Leakage Diagnosis System and Method for Hydraulic Support

Abstract

The present invention provides a leakage diagnosis system and method for hydraulic supports, belonging to the technical field of coal mine equipment monitoring and diagnosis, including: a data acquisition module: constructing a sensor network to monitor and collect the working data of the hydraulic support in real time, and then performing initial processing on the working data of the hydraulic support; a leakage diagnosis module: analyzing the working data of the hydraulic support after initial processing, and performing leakage diagnosis in combination with a preset method; a leakage location module: determining the leakage location based on the preset sensor network and the working data of the hydraulic support; a leakage analysis module: determining the fault type of the hydraulic support based on the leakage diagnosis result and in combination with the leakage location; a fault warning module: generating a fault warning report based on the fault type of the hydraulic support and sending it to the control end, providing an important technical support for the 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 particularly to a leakage diagnosis system and method for hydraulic supports. 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 of the mine and the operation efficiency. However, due to factors such as component wear during long-term operation and complex environments, hydraulic supports often have leakage problems, resulting in a decline in the support capacity of the supports and even shutdown for maintenance.

[0003] Existing technical solutions usually judge leakage through simple pressure monitoring or regular maintenance, but their diagnostic accuracy is low, the response is lagged, and it is difficult to locate the leakage point in time, resulting in high maintenance costs and low operation efficiency. Based on the deficiencies 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 the equipment operation efficiency and reduce potential safety hazards.

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

[0005] The present invention provides a method for analyzing the performance of a coal mine hydraulic support, which constructs a full-process automated diagnosis system by real-time monitoring, diagnosing, locating, and analyzing the leakage problems of the hydraulic support, identifies the leakage location and fault type, provides timely warnings, greatly improves the diagnostic efficiency and maintenance response speed, significantly reduces the operation risk and maintenance cost, and provides an 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, including:

[0007] A data acquisition module: constructing a sensor network to monitor and collect the working data of the hydraulic support in real time, and then performing initial processing on the working data of the hydraulic support;

[0008] A leakage diagnosis module: analyzing the working data of the hydraulic support after initial processing, and performing leakage diagnosis in combination with a preset method;

[0009] A leakage location module: determining the leakage location based on the preset sensor network and the working data of the hydraulic support;

[0010] A leakage analysis module: determining the fault type of the hydraulic support based on the leakage diagnosis result and in combination with the leakage location;

[0011] A fault warning module: generating a fault warning report based on the fault type of the hydraulic support and sending it to the control end.

[0012] The present invention provides a leakage diagnosis system for a hydraulic support. The data acquisition module includes:

[0013] Node determination unit: Analyze the hydraulic support and the environment where the hydraulic support is located respectively, and determine a number of sensor nodes based on the analysis results;

[0014] Network construction unit: Construct a sensor network based on the sensor nodes and a preset network protocol;

[0015] Data processing unit: Monitor and collect the working data of the hydraulic support in real time based on the sensor network, and perform initial processing on the collected working data of the hydraulic support.

[0016] The present invention provides a leakage diagnosis system for a hydraulic support. The node determination unit includes:

[0017] System determination subunit: Analyze the structure of the hydraulic support to determine several key systems of the hydraulic support;

[0018] Signal acquisition subunit: Determine several sensors to be deployed for each key system based on a preset system-sensor data table, and deploy corresponding sensors in each key system to monitor and collect the change signals of the key system;

[0019] Data acquisition subunit: Deploy sensors of a preset type in the environment where the hydraulic support is located and collect environmental data;

[0020] Data analysis subunit: Analyze the change signals of each key system and the environmental data based on a preset analysis method;

[0021] Part determination subunit: Determine several key parts of each key system based on the analysis results;

[0022] Node determination subunit: Determine several initial nodes for each key part of each key system based on a preset system-part-node data table;

[0023] Node analysis subunit: Analyze all the initial nodes, and then determine several central nodes.

