines a number of sensor nodes based on the analysis results; Network construction unit: constructs a sensor network based on sensor nodes and preset network protocols; Data processing unit: monitors and collects the working data of the hydraulic support in real time based on the sensor network, and performs initial processing on the collected working data of the hydraulic support.

[0026] In this embodiment, the sensor node refers to a single sensor device arranged in the hydraulic support and its environment, which is used to collect specific physical or environmental parameters (such as pressure, flow, temperature, vibration, etc.) and transmit the data to the data processing unit. For example: a pressure sensor node is installed on the main support cylinder of the hydraulic support to monitor the hydraulic oil pressure; another node is installed in the surrounding environment to detect temperature changes.

[0027] In this embodiment, the sensor network is a system composed of multiple sensor nodes interconnected by a network protocol, which is used to realize data collection, transmission and sharing. The sensor network can use wired or wireless connections to ensure that data at different locations can be summarized and analyzed in real time. The sensor network includes pressure sensor nodes and temperature sensor nodes arranged on the support, and flow sensor nodes installed on the hydraulic pipeline. The data is transmitted to the control center through wireless communication protocols (such as LoRa or Zigbee) to realize the overall status monitoring of the hydraulic support.

[0028] The beneficial effects of the above technical solution are: building an efficient sensor network through joint analysis of hydraulic supports and the environment, integrating real-time monitoring and preliminary data processing functions, significantly improving the comprehensiveness of data collection and the stability of network transmission, and laying the foundation for accurate leakage diagnosis under complex working conditions.

[0029] Embodiment 3: The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, a node determination unit, comprising: System determination subunit: Conduct structural analysis on the hydraulic support to determine several key systems of the hydraulic support; Signal acquisition subunit: Determine the number of sensors to be deployed for each key system based on the preset system-sensor data table, and deploy corresponding sensors in each key system to monitor and collect change signals of the key system; Data acquisition subunit: deploying preset sensors in the environment where the hydraulic support is located and collecting environmental data; Data analysis subunit: Analyzes the change signals and environmental data of each key system based on preset analysis methods; Location determination subunit: determines several key locations of each key system based on the analysis results; Node determination subunit: determines a number of initial nodes of each key part of each key system based on a preset system-part-node data table; Node analysis subunit: Analyze all initial nodes and determine several central nodes.

[0030] In this embodiment, the key parts refer to the core positions in the key systems of the hydraulic support that are most prone to leakage or failure, usually including high-pressure cylinders, hydraulic pipe interfaces, valve groups, etc. Focusing on monitoring these parts can improve diagnostic efficiency and accuracy. For example: the sealing interface of the main support cylinder of the hydraulic support is a key part, because it is subjected to high pressure and the wear of the seals can easily lead to leakage.

[0031] In this embodiment, the initial nodes are the sensor locations deployed on the key parts according to the preset system-part-node data table, which represent all the monitoring points recommended in the preliminary design stage. These nodes cover the key parts to ensure the collection of complete data. For example, a pressure sensor and a temperature sensor are deployed on the sealing interface (key part) of the main support cylinder, and the installation points corresponding to these sensors are the initial nodes.

[0032] In this embodiment, the central node is the optimal monitoring point determined after analysis and optimization from the initial nodes. It is usually selected based on data importance, sensor cost and network redundancy, and is ultimately used for actual monitoring. For example: through analysis, it is found that the data of the pressure sensor is most critical for diagnosing leaks. Therefore, the pressure sensor is retained as the central node at the main support cylinder sealing interface, and the temperature sensor is cancelled.

[0033] In this embodiment, the key parts are the results of system structure analysis, indicating the areas that need to be monitored. The initial nodes are all sensor points arranged at the key parts, which are used to comprehensively monitor the changes in the key parts. The central node is the final monitoring point after optimizing the initial node, which reduces redundancy and costs while ensuring monitoring accuracy. Relationship example: The sealing interface of the main support cylinder of the hydraulic support is a key part. Pressure, flow, vibration and other sensors are arranged at the sealing interface. These monitoring points are initial nodes. Analysis shows that pressure data can best reflect the leakage problem. Therefore, only the pressure sensor is retained in the end and determined as the central node.

[0034] In this embodiment, the preset system-part-node data table is a structured configuration table for the hydraulic support leakage diagnosis system, which defines the monitoring parts of each key system and the corresponding sensor node deployment rules as the basis for node determination and layout. It is an important tool in the system design stage to ensure the reasonable layout of sensors, comprehensiveness and effectiveness of data collection.

