Performance analysis method of hydraulic support for coal mine

Abstract

The invention provides a performance analysis method of a hydraulic support for a coal mine, and belongs to the technical field of monitoring and analysis of coal mine supporting equipment, and the performance analysis method comprises the following steps: step 1, collecting real-time data of a preset type, and meanwhile, collecting environmental parameters of the preset type; 2, constructing a stratified analysis logic model based on all the collected data, and obtaining a model output result; 3, a plurality of physical analysis models are constructed based on the output result of the stratified analysis logic model, and then performance data of the hydraulic support are obtained based on a preset analysis method and the physical analysis models; step 4, based on the performance data of the hydraulic support and a preset method, constructing a fault propagation path among the components of the hydraulic support, and determining a fault influence condition of each component of the hydraulic support; and step 5, generating a performance analysis report of the hydraulic support based on the performance data of the hydraulic support and the fault influence condition of each component, thereby remarkably enhancing the safety and efficiency of coal mine support.

Description

Technical Field

[0001] The invention relates to the technical field of monitoring and analyzing coal mine support equipment, and in particular to a performance analysis method for a hydraulic support used in a coal mine. Background Art

[0002] Hydraulic supports are the core support equipment in coal mining, and their performance is directly related to the safety and efficiency of mine mining. As the complexity of the coal mining environment increases, the demand for monitoring and analysis of hydraulic supports performance continues to increase.

[0003] Existing technical solutions usually analyze the key performance of hydraulic supports through single parameter monitoring or simple physical models, such as single parameter monitoring based on hydraulic cylinder pressure or support displacement. However, these methods often lack multi-parameter correlation analysis, making it difficult to fully and accurately reflect the comprehensive performance of hydraulic supports, unable to achieve multi-dimensional comprehensive analysis of the key performance of hydraulic supports, and lack accurate modeling of fault propagation paths and the influence relationship between components, resulting in low reliability of performance evaluation results and difficulty in providing accurate guidance for equipment maintenance and optimization.

[0004] Therefore, the present invention provides a performance analysis method for a hydraulic support for a coal mine. Summary of the invention

[0005] The present invention provides a performance analysis method for a hydraulic support for coal mines, which realizes a comprehensive and multi-dimensional evaluation of the performance of the hydraulic support through the combination of a sensor network and a multi-layer analysis model, improves the accuracy of diagnosis through fault propagation path modeling and component impact analysis, and generates a performance analysis report to provide scientific guidance for support maintenance and optimization, thereby significantly enhancing the safety and efficiency of coal mine support.

[0006] The present invention provides a performance analysis method for a hydraulic support for a coal mine, comprising: Step 1: Install a preset sensor network at key locations of the hydraulic support to collect real-time data of a preset type, and at the same time, collect environmental parameters of a preset type based on the preset sensors; Step 2: Build a hierarchical analysis logic model based on all collected data and obtain the model output results; Step 3: construct several physical analysis models based on the output results of the hierarchical analysis logic model, and then obtain the performance data of the hydraulic support based on the preset analysis method and the physical analysis model; Step 4: construct the fault propagation path between the components of the hydraulic support based on the performance data of the hydraulic support and the preset method, and determine the fault impact of each component of the hydraulic support; Step 5: Generate a performance analysis report of the hydraulic support based on the performance data of the hydraulic support and the impact of failures of each component.

[0007] The present invention provides a performance analysis method for a hydraulic support for a coal mine, which constructs a hierarchical analysis logic model based on fused data and obtains the model output result, including: Build a hierarchical logic model based on all collected data; The corresponding fuzzy logic rules of each main level are defined based on the preset definition method, and the relationship between the levels is analyzed through logical reasoning to output the results of the model.