[0024] The present invention provides a leakage diagnosis system for a hydraulic support. The data processing unit includes:

[0025] Preliminary analysis subunit: Perform preliminary analysis on the working data of the hydraulic support to determine the real-time node status value of each node;

[0026] Abnormality judgment subunit: Judge whether a node is abnormal based on the node status value of each node and a preset node status threshold;

[0027] Abnormal sending subunit: If an abnormality occurs, determine the corresponding node as an abnormal node, transmit the data of the abnormal node to the central node, and at the same time transmit the data of the nodes other than the abnormal node to the central node;

[0028] Determine the data sent to the central node as the working data of the initially processed hydraulic support.

[0029] The present invention provides a leakage diagnosis system for a hydraulic support. The preliminary analysis subunit includes:

[0030] Data extraction block: Preprocess the working data of the hydraulic support, and extract the data related to the node state of each sensor node based on a preset data extraction method;

[0031] State acquisition block: Determine the real-time node state value of each sensor node based on the data related to the node state of each sensor node:

[0032] ; where is the real-time node state value of the i-th sensor node, is the weight of the j-th sensor under the i-th sensor node, is the real-time monitoring value of the j-th sensor under the i-th sensor node, is the preset reference value of the j-th sensor under the i-th sensor node, is the number of sensors deployed by the i-th sensor node, is the error correction factor of the real-time monitoring value of the j-th sensor under the i-th sensor node, is the standard deviation of the historical monitoring values of the j-th sensor under the i-th sensor node, is the preset time correction coefficient.

[0033] The present invention provides a leakage diagnosis system for a hydraulic support. The leakage diagnosis module includes:

[0034] Pretreatment unit: Perform noise filtering and data smoothing on the initially processed working data of the hydraulic support, and perform normalization processing on different types of sensor data;

[0035] Attribute acquisition unit: Analyze the attributes of the hydraulic support, and then determine the attributes of the hydraulic support;

[0036] Method determination unit: Determine the leakage diagnosis method based on the attributes of the hydraulic support and the preset attribute-diagnosis method;

[0037] 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;

[0038] Result determination unit: Obtain the historical data of the hydraulic support, construct a data-driven leakage diagnosis model through a preset algorithm and the standard working parameter range of the hydraulic support, and then output the leakage diagnosis result.

[0039] The present invention provides a leakage diagnosis system and method for a hydraulic support, including: pressure-flow analysis method, pressure difference analysis method, temperature change analysis method, and vibration mode analysis method.

[0040] The present invention provides a leakage diagnosis method for a hydraulic support, including:

[0041] Step 1: Construct 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.

[0042] Step 2: Analyze the initially processed working data of the hydraulic support, and perform leakage diagnosis in combination with a preset method.

[0043] Step 3: Determine the leakage location based on the preset sensor network and the working data of the hydraulic support.

[0044] Step 4: Based on the leakage diagnosis result and in combination with the leakage location, determine the fault type of the hydraulic support.

[0045] Step 5: Generate a fault warning report based on the fault type of the hydraulic support and send it to the control end.

[0046] Compared with the prior art, the beneficial effects of the present application are as follows:

[0047] By monitoring, diagnosing, locating, and analyzing the leakage problem of the hydraulic support in real time, a full-process automated diagnosis system is constructed to 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. Description of the Drawings

[0048] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0049] Figure 1 It is a schematic structural diagram of the leakage diagnosis system of the hydraulic support provided by the embodiment of the present invention.

[0050] Figure 2 It is a schematic flow diagram of the leakage diagnosis system method of the hydraulic support provided by the embodiment of the present invention. Detailed implementation manners

[0051] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without making creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0052] Embodiment 1:

[0053] The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, as Figure 1 shown, including:

[0054] A data acquisition module: constructing a sensor network to monitor and acquire the working data of the hydraulic support in real time, and then performing initial processing on the working data of the hydraulic support;

[0055] A leakage diagnosis module: analyzing the working data of the hydraulic support after initial processing, and performing leakage diagnosis in combination with a preset method;

[0056] A leakage location module: determining the leakage location based on the preset sensor network and the working data of the hydraulic support;

[0057] A leakage analysis module: determining the fault type of the hydraulic support based on the leakage diagnosis result and in combination with the leakage location;

[0058] A fault warning module: generating a fault warning report based on the fault type of the hydraulic support and sending it to the control end.