[0035] The beneficial effects of the above technical solution are: through systematic structural analysis and multi-level data acquisition and processing, accurate determination from the environment to key parts, from the initial node to the central node is achieved, sensor deployment and node division are optimized, and the pertinence of signal acquisition and the accuracy of diagnostic analysis are improved, providing efficient support for leakage diagnosis under complex working conditions.

[0036] Embodiment 4: The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, a data processing unit, comprising: Preliminary analysis subunit: perform preliminary analysis on the working data of the hydraulic support and determine the real-time node status value of each node; Abnormal judgment subunit: judges whether an abnormality occurs in a node based on the node status value of each node and a preset node status threshold; Abnormal sending subunit: if an abnormality occurs, the corresponding node is determined as an abnormal node, and the data of the abnormal node is transmitted to the central node, and the data of nodes other than the abnormal node is transmitted to the central node; The data sent to the central node is determined as the working data of the hydraulic support that has been initially processed.

[0037] In this embodiment, the preset node status threshold refers to a reference range or critical value set by the system according to the normal operating conditions of the hydraulic support, which is used to determine whether the data monitored by the sensor is abnormal. The threshold is usually set based on empirical data, historical data or engineering design standards. For example: For a pressure sensor node, the preset normal operating pressure range is 25-35 MPa. If the pressure monitored by the node is lower than 25 MPa or higher than 35 MPa, it exceeds the preset node status threshold and there may be an abnormality.

[0038] In this embodiment, an abnormal node refers to a sensor node whose monitoring data exceeds the preset node status threshold range, indicating that there may be a leak or fault at the location, which requires further analysis and processing. For example, the temperature monitored by the temperature sensor node of a hydraulic support is 90°C, while the preset normal temperature threshold range is 20-60°C, so the temperature node is determined to be an abnormal node. Assume that the sealing interface of the hydraulic support is arranged with pressure and temperature sensor nodes: the system sets the pressure threshold to 25-35 MPa and the temperature threshold to 20-60°C. The data collected by the pressure node is 20 MPa, which is lower than the threshold and is judged as an abnormal node. The system transmits the data of the pressure node to the central node, and at the same time transmits the normal data of the temperature node together for further comprehensive analysis.

[0039] The beneficial effects of the above technical solution are: by introducing real-time monitoring of node status and a hierarchical abnormality judgment mechanism, the classified processing and synchronous transmission of abnormal node and normal node data are realized, data redundancy is reduced, the efficiency of abnormality positioning and the accuracy of data transmission are improved, and reliable support is provided for the rapid decision-making of the central node.

[0040] Embodiment 5: The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, wherein the preliminary analysis subunit comprises: Data extraction block: pre-processes the working data of the hydraulic support and extracts the node status related data of each sensor node based on the preset data extraction method; Status acquisition block: Determines the real-time node status value of each sensor node based on the node status related data of each sensor node: ;in, is the real-time node status value of the i-th sensor node, is the weight of the jth sensor under the i-th sensor node, is the real-time monitoring value of the jth sensor under the i-th sensor node, is the preset reference value of the jth sensor under the i-th sensor node, The number of sensors deployed for the i-th sensor node, is the error correction factor of the real-time monitoring value of the jth sensor under the i-th sensor node, is the standard deviation of the historical monitoring value of the jth sensor under the i-th sensor node, is the preset time correction factor.

[0041] In this embodiment, the error correction factor is a coefficient used to correct the deviation in the real-time monitoring data of the sensor due to environmental interference, sensor aging or installation errors. It is determined through historical data analysis or calibration testing to ensure the accuracy and reliability of the monitoring data. When calculating the sensor node status value, the real-time monitoring value of the sensor will be multiplied by the error correction factor to eliminate or reduce data errors. For example: The historical records of a pressure sensor show that due to temperature changes, its monitoring value has a systematic deviation, and the actual value is 1 MPa higher than the measured value. The error correction factor is set to 1.05, which is used to correct the measured value to be closer to the actual value. For example, the real-time value monitored by the sensor is 20 MPa, and the calculated value after correction is 21 MPa; In this embodiment, the preset time correction coefficient is used to weight the sensor's historical data to reflect the weight of the impact of data in different time periods on the current state value. Usually, newer data has a greater weight and older data has a smaller weight, which is used to capture the dynamic change trend of the current state. Formula meaning: In the state value calculation, the influence of the historical monitoring value is adjusted by the time correction coefficient to make the state calculation more sensitive. For example, a flow sensor has recorded multiple data points in the past three days. In order to pay more attention to recent changes, the preset time correction coefficient is used to weight the historical data: the first day's data weight is 0.5; the second day's data weight is 0.8; the third day (today) data weight is 1.0. In this way, today's monitoring data has the greatest impact on the state value, while the impact of earlier data gradually decreases, ensuring that the state value reflects the latest situation.