[0008] The present invention provides a performance analysis method for a hydraulic support for a coal mine, which constructs a hierarchical logic model based on all collected data, including: Conduct a first structural analysis on the hydraulic support, and determine the main layers of the hierarchical logic model based on the analysis results, including: equipment layer, environment layer, and interaction layer; Get the input variables and output variables of the device layer, environment layer and interaction layer respectively; Determine the modeling method for each main level based on the preset level-modeling method data table; Constructing analytical models for each major level based on the modeling approach, input variables, and output variables of each major level; Conduct interaction analysis on the device layer, environment layer and interaction layer to determine the interaction relationship between them; Determine the mapping rules between the device layer, the environment layer and the interaction layer based on the preset interaction relationship-mapping rule data table; The hierarchical logic model is determined based on the interaction relationship and mapping rules among the device layer, the environment layer and the interaction layer in combination with the analysis models of the device layer, the environment layer and the interaction layer.

[0009] The present invention provides a performance analysis method for a hydraulic support for a coal mine, which obtains input variables and output variables of an equipment layer, an environment layer, and an interaction layer respectively, including: Performing a second structural analysis on the hydraulic support to obtain component characteristics of the hydraulic support; Determine the input variables of the equipment layer based on the real-time data collected by the preset sensor network and the component characteristics of the hydraulic support; Determine the device layer output variable based on a preset formula and the device layer input variable; Determine input variables of the environmental layer based on environmental parameters of a preset type collected by a preset sensor; Determine the output variables of the environment layer based on the preset environment model and the input variables of the environment layer; Determine the input variables of the interaction layer based on the output variables of the device layer and the output variables of the environment layer; The output variables of the interaction layer are determined based on several preset models.

[0010] The present invention provides a performance analysis method for a hydraulic support for a coal mine, which constructs a plurality of physical analysis models based on the output results of a hierarchical analysis logic model, and then obtains the performance data of the hydraulic support based on a preset analysis method and the physical analysis model, including: Extract key parameters related to hydraulic support performance from the output of the hierarchical logic model; Based on key parameters related to the performance of the hydraulic support and several preset physical modeling methods, a physical analysis model corresponding to each preset physical modeling method is constructed; Obtaining the analysis method corresponding to the physical analysis model based on the preset model-analysis method data table; Based on all physical analysis models and the analysis method corresponding to each physical analysis model, the performance of the hydraulic support is analyzed to obtain the performance data of the hydraulic support.

[0011] The present invention provides a performance analysis method for a hydraulic support for a coal mine, which constructs a fault propagation path between components of the hydraulic support based on performance data of the hydraulic support and a preset method, and determines the fault influence of each component of the hydraulic support, including: Acquire the properties of each component of the hydraulic support, and build a mechanical model for each component based on the properties of each component of the hydraulic support; Determine the coupling relationship between the hydraulic support components based on the properties of each component of the hydraulic support and a preset algorithm; Construct a coupling relationship model between components based on the coupling relationship between hydraulic support components; Determine and establish a time series diagram of fault propagation based on the output results of the mechanical models of all components, the coupling relationship model between components, and the performance data of the hydraulic support; Determine the fault propagation path based on the output results of the coupling relationship model between components, the time series diagram of fault propagation, and the preset analysis method; Obtain and analyze the historical failure data of the hydraulic support to determine several failure modes and failure data of the hydraulic support; Determine the failure coefficient of each component on each fault propagation path based on the performance data of the hydraulic support, a number of failure modes and failure data of the hydraulic support, and the failure propagation path; The fault impact of each component on each fault path is obtained based on the fault coefficient of each component on each fault propagation path and a preset path-coefficient-fault condition database.

[0012] The present invention provides a performance analysis method for a hydraulic support for a coal mine, wherein the failure modes include: a mechanical failure mode, a hydraulic failure mode and an electronic failure mode.

[0013] The present invention provides a performance analysis method for a hydraulic support for a coal mine, which determines the fault coefficient of each component on each fault propagation path, including: Based on the performance data of the hydraulic support, several failure modes and failure data of the hydraulic support, and the failure propagation path, the failure-related data of each component on each failure path is determined; Determine the nonlinear coupling coefficient between the components based on the output result of the coupling relationship model between the components; The fault coefficient of each component on each fault propagation path is determined based on the fault-related data of each component on each fault path and the nonlinear coupling coefficient between the components: ;in, is the failure coefficient of the i-th component on the g-th fault path, is the failure probability of the i-th component on the g-th fault path under the m-th fault mode, is the fault severity of the i-th component on the g-th fault path under the m-th fault mode, is the weight factor of the i-th component on the g-th fault path under the m-th fault mode, is the nonlinear coupling coefficient between the i-th component and the j-th component on the g-th fault path, is the preset maximum coupling coefficient, is the preset reference fault coefficient, n is the number of components on the g-th fault path, is the state coefficient of the i-th component on the g-th fault path, is the preset time influence coefficient, is the number of failure modes.