[0059] In this embodiment, the working data of the hydraulic support are key parameters collected by sensors during operation, including real-time data such as pressure, flow rate, temperature, vibration, displacement, etc. These data reflect the working state of the hydraulic support. For example, the sensor records that the pressure data of a certain support cylinder of the hydraulic support is 30 MPa, and the normal range is 25 - 35 MPa, indicating that the support is working normally. If the monitored pressure suddenly drops to 15 MPa, there may be a leakage.

[0060] In this embodiment, the preset method is an algorithm or standard process for analysis and diagnosis preset in the system, usually including threshold setting, data models or logical rules. These methods are used to judge whether there are abnormal situations in the system. For example, the preset method defines that when the pressure drops by more than 10%, the flow rate increases by 15%, and the temperature rises abnormally by 5°C, the system determines that a leakage has occurred;

[0061] In this embodiment, the leakage diagnosis is based on the collected working data and a preset method to analyze the hydraulic system, and determine whether there is hydraulic oil leakage and the severity of the leakage. For example: System analysis shows that the oil pressure of a certain support decreases and the flow rate increases abnormally. Combining with the rising temperature, the diagnosis result indicates that there is a medium-level leakage in the hydraulic pipeline.

[0062] In this embodiment, the leakage location is accurately determined by analyzing the sensor data and the system model, including components such as hydraulic cylinders, valves, and pipelines. For example: The analysis of the leakage location module shows that the leakage point is at the interface of the main support cylinder, and the reason may be the wear of the sealing ring.

[0063] In this embodiment, the fault types of the hydraulic support are further analyzed according to the leakage diagnosis results and the leakage locations, such as seal aging, pipeline cracks, joint loosening, etc. For example: The diagnosis result shows that the leakage point is in the hydraulic valve group, and the fault type is internal leakage caused by spool wear;

[0064] In this embodiment, the fault warning report is a report automatically generated by the system, which details the fault diagnosis results, leakage locations, fault types, and treatment suggestions, and sends them to management or maintenance personnel. For example, the report states that: The leakage location is at the No. 2 main cylinder of the support, the fault type is seal aging, and it is recommended to stop the machine for maintenance;

[0065] In this embodiment, the control end is the monitoring center or operation platform of the system, which is used to receive the fault warning report, monitor the state of the hydraulic support, and perform remote control. For example: After receiving the leakage alarm, the control end automatically notifies the maintenance personnel and can remotely shut down the hydraulic system to prevent the accident from expanding.

[0066] The beneficial effects of the above technical solutions are as follows: By real-time monitoring, diagnosing, locating, and analyzing the leakage problems of the hydraulic support, a full-process automated diagnosis system is constructed, which can identify the leakage location and fault types, 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.

[0067] Embodiment 2:

[0068] The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, including:

[0069] Node determination unit: Analyze the hydraulic support and the environment where the hydraulic support is located respectively, and determine a number of sensor nodes based on the analysis results;

[0070] Network construction unit: Construct a sensor network based on the sensor nodes and a preset network protocol;

[0071] Data processing unit: It 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.

[0072] In this embodiment, a sensor node refers to a single sensing device arranged in the hydraulic support and its environment, which is used to collect specific physical or environmental parameters (such as pressure, flow rate, 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.

[0073] In this embodiment, the sensor network is a system composed of multiple sensor nodes interconnected through network protocols, which is used to realize data collection, transmission and sharing. The sensor network can adopt wired or wireless connections to ensure that data at different positions can be summarized and analyzed in real time. The sensor network includes pressure sensor nodes, temperature sensor nodes arranged on the support, and flow sensor nodes installed on the hydraulic pipeline, and transmits the data to the control center through wireless communication protocols (such as LoRa or Zigbee) to realize the overall state monitoring of the hydraulic support.