[0042] The beneficial effects of the above technical solution are: by constructing a dynamic calculation model of real-time node status values ​​and integrating multi-dimensional factors such as sensor weights, error correction and time correction, the problems of data inconsistency and error accumulation under complex working conditions are solved, and the accuracy and adaptability of hydraulic support status monitoring are significantly improved, laying the foundation for intelligent diagnosis.

[0043] Embodiment 6: The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, and a leakage diagnosis module, including: Preprocessing unit: performs noise filtering and data smoothing on the initially processed hydraulic support working data, and normalizes different types of sensor data; Attribute acquisition unit: performs attribute analysis on the hydraulic support, and then determines the attributes of the hydraulic support; A method determination unit: determines a leakage diagnosis method based on the properties of the hydraulic support and a preset property-diagnosis method; Range determination unit: obtain the working mechanism of the hydraulic support, establish a mathematical model of the hydraulic system in combination with the leakage diagnosis method, and then determine the standard working parameter range of the hydraulic support; Result determination unit: obtains historical data of the hydraulic support, and constructs a data-driven leakage diagnosis model through a preset algorithm and a standard working parameter range of the hydraulic support, and then outputs the leakage diagnosis result.

[0044] In this embodiment, the attribute analysis is a comprehensive analysis of the structure, function, working conditions and related characteristics of the hydraulic support to determine its core characteristics and key factors required for diagnosis. For example, after analyzing the hydraulic support, its attributes include the load capacity of the support (such as the maximum support force of 1000 tons), the pressure range of the hydraulic system, the environmental temperature adaptability range (-20℃ to 50℃), etc. In this embodiment, the properties of the hydraulic support refer to the characteristic parameters inherent in its design and operation process, including structural properties (such as the height and weight of the support), performance properties (such as pressure and flow), and adaptability properties (such as applicable environment). For example, the properties of the hydraulic support include: Structural properties: The bracket height is 3 meters and the weight is 2 tons; Performance properties: The hydraulic cylinder pressure range is 25-35 MPa and the flow rate is 5-10 L / min; Adaptability properties: It can work normally in dusty environments and the protection level is IP65.

[0045] In this embodiment, the working mechanism of the hydraulic support refers to its operating principle when supporting ore or load, including processes such as force on the hydraulic cylinder, flow of hydraulic oil, and pressure balance adjustment, which usually involves the coordinated work of multiple components. For example: in the working mechanism, the hydraulic oil is transported to the hydraulic cylinder through the pump station, and the hydraulic cylinder provides supporting force under a pressure of 25 MPa. If the pressure drops suddenly, the supporting force weakens, which may cause system leakage.

[0046] In this embodiment, the mathematical model of the hydraulic system is a mathematical formula or equation that represents the relationship and law of the hydraulic system operation process, which is usually used to simulate and analyze the performance or fault behavior of the hydraulic support; in this embodiment, the standard operating parameter range is the value range of each key parameter of the hydraulic support under normal working conditions, which is used to determine whether the system is operating normally. For example: the standard operating parameter range of the hydraulic support may include: hydraulic oil pressure: 25-35 MPa; flow: 5-10 L / min; temperature: 20-60℃. If the actual parameters exceed this range, there may be leakage or other faults.

[0047] In this embodiment, the data-driven leakage diagnosis model is a model constructed based on the historical data and real-time monitoring data of the hydraulic support through machine learning, statistical analysis and other methods, and is used to diagnose whether a hydraulic system leaks and its possible causes. For example: a neural network model trained using the historical operating data of the hydraulic support (such as pressure fluctuation trends, abnormal flow changes) can output the possible leakage location and degree when a sudden increase in flow is monitored in real time.