[0014] Compared with the prior art, the present invention has the following beneficial effects: Through the combination of sensor networks and multi-layer analysis models, a comprehensive and multi-dimensional evaluation of the performance of hydraulic supports is achieved. The diagnostic accuracy is improved through fault propagation path modeling and component impact analysis. The generated performance analysis report provides scientific guidance for support maintenance and optimization, significantly enhancing the safety and efficiency of coal mine support. 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 1It is a flow chart of a performance analysis method of a hydraulic support for coal mines provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] 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.

[0018] Example 1 The embodiment of the present invention provides a performance analysis method for a hydraulic support for a coal mine, such as Figure 1 As shown, including: Step 1: Install a preset sensor network at key locations of the hydraulic support to collect real-time data of a preset type, and at the same time, collect environmental parameters of a preset type based on the preset sensors; Step 2: Build a hierarchical analysis logic model based on all collected data and obtain the model output results; Step 3: construct several physical analysis models based on the output results of the hierarchical analysis logic model, and then obtain the performance data of the hydraulic support based on the preset analysis method and the physical analysis model; Step 4: construct the fault propagation path between the components of the hydraulic support based on the performance data of the hydraulic support and the preset method, and determine the fault impact of each component of the hydraulic support; Step 5: Generate a performance analysis report of the hydraulic support based on the performance data of the hydraulic support and the impact of failures of each component.

[0019] In this embodiment, the hydraulic support is a device used to support the roof during underground mining in coal mines. It adjusts the height of the support through a hydraulic system to prevent mine collapse. Common models such as the ZY6800 support have strong load-bearing capacity and height adjustment functions, and can provide safe support in different working environments. For example, the ZY6800 support can automatically adjust its height under the pressure of the roof of the coal mine working face to maintain the stability of the roof; In this embodiment, the key parts refer to the parts of the hydraulic support that are crucial to its normal operation. Once these parts fail, the entire support may fail, or even cause a safety accident. Common key parts include hydraulic cylinders and valve groups. For example, the hydraulic cylinder is the core actuator of the hydraulic support. If there is oil leakage or insufficient pressure, the support will not be able to effectively support the top plate; In this embodiment, the sensor network is a system composed of multiple sensors, which is used to monitor the operating status of the hydraulic support in real time. The sensor network may include various types of sensors, such as pressure sensors, temperature sensors, displacement sensors, etc. These sensors cooperate with each other to provide real-time data of various components of the support. The sensor network can monitor the hydraulic system pressure of the hydraulic support, the displacement of the support, and the temperature change of the surrounding environment in real time, thereby helping to perform accurate performance evaluation; In this embodiment, environmental parameters refer to external factors that affect the performance of the hydraulic support, including temperature, humidity, coal seam hardness, etc. These parameters will directly or indirectly affect the working efficiency and service life of the hydraulic support. For example, when the working surface temperature is too high, the viscosity of the hydraulic oil of the hydraulic support will decrease, which may cause the working pressure of the support to drop.

[0020] In this embodiment, real-time data is dynamic information collected by sensors during the operation of the hydraulic support, which reflects the performance of the support in actual work and helps analyze whether there is any abnormality in the support. For example, by real-time monitoring of the telescopic displacement curve of the hydraulic cylinder, it can be determined whether the lifting and lowering of the support is normal, and whether the support is stuck or slow to respond can be discovered in time.

[0021] The beneficial effects of the above technical solution are: through the combination of sensor networks and multi-layer analysis models, a comprehensive and multi-dimensional evaluation of the performance of hydraulic supports is achieved, the diagnostic accuracy is improved through fault propagation path modeling and component impact analysis, and the performance analysis report generated provides scientific guidance for support maintenance and optimization, significantly enhancing the safety and efficiency of coal mine support.