[0074] The beneficial effects of the above technical solution are: By jointly analyzing the hydraulic support and the environment, an efficient sensor network is constructed, integrating the functions of real-time monitoring and preliminary data processing, significantly improving the comprehensiveness of data collection and the stability of network transmission, and laying a foundation for accurate leakage diagnosis under complex working conditions.

[0075] Embodiment 3:

[0076] The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support. The node determination unit includes:

[0077] System determination subunit: Analyze the structure of the hydraulic support to determine several key systems of the hydraulic support;

[0078] Signal acquisition subunit: Based on the preset system-sensor data table, determine several sensors to be deployed for each key system, and deploy corresponding sensors in each key system to monitor and collect the change signals of the key system;

[0079] Data acquisition subunit: Deploy preset types of sensors in the environment where the hydraulic support is located and collect environmental data;

[0080] Data analysis subunit: Analyze the change signals of each key system and the environmental data based on the preset analysis method;

[0081] Part determination subunit: Determine several key parts of each key system based on the analysis results;

[0082] Node determination subunit: Determine a number of initial nodes for each key part of each key system based on a preset system - part - node data table;

[0083] Node analysis subunit: Analyze all the initial nodes to further determine a number of central nodes.

[0084] In this embodiment, the key part refers to the core position in the key system of the hydraulic support that is most prone to leakage or failure, usually including high - pressure cylinders, hydraulic pipe interfaces, valve groups, etc. Focusing on monitoring these parts can improve the diagnostic efficiency and accuracy. For example, the sealing interface of the main support cylinder of the hydraulic support is a key part because it bears high pressure and wear of the seal is likely to cause leakage.

[0085] In this embodiment, the initial nodes are the positions of sensors deployed on the key parts according to the preset system - part - node data table, representing all the monitoring points recommended in the preliminary design stage. These nodes cover the key parts to ensure complete data collection. For example, a pressure sensor and a temperature sensor are deployed at the sealing interface (key part) of the main support cylinder, and the installation points corresponding to these sensors are the initial nodes.

[0086] In this embodiment, the central nodes are the optimal monitoring points determined after analysis and optimization from the initial nodes, usually selected based on data importance, sensor cost, and network redundancy, and finally used for actual monitoring. For example, through analysis, it is found that the data of the pressure sensor is the most critical for diagnosing leakage. Therefore, the pressure sensor is retained as the central node at the sealing interface of the main support cylinder, while the temperature sensor is removed.

[0087] In this embodiment, the key part is the result of system structure analysis, representing the area that needs to be monitored keyly. The initial nodes are all the sensor points arranged on the key parts, used to comprehensively monitor the changes of the key parts. The central nodes are the final monitoring points after optimizing the initial nodes, reducing redundancy, lowering costs, and at the same time ensuring the monitoring accuracy. Example of the relationship: 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 the initial nodes. After analysis, it is found that the pressure data can best reflect the leakage problem. Therefore, finally only the pressure sensor is retained and determined as the central node.

[0088] 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 their corresponding sensor node deployment rules, serving as the basis for node determination and arrangement. It is an important tool in the system design stage, used to ensure the reasonable arrangement of sensors, the comprehensiveness and effectiveness of data collection.

[0089] The beneficial effects of the above technical solution are as follows: Through systematic structure analysis and multi-level data acquisition and processing, the accurate determination from the environment to the key parts and from the initial nodes to the central node is realized, the sensor deployment and node division are optimized, the pertinence of signal acquisition and the accuracy of diagnostic analysis are improved, and efficient support is provided for leakage diagnosis under complex working conditions.