[0048] In this embodiment, the final analysis result output by the leakage diagnosis module includes the possible location, severity, fault type and recommended measures of the leakage. For example: the diagnosis result shows that there is a slight leakage in the sealing interface of the main support cylinder (the flow rate exceeds the normal range by 15%), and it is recommended to replace the seal and recheck the pipeline pressure.

[0049] The beneficial effects of the above technical solution are: by introducing multi-level diagnosis, organically combining data preprocessing, attribute analysis, mathematical modeling and data-driven technology, the efficient, intelligent and precise diagnosis of hydraulic support leakage can be achieved, the diagnostic methods of different attributes can be dynamically adapted, and a self-optimization model can be constructed through standard parameters and historical data to effectively improve the system adaptability and reliability.

[0050] Embodiment 7: The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, including: a pressure flow analysis method, a pressure difference analysis method, a temperature change analysis method and a vibration mode analysis method.

[0051] In this embodiment, the pressure difference analysis method is to identify whether the pressure difference is abnormal by comparing the pressure data of different parts of the hydraulic system. Leakage usually leads to abnormal pressure gradient distribution, which can be used as an important basis for diagnosis. For example, the pressure difference between the main oil cylinder and the branch pipe of the hydraulic support is usually 5MPa, but the actual monitoring found that the pressure difference increased to 8MPa, which may be caused by leakage of the main oil cylinder seal; In this embodiment, the temperature change analysis method is that hydraulic oil leakage will cause abnormal local temperature changes. Leakage can be indirectly diagnosed by monitoring the temperature change trend of key parts. When leakage causes oil loss or increased friction, the local temperature rises. For example: the temperature sensor near a valve group of a hydraulic support shows that the temperature continues to rise by 10°C, while the temperature of other parts is normal, which may be due to leakage of the valve group; In this embodiment, the vibration mode analysis method is that hydraulic leakage will cause changes in the vibration characteristics of the system, especially when high-pressure oil flow impact or cavitation occurs, the vibration mode will be abnormal. By analyzing the frequency spectrum and intensity changes of the vibration signal, the location and type of leakage can be determined. For example: during the operation of a certain bracket, the vibration monitoring equipment detected a characteristic peak with a frequency of 500Hz. Combined with empirical analysis, it is shown that this feature is associated with leakage in the oil pipe.

[0052] The beneficial effects of the above technical solution are: by combining pressure flow analysis, pressure difference analysis, temperature change analysis and vibration mode analysis, multi-dimensional and in-depth hydraulic support leakage diagnosis can be achieved, leakage characteristics can be captured, and diagnostic accuracy and efficiency can be improved. It can quickly locate the source of the fault and quantify the degree of leakage, providing reliable support for preventive maintenance and extending equipment life.

[0053] Embodiment 8: The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, such as Figure 2 As shown, including: Step 1: Build a sensor network to monitor and collect the working data of the hydraulic support in real time, and then perform initial processing on the working data of the hydraulic support; Step 2: Analyze the working data of the hydraulic support that has been initially processed, and perform leakage diagnosis in combination with the preset method; Step 3: Determine the leakage location based on the preset sensor network and the working data of the hydraulic support; Step 4: Determine the fault type of the hydraulic support based on the leakage diagnosis result and the leakage location; Step 5: Generate a fault warning report based on the fault type of the hydraulic support and send it to the control end.

[0054] The beneficial effects of the above technical solution are: through real-time monitoring, diagnosis, positioning and analysis of hydraulic support leakage problems, a full-process automated diagnosis system is built to identify leakage locations and fault types, provide timely warnings, greatly improve diagnostic efficiency and maintenance response speed, significantly reduce operating risks and maintenance costs, and provide important technical support for the intelligent operation and maintenance of coal mine equipment.

[0055] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A leakage diagnosis system for a hydraulic support, characterized in that: include: Data acquisition module: build a sensor network to monitor and collect the working data of the hydraulic support in real time, and then perform initial processing on the working data of the hydraulic support; Leakage diagnosis module: analyzes the working data of the hydraulic support that has been initially processed, and performs leakage diagnosis in combination with preset methods; Leak location module: determines the leak location based on the preset sensor network and the working data of the hydraulic support; Leakage analysis module: Determine the fault type of the hydraulic support based on the leakage diagnosis results and the leakage location; Fault warning module: Generates a fault warning report based on the fault type of the hydraulic support and sends it to the control end.