[0022] Example 2 The embodiment of the present invention provides a performance analysis method for a hydraulic support for a coal mine, which constructs a hierarchical analysis logic model based on fused data and obtains the model output result, including: Build a hierarchical logic model based on all collected data; The corresponding fuzzy logic rules of each main level are defined based on the preset definition method, and the relationship between the levels is analyzed through logical reasoning to output the model results.

[0023] In this embodiment, the hierarchical logic model is a model that divides the behavior of a complex system into levels for analysis. It is often used to understand and simulate the interaction between different levels. For example, in the performance analysis of coal mine hydraulic supports, the hierarchical logic model can be divided into "equipment layer", "environmental layer" and "interaction layer". For example, the equipment layer is responsible for monitoring the stress of the hydraulic cylinder, the environmental layer focuses on humidity conditions, and the interaction layer studies the effect of humidity on the fatigue of the hydraulic cylinder material.

[0024] In this embodiment, the fuzzy logic rule uses fuzzy mathematics to quantify uncertainty factors into rules for analyzing the behavior relationship of the system. For example, a fuzzy logic rule may be "if the humidity exceeds 80% and the temperature exceeds 40°C, the performance of the hydraulic oil will decrease significantly". This rule can be inferred based on the input data to obtain an evaluation of the system performance; In this embodiment, logical reasoning is the process of deriving the analysis results layer by layer according to the rules of the model and the input data. For example, by inputting the hydraulic cylinder stress data and the high humidity environment data, logical reasoning can derive the performance score of the hydraulic support. For example, the analysis result may show that the performance score of the support in the current environment is 85 points (out of 100 points); In this embodiment, the model output result is the final output after logical reasoning, which is used to evaluate the equipment status or provide a basis for decision-making. For example, after the model runs, the output of the equipment health score may be 75 points, and a "risk of hydraulic oil performance degradation" fault warning may be given. This result can help coal mine engineers perform maintenance in advance.

[0025] The beneficial effects of the above technical solution are: by constructing a hierarchical analysis logic model and introducing fuzzy logic rules, intelligent reasoning of complex system relationships and precise integration of multi-level data are realized, which significantly improves the intelligence and reliability of hydraulic support performance evaluation and provides strong support for scientific decision-making under complex working conditions.

[0026] Example 3 The embodiment of the present invention provides a performance analysis method for a hydraulic support for a coal mine, which constructs a hierarchical logic model based on all collected data, including: Conduct a first structural analysis on the hydraulic support, and determine the main layers of the hierarchical logic model based on the analysis results, including: equipment layer, environment layer, and interaction layer; Get the input variables and output variables of the device layer, environment layer and interaction layer respectively; Determine the modeling method for each main level based on the preset level-modeling method data table; Constructing analytical models for each major level based on the modeling approach, input variables, and output variables of each major level; Conduct interaction analysis on the device layer, environment layer and interaction layer to determine the interaction relationship between them; Determine the mapping rules between the device layer, the environment layer and the interaction layer based on the preset interaction relationship-mapping rule data table; The hierarchical logic model is determined based on the interaction relationship and mapping rules among the device layer, the environment layer and the interaction layer in combination with the analysis models of the device layer, the environment layer and the interaction layer.

[0027] In this embodiment, structural analysis refers to the decomposition and analysis of the various components of the hydraulic support and their functional relationships, clarifying the composition of the support and the role of each part. For example, the functional relationship between the hydraulic cylinder, support and valve group of the hydraulic support is analyzed. For example, the hydraulic cylinder pushes the support to move up and down through the hydraulic oil, the support bears the main task of supporting the rock formation, and the valve group is used to control the flow and pressure of the hydraulic oil; In this embodiment, the equipment layer is the basic layer of the model, which contains the performance data of the core components of the support and reflects the status of the equipment itself. For example, the equipment layer of a hydraulic support may include the stress monitoring data of the hydraulic cylinder and the pressure parameters of the pump station. For example, when the hydraulic cylinder is subjected to a working pressure of 20 MPa, the data is recorded as the input parameters of the equipment layer; In this embodiment, the environment layer is a layer in the model used to reflect the impact of the external environment on the performance of the equipment. If the humidity in the area where the coal mine is located is as high as 90%, this information will be recorded in the environment layer. High humidity may cause rust on the surface of the equipment, thereby affecting the life of the hydraulic cylinder; In this embodiment, the interaction layer describes the dynamic coupling relationship between the device layer and the environment layer, reflecting how the two affect each other. For example, the viscosity of the hydraulic oil will decrease as the temperature rises, thus affecting the operating efficiency of the hydraulic cylinder. The interaction layer will reveal how temperature changes affect the key performance of the device layer through dynamic simulation.