[0090] Embodiment 4:

[0091] The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support. The data processing unit includes:

[0092] Preliminary analysis subunit: Perform preliminary analysis on the working data of the hydraulic support to determine the real-time node status value of each node;

[0093] Abnormality judgment subunit: Judge whether a node is abnormal based on the node status value of each node and a preset node status threshold;

[0094] Abnormality sending subunit: If an abnormality occurs, determine the corresponding node as an abnormal node, transmit the data of the abnormal node to the central node, and at the same time transmit the node data other than the abnormal node to the central node;

[0095] Determine the data sent to the central node as the working data of the hydraulic support after initial processing.

[0096] In this embodiment, the preset node status threshold refers to the reference range or critical value set by the system according to the normal operating conditions of the hydraulic support, and is used to judge whether the data monitored by the sensor is abnormal. The threshold is usually set based on empirical data, historical data or engineering design standards. Example: For a pressure sensor node, the preset normal working 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.

[0097] In this embodiment, an abnormal node refers to a sensor node whose monitored data exceeds the preset node status threshold range, indicating that there may be a leakage or a fault at this position, and further analysis and processing are required. Example: The temperature monitored by the temperature sensor node of a certain hydraulic support is 90°C, while the preset normal temperature threshold range is 20 - 60°C. Therefore, this temperature node is determined as an abnormal node. Assume that pressure and temperature sensor nodes are arranged at the sealing interface of the hydraulic support: The system sets the pressure threshold as 25 - 35 MPa and the temperature threshold as 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.

[0098] The beneficial effects of the above technical solution are as follows: By introducing a real-time monitoring mechanism for node status and a hierarchical anomaly judgment mechanism, the classification processing and synchronous transmission of data for abnormal nodes and normal nodes are realized, reducing data redundancy, improving the efficiency of anomaly location and the accuracy of data transmission, and providing reliable support for the rapid decision-making of the central node.

[0099] Embodiment 5:

[0100] The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support. The preliminary analysis subunit includes:

[0101] Data extraction block: Preprocess the working data of the hydraulic support and extract the data related to the node status of each sensor node based on a preset data extraction method;

[0102] Status acquisition block: Determine the real-time node status value of each sensor node based on the data related to the node status of each sensor node:

[0103] ; where is the real-time node status value of the i-th sensor node, is the weight of the j-th sensor under the i-th sensor node, is the real-time monitoring value of the j-th sensor under the i-th sensor node, is the preset reference value of the j-th sensor under the i-th sensor node, is the number of sensors deployed by the i-th sensor node, is the error correction factor of the real-time monitoring value of the j-th sensor under the i-th sensor node, is the standard deviation of the historical monitoring values of the j-th sensor under the i-th sensor node, is the preset time correction coefficient.

[0104] In this embodiment, the error correction factor is a coefficient used to correct the deviation caused by environmental interference, sensor aging, installation error, etc. in the real-time monitoring data of the sensor. It is determined through historical data analysis or calibration tests 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 is multiplied by the error correction factor to eliminate or reduce data errors. For example: The historical record of a pressure sensor shows 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 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;

[0105] In this embodiment, the preset time correction coefficient is used to weight the historical data of the sensor to reflect the influence weights of data in different time periods on the current state value. Generally, the weight of newer data is larger, and the weight of older data is smaller, which is used to capture the dynamic change trend of the current state. Formula meaning: In the calculation of the state value, the influence of the historical monitoring value is adjusted through 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. To pay more attention to the recent changes, the preset time correction coefficient weights the historical data: the weight of the data on the first day is 0.5; the weight of the data on the second day is 0.8; the weight of the data on the third day (today) is 1.0. In this way, the monitoring data today has the greatest influence on the state value, and the influence of earlier data gradually decreases, ensuring that the state value reflects the latest situation.

[0106] The beneficial effects of the above technical solutions are as follows: By constructing a dynamic calculation model for the real-time node state value 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 the hydraulic support state monitoring are significantly improved, laying a foundation for intelligent diagnosis.