2. The leakage diagnosis system of the hydraulic support according to claim 1, characterized in that: Data acquisition module, including: Node determination unit: analyzes the hydraulic support and the environment where the hydraulic support is located respectively, and determines a number of sensor nodes based on the analysis results; Network construction unit: constructs a sensor network based on sensor nodes and preset network protocols; Data processing unit: monitors and collects the working data of the hydraulic support in real time based on the sensor network, and performs initial processing on the collected working data of the hydraulic support.

3. The leakage diagnosis system of the hydraulic support according to claim 2, characterized in that: The node determination unit includes: System determination subunit: Conduct structural analysis on the hydraulic support to determine several key systems of the hydraulic support; Signal acquisition subunit: Determine the number of sensors to be deployed for each key system based on the preset system-sensor data table, and deploy corresponding sensors in each key system to monitor and collect change signals of the key system; Data acquisition subunit: deploying preset sensors in the environment where the hydraulic support is located and collecting environmental data; Data analysis subunit: Analyzes the change signals and environmental data of each key system based on preset analysis methods; Location determination subunit: determines several key locations of each key system based on the analysis results; Node determination subunit: determines a number of initial nodes of each key part of each key system based on a preset system-part-node data table; Node analysis subunit: Analyze all initial nodes and determine several central nodes.

4. The leakage diagnosis system of the hydraulic support according to claim 2, characterized in that: Data processing unit, including: Preliminary analysis subunit: perform preliminary analysis on the working data of the hydraulic support and determine the real-time node status value of each node; Abnormal judgment subunit: judges whether an abnormality occurs in a node based on the node status value of each node and a preset node status threshold; Abnormal sending subunit: if an abnormality occurs, the corresponding node is determined as an abnormal node, and the data of the abnormal node is transmitted to the central node, and the data of nodes other than the abnormal node is transmitted to the central node; The data sent to the central node is determined as the working data of the hydraulic support that has been initially processed.

5. The leakage diagnosis system of the hydraulic support according to claim 4, characterized in that: The preliminary analysis subunit includes: Data extraction block: pre-processes the working data of the hydraulic support and extracts the node status related data of each sensor node based on the preset data extraction method; Status acquisition block: Determines the real-time node status value of each sensor node based on the node status related data of each sensor node: ;in, is the real-time node status value of the i-th sensor node, is the weight of the jth sensor under the i-th sensor node, is the real-time monitoring value of the jth sensor under the i-th sensor node, is the preset reference value of the jth sensor under the i-th sensor node, The number of sensors deployed for the i-th sensor node, is the error correction factor of the real-time monitoring value of the jth sensor under the i-th sensor node, is the standard deviation of the historical monitoring value of the jth sensor under the i-th sensor node, is the preset time correction factor.

6. The leakage diagnosis system of the hydraulic support according to claim 1, characterized in that: Leak diagnostic module, including: Preprocessing unit: performs noise filtering and data smoothing on the initially processed hydraulic support working data, and normalizes different types of sensor data; Attribute acquisition unit: performs attribute analysis on the hydraulic support, and then determines the attributes of the hydraulic support; A method determination unit: determines a leakage diagnosis method based on the properties of the hydraulic support and a preset property-diagnosis method; Range determination unit: obtain the working mechanism of the hydraulic support, establish a mathematical model of the hydraulic system in combination with the leakage diagnosis method, and then determine the standard working parameter range of the hydraulic support; Result determination unit: obtains historical data of the hydraulic support, and constructs a data-driven leakage diagnosis model through a preset algorithm and a standard working parameter range of the hydraulic support, and then outputs the leakage diagnosis result.

7. The leakage diagnosis system of the hydraulic support according to claim 6, characterized in that: Leakage diagnosis methods include: pressure flow analysis, pressure difference analysis, temperature change analysis and vibration mode analysis.

8. A leakage diagnosis method for a hydraulic support, characterized in that: include: Step 1: Build a sensor network to monitor and collect the working data of the hydraulic support in real time, and then perform initial processing on the working data of the hydraulic support; Step 2: Analyze the working data of the hydraulic support that has been initially processed, and perform leakage diagnosis in combination with the preset method; Step 3: Determine the leakage location based on the preset sensor network and the working data of the hydraulic support; Step 4: Determine the fault type of the hydraulic support based on the leakage diagnosis result and the leakage location; Step 5: Generate a fault warning report based on the fault type of the hydraulic support and send it to the control end.

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