[0028] In this embodiment, input variables refer to external data required for the analysis model, which are used to describe the state or condition of each layer. For example: Equipment layer input: hydraulic cylinder pressure (e.g., 25 MPa) and support displacement data. Environment layer input: working surface temperature (e.g., 35°C) and humidity (e.g., 85%). Interaction layer input: the effect of temperature on hydraulic oil viscosity (e.g., viscosity decreases by 10%). In this embodiment, the output variable refers to the result derived through model analysis, reflecting the state or performance of each layer. For example, the output of the equipment layer: the stress state of the hydraulic cylinder (e.g., normal or abnormal), the stability of the support. The output of the environment layer: the degree of influence of the current environment on the performance of the support (e.g., "large influence"). The output of the interaction layer: the change in the operating state of the equipment caused by the change in the viscosity of the hydraulic oil (e.g., "may cause accelerated aging of the seal").

[0029] In this embodiment, the modeling method is a specific analysis method selected for each level, adapted to the characteristics and variables of the level, for example, the equipment level: using a mechanical model, such as using finite element analysis to simulate the force distribution of a hydraulic cylinder. The environment level: using a statistical model, analyzing the changing patterns of temperature and humidity through environmental sensor data. The interaction level: using a fuzzy model, using fuzzy logic to handle uncertainty relationships, such as the effect of temperature on equipment wear rate.

[0030] In this embodiment, the interaction relationship refers to the dynamic influence mechanism between the equipment layer and the environment layer, describing how they interact with each other. For example, high temperature (environmental layer) will cause the viscosity of the hydraulic oil to decrease (interaction layer), which in turn affects the sealing performance of the hydraulic cylinder (equipment layer), which may eventually cause abnormal operation of the bracket.

[0031] In this embodiment, the mapping rule converts the input variable into the output variable through a specific rule, reflecting the causal relationship between the variables. For example: Mapping rule example 1: "Hydraulic cylinder pressure exceeds the standard (exceeds 30 MPa) → stress abnormality (may cause fatigue cracks in the hydraulic cylinder)", mapping rule example 2: "Working surface temperature exceeds 40°C and humidity exceeds 90% → Support health status declines (needs to strengthen maintenance)".

[0032] The beneficial effect of the above technical solution is that by constructing a hierarchical logical model of the equipment layer, the environment layer and the interaction layer, the interaction analysis and mapping rule optimization between multiple layers are realized. This method systematically integrates multi-source data, reveals complex relationship networks, improves the accuracy of performance analysis and hierarchical management capabilities, and provides a new way to optimize the performance of hydraulic supports.

[0033] Example 4 The embodiment of the present invention provides a performance analysis method for a hydraulic support for a coal mine, which obtains input variables and output variables of a device layer, an environment layer, and an interaction layer respectively, including: Performing a second structural analysis on the hydraulic support to obtain component characteristics of the hydraulic support; Determine the input variables of the equipment layer based on the real-time data collected by the preset sensor network and the component characteristics of the hydraulic support; Determine the device layer output variable based on a preset formula and the device layer input variable; Determine input variables of the environmental layer based on environmental parameters of a preset type collected by a preset sensor; Determine the output variables of the environment layer based on the preset environment model and the input variables of the environment layer; Determine the input variables of the interaction layer based on the output variables of the device layer and the output variables of the environment layer; The output variables of the interaction layer are determined based on several preset models.