[0107] Embodiment 6:

[0108] The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support. The leakage diagnosis module includes:

[0109] Pretreatment unit: Perform noise filtering and data smoothing processing on the initially processed working data of the hydraulic support, and perform normalization processing on the data of different types of sensors;

[0110] Attribute acquisition unit: Analyze the attributes of the hydraulic support to determine the attributes of the hydraulic support;

[0111] Method determination unit: Determine the leakage diagnosis method based on the attributes of the hydraulic support and the preset attribute-diagnosis method;

[0112] 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;

[0113] Result determination unit: Obtain the historical data of the hydraulic support, and construct a data-driven leakage diagnosis model through a preset algorithm and the standard working parameter range of the hydraulic support, and then output the leakage diagnosis result.

[0114] 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, it is determined that its attributes include the load capacity of the support (such as the maximum support force is 1000 tons), the pressure range of the hydraulic system, the environmental temperature adaptation range (-20°C to 50°C), etc.;

[0115] In this embodiment, the attributes of the hydraulic support refer to the characteristic parameters inherent in its design and operation process, including structural attributes (such as the height and weight of the support), performance attributes (such as pressure, flow rate), and adaptability attributes (such as the applicable environment). For example, the attributes of the hydraulic support include:

[0116] Structural attributes: the height of the support is 3 meters and the weight is 2 tons; Performance attributes: the pressure range of the hydraulic cylinder is 25 - 35 MPa, and the flow rate is 5 - 10 L / min; Adaptability attributes: it can work normally in a dusty environment, and the protection level is IP65.

[0117] In this embodiment, the working mechanism of the hydraulic support refers to the operating principle when it supports the ore rock or load, including processes such as the force on the hydraulic cylinder, the flow of hydraulic oil, and the pressure balance adjustment. Usually, it involves multiple components working together. For example, in the working mechanism, the hydraulic oil is transported to the hydraulic cylinder through the pump station, and the hydraulic cylinder provides a support force at a pressure of 25 MPa. If the pressure suddenly drops and the support force weakens, it may cause system leakage.

[0118] In this embodiment, the mathematical model of the hydraulic system represents the relationships and laws of the hydraulic system operation process with mathematical formulas or equations, and is usually used to simulate and analyze the performance or fault behavior of the hydraulic support; In this embodiment, the standard working parameter range is the value range of each key parameter of the hydraulic support under normal working conditions, which is used to judge whether the system is operating normally. For example, the standard working parameter range of the hydraulic support may include: hydraulic oil pressure: 25 - 35 MPa; flow rate: 5 - 10 L / min; temperature: 20 - 60°C. If the actual parameters exceed this range, there may be leakage or other faults.

[0119] 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 methods such as machine learning and statistical analysis, and is used to diagnose whether the hydraulic system has leakage and its possible causes. For example, a neural network model trained with the historical operation data of the hydraulic support (such as the pressure fluctuation trend, abnormal flow rate change) can output the possible leakage location and degree when a sudden increase in flow rate is detected in real time.

[0120] In this embodiment, the final analysis result output by the leakage diagnosis module includes the possible leakage location, severity, fault type, and recommended measures. For example, the diagnosis result shows that there is a slight leakage (the flow rate exceeds the normal range by 15%) at the sealing interface of the main support cylinder, and it is recommended to replace the seal and recheck the pipeline pressure.

[0121] The beneficial effects of the above technical solution are as follows: By introducing multi-level diagnosis, organically combining data preprocessing, attribute analysis, mathematical modeling, and data-driven technology, the high-efficiency, intelligent, and precise hydraulic support leakage diagnosis is realized. The diagnosis method with different attributes is dynamically adapted, and a self-optimizing model is constructed through standard parameters and historical data, effectively improving the system adaptability and reliability.

[0122] Embodiment 7:

[0123] The embodiment of the present invention provides a leakage diagnosis system for a hydraulic support. The leakage diagnosis method includes: pressure-flow analysis method, pressure-difference analysis method, temperature-change analysis method, and vibration-mode analysis method.

[0124] 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 diagnosis basis. For example, the pressure difference between the main oil cylinder and the branch pipeline of the hydraulic support is usually 5 MPa, but the actual monitoring finds that the pressure difference increases to 8 MPa, which may be caused by the leakage of the main oil cylinder seal;

[0125] In this embodiment, the temperature-change analysis method is that the leakage of hydraulic oil will cause abnormal local temperature changes. By monitoring the temperature change trend of key parts, the leakage can be indirectly diagnosed. When leakage causes oil loss or increased friction, the local temperature rises. For example, the temperature sensor near a valve group of the hydraulic support shows that the temperature continuously rises by 10 °C, while the temperatures of other parts are normal, which may be caused by the leakage of this valve group;

[0126] 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 spectrum and intensity changes of the vibration signal, the leakage location and type can be judged. For example, during the operation of a certain support, the vibration monitoring equipment detects a characteristic peak with a frequency of 500 Hz. Combining with experience analysis, it shows that this characteristic is associated with the internal leakage of the oil pipe.

[0127] The beneficial effects of the above technical solution are as follows: By combining pressure-flow analysis, pressure-difference analysis, temperature-change analysis, and vibration-mode analysis, multi-dimensional and in-depth hydraulic support leakage diagnosis is realized, capturing leakage characteristics, improving the diagnosis accuracy and efficiency, being able to quickly locate the fault source and quantify the leakage degree, and providing reliable support for preventive maintenance and extending the equipment life.

[0128] Example 8:

[0129] An embodiment of the present invention provides a leakage diagnosis system for a hydraulic support, as Figure 2 shown, including:

[0130] Step 1: Construct 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;

[0131] Step 2: Analyze the working data of the hydraulic support after initial processing, and perform leakage diagnosis in combination with a preset method;

[0132] Step 3: Determine the leakage location based on the preset sensor network and the working data of the hydraulic support;

[0133] Step 4: Determine the fault type of the hydraulic support based on the leakage diagnosis result and in combination with the leakage location;

[0134] Step 5: Generate a fault warning report based on the fault type of the hydraulic support and send it to the control end.

[0135] The beneficial effects of the above technical solutions are as follows: By monitoring, diagnosing, locating, and analyzing the leakage problems of the hydraulic support in real time, a full-process automated diagnosis system is constructed, the leakage location and fault type are identified, timely warnings are provided, the diagnosis efficiency and maintenance response speed are greatly improved, the operation risk and maintenance cost are significantly reduced, and important technical support is provided for the intelligent operation and maintenance of coal mine equipment.

[0136] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various 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 fault warning report based on the fault type of hydraulic support and sends it to the control end; The data acquisition module includes: 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; 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.

2. The leakage diagnosis system of the hydraulic support according to claim 1, 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 are determined as the working data of the hydraulic support after initial processing.

3. 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 working data of the hydraulic support, and normalizes the sensor data of different types; 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.

4. The leakage diagnosis system of the hydraulic support according to claim 3, characterized in that: Leakage diagnosis methods include: pressure flow analysis, pressure difference analysis, temperature change analysis and vibration mode analysis.

5. 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; Wherein, step 1 includes: Analyze the hydraulic support and the environment where the hydraulic support is located respectively, and determine several sensor nodes based on the analysis results; Build a sensor network based on sensor nodes and preset network protocols; Based on the sensor network, the working data of the hydraulic support is monitored and collected in real time, and the collected working data of the hydraulic support is initially processed; Among them, the hydraulic support and the environment where the hydraulic support is located are analyzed respectively, including: Conduct structural analysis on hydraulic supports to determine several key systems of hydraulic supports; 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; Deploy preset types of sensors in the environment where the hydraulic support is located and collect environmental data; Analyze the change signals and environmental data of each key system based on preset analysis methods; Determine several key parts of each key system based on the analysis results; Determine a number of initial nodes of each key part of each key system based on a preset system-part-node data table; All initial nodes are analyzed to determine several central nodes.

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