[0034] In this embodiment, the output variables of the equipment layer include: stress and strain calculation: based on the sensor data (such as force and displacement) and the geometric characteristics of the components, the stress and strain of each component of the hydraulic support are calculated by mechanical formulas or finite element analysis (FEA). For example, the compression force of the hydraulic cylinder on the column can be calculated by using the working pressure of the hydraulic cylinder and the geometric dimensions of the column, and then the stress of the column can be derived. Deformation and displacement: the displacement data obtained by the sensor can be directly used as an output variable to evaluate the degree of deformation of the hydraulic support. Bearing capacity: based on the stress and the yield strength of the material, the bearing capacity of the hydraulic support can be evaluated to determine whether there is a risk of structural failure. Fatigue life prediction: by monitoring the stress changes of the hydraulic support components and combining the fatigue performance data of the material, the fatigue life of the hydraulic support can be predicted.

[0035] In this embodiment, the output variables of the environmental layer include: the stability and bearing capacity of the hydraulic support under different temperatures and humidity: the deformation, stress, displacement, etc. of the hydraulic support are calculated by the influence of temperature changes; the compressive performance of the support: changes in geological pressure may affect the stability of the support. By calculating the deformation and stress of the support under different geological pressures, the compressive capacity of the support is obtained; the dynamic response of the support: the impact of external vibration or impact on the support. The dynamic response of the hydraulic support can be evaluated through a dynamic model to predict possible failures.

[0036] In this embodiment, the output variables of the interaction layer are indicators describing the overall performance or dynamic coupling effect obtained by analyzing the interaction between the equipment and the environment based on the output variables of the equipment layer and the environment layer. These variables usually reflect the changes in the equipment operating state under the influence of the environment, as well as the comprehensive impact of the equipment-environment interaction on the system performance. For example: Change in hydraulic oil viscosity: Due to the increase in ambient temperature (environmental layer output) and abnormal hydraulic oil pressure (equipment layer output), the interaction layer outputs "hydraulic oil viscosity decreases by 10%" after analysis. Seal wear rate: The interaction layer outputs the expected wear rate of the seal (for example, "wear rate increases by 20%) by simulating the combined effect of equipment force (equipment layer output) and humidity (environmental layer output). Support operation stability index: Based on the stress state of the hydraulic cylinder (equipment layer output) and the influence of environmental vibration (environmental layer output), the interaction layer calculates the overall operation stability of the support (for example, "the index is 0.85, which is lower than the normal value"). System risk level: The interaction layer combines the outputs of the equipment layer and the environment layer to evaluate the risk level of support failure (for example, "medium risk").

[0037] The beneficial effects of the above technical solution are: through hierarchical analysis of equipment, environment and interaction variables, a multi-level performance evaluation system for hydraulic supports is constructed by integrating sensor networks and multi-model calculations, which improves the comprehensiveness and real-time nature of performance analysis and provides a scientific basis for the reliable operation and optimization of hydraulic supports.

[0038] Example 5 The embodiment of the present invention provides a performance analysis method for a hydraulic support for a coal mine, which constructs a plurality of physical analysis models based on the output results of a hierarchical analysis logic model, and then obtains the performance data of the hydraulic support based on a preset analysis method and the physical analysis model, including: Extract key parameters related to hydraulic support performance from the output of the hierarchical logic model; Based on key parameters related to the performance of the hydraulic support and several preset physical modeling methods, a physical analysis model corresponding to each preset physical modeling method is constructed; Obtaining the analysis method corresponding to the physical analysis model based on the preset model-analysis method data table; Based on all physical analysis models and the analysis method corresponding to each physical analysis model, the performance of the hydraulic support is analyzed to obtain the performance data of the hydraulic support.

[0039] In this embodiment, the physical analysis model is a mathematical model built based on physical laws (such as mechanics, thermodynamics, and fluid mechanics) to simulate and analyze the performance of the equipment and reflect the physical behavior and performance indicators of the equipment under actual working conditions. For example, the hydraulic support force analysis model is used to calculate the stress distribution of the support under different loads. For example, a mechanical model describing the force relationship between the hydraulic cylinder, support, and top beam is established to analyze its compressive resistance and instability risk. The hydraulic oil flow model is used to simulate the flow characteristics of the hydraulic oil in the pipeline and calculate the flow and pressure loss caused by temperature changes. In this embodiment, the key parameters are core variables directly related to equipment performance extracted from the output results of the hierarchical logic model. These parameters provide input for the physical analysis model and determine the accuracy of the analysis results, such as hydraulic cylinder pressure: for example, the current hydraulic cylinder pressure is 25 MPa, which is used to analyze whether the hydraulic cylinder is in an overload state, support inclination angle: for example, the support inclination angle is 5°, which is used to determine whether the support has an instability tendency, and ambient temperature: for example, the ambient temperature is 40°C, which is used to evaluate the impact of reduced hydraulic oil viscosity on equipment performance.

[0040] In this embodiment, performance data is data describing the current operating status or performance indicators of the equipment calculated by a physical analysis model, and is used to evaluate the reliability and stability of the equipment. For example: Maximum stress value: The force analysis of the bracket shows that the maximum stress is 150 MPa, indicating that the bracket is close to the limit load. Displacement amplitude: The displacement amplitude of the bracket top beam is 2.5 cm, which exceeds the safety threshold, indicating that the bracket posture needs to be adjusted. Remaining life estimation: Combined with the fatigue analysis model, the remaining life of the bracket is estimated to be 3000 hours.

[0041] In this embodiment, the preset physical modeling method is a modeling technology selected in advance according to the characteristics of the coal mine hydraulic support, and is used to construct different physical analysis models, for example, the static analysis method: used to calculate the stress conditions of the support under static conditions, the dynamic analysis method: used to analyze the dynamic response of the support under external impact or vibration conditions, and the fluid dynamics method: used to simulate the flow characteristics of hydraulic oil under high temperature and high pressure.

[0042] In this embodiment, the preset model-analysis method data table is a preset rule table that corresponds physical analysis models to corresponding analysis methods, and is used to guide the selection and application of analysis models.

[0043] The beneficial effects of the above technical solution are: extracting key parameters through a hierarchical logical model and constructing a variety of physical analysis models, combining preset analysis methods to achieve accurate evaluation of the performance of the hydraulic support, integrating multi-model and multi-method analysis, improving the comprehensiveness and accuracy of performance data acquisition, and providing new ideas and technical support for the optimized design and intelligent maintenance of the hydraulic support.

[0044] Example 6 The embodiment of the present invention provides a performance analysis method for a hydraulic support for a coal mine, which constructs a fault propagation path between components of the hydraulic support based on performance data of the hydraulic support and a preset method, and determines the fault impact of each component of the hydraulic support, including: Acquire the properties of each component of the hydraulic support, and build a mechanical model for each component based on the properties of each component of the hydraulic support; Determine the coupling relationship between the hydraulic support components based on the properties of each component of the hydraulic support and a preset algorithm; Construct a coupling relationship model between components based on the coupling relationship between hydraulic support components; Determine and establish a time series diagram of fault propagation based on the output results of the mechanical models of all components, the coupling relationship model between components, and the performance data of the hydraulic support; Determine the fault propagation path based on the output results of the coupling relationship model between components, the time series diagram of fault propagation, and the preset analysis method; Obtain and analyze the historical failure data of the hydraulic support to determine several failure modes and failure data of the hydraulic support; Determine the failure coefficient of each component on each fault propagation path based on the performance data of the hydraulic support, a number of failure modes and failure data of the hydraulic support, and the failure propagation path; The fault impact of each component on each fault path is obtained based on the fault coefficient of each component on each fault propagation path and a preset path-coefficient-fault condition database.

[0045] In this embodiment, the fault propagation path is how the fault of a component gradually spreads to other components through coupling relationships, affecting the performance of the entire system. An example of the path is: hydraulic cylinder leaks → hydraulic oil pressure decreases → support pillar loses support force → support tilts as a whole → the risk of roof collapse increases. In this path, the fault of each link gradually spreads through the hydraulic oil flow and mechanical coupling relationship, ultimately affecting system safety.

[0046] In this embodiment, the time series diagram is a dynamic change diagram that records the expansion of the fault over time with time as the axis, reflecting the propagation speed and degree of the fault, and helping to analyze the response delay and impact range of each component. Fault expansion example: The time series diagram recorded by the pressure sensor of a certain bracket shows: T0: The hydraulic cylinder pressure is 25 MPa (normal). T1: The hydraulic cylinder leaks and the pressure drops to 15 MPa. T2: The pillar begins to tilt with a tilt angle of 3°. T3: The stability of the bracket decreases, which may cause further instability.

[0047] In this embodiment, the coupling relationship model is a mathematical or logical model that describes how components interact with each other through physical, hydraulic or mechanical connections. It clarifies the dependencies and impact paths between components and provides a basis for fault propagation analysis. For example, the linkage relationship between the hydraulic cylinder and the support: the hydraulic cylinder provides lifting power for the support, and the two are connected by the flow of hydraulic oil. If the hydraulic cylinder pressure is insufficient, the support lifting cannot be completed, which may cause the bracket to fail to effectively support the top plate. The relationship between the valve group and the hydraulic cylinder: the valve group controls the flow direction and pressure of the hydraulic oil. Failure of the valve group may cause the hydraulic cylinder to be unable to obtain sufficient pressure, thereby affecting the normal operation of the support.

[0048] The beneficial effects of the above technical solution are: by constructing a coupling relationship model and fault propagation path between hydraulic support components, combining historical data with mechanical models, time series analysis and impact assessment of fault propagation are realized, multi-dimensional data and models are integrated, and component failure coefficients and their impacts are accurately identified, which effectively improves the scientificity and systematicness of fault diagnosis and provides important technical support for the intelligent operation and maintenance of hydraulic supports.

[0049] Example 7 The embodiment of the present invention provides a performance analysis method for a hydraulic support for a coal mine, wherein the failure modes include: a mechanical failure mode, a hydraulic failure mode and an electronic failure mode.

[0050] In this embodiment, the mechanical failure mode refers to the failure of the mechanical components in the hydraulic support caused by material loss, overload, fatigue, deformation or physical damage. Mechanical failure modes usually directly affect the load-bearing capacity and stability of the support. For example: Pillar instability: due to bending or breaking caused by fatigue or overload of the pillar material, the support cannot normally support the top plate. Weld cracking: The welds at the connection of the support components cause crack propagation due to long-term stress concentration or corrosion, reducing the structural strength. Top beam deformation: The top beam of the support is permanently bent due to uneven force or excessive pressure on the top plate, affecting the normal expansion and contraction of the support; In this embodiment, the hydraulic failure mode refers to insufficient pressure, leakage or abnormal control of the hydraulic system due to problems with components such as the hydraulic oil, pipelines, valve groups or hydraulic cylinders in the hydraulic system. Hydraulic failures directly affect the lifting and pressure balancing capabilities of the bracket. For example: Hydraulic cylinder leakage: wear or damage to the hydraulic cylinder seal causes hydraulic oil leakage and makes it impossible to maintain the stability of the bracket. Hydraulic oil contamination: water or impurities are mixed into the hydraulic oil, reducing the efficiency of the hydraulic system and causing blockage of the hydraulic pump or valve group. Valve group failure: the hydraulic valve fails to function due to wear or blockage, and the bracket cannot be lifted or lowered normally or maintain pressure; In this embodiment, the electronic failure mode refers to the failure of electronic components such as sensors, control modules, lines or communication systems of the hydraulic support, resulting in malfunction of the support monitoring, control and communication functions. Electronic failures usually affect the automatic operation and safety warning capabilities of the support. For example: Sensor failure: The pressure sensor or tilt sensor fails and the operating status of the support cannot be monitored in real time. Control module failure: The PLC (programmable logic controller) has a logical error or hardware damage, and the support cannot perform the intended action. Communication interruption: The wireless communication signal between the support and the central control system is interrupted, and remote control or data transmission cannot be achieved.

[0051] The beneficial effects of the above technical solution are: through systematic analysis of the three major failure modes of mechanical, hydraulic and electronic hydraulic supports for coal mines, the integrated analysis of multidisciplinary failure modes is realized, the support fault diagnosis and prevention system is optimized, the reliability and safety of equipment operation are improved, and at the same time, more efficient technical support is provided for coal mine production.

[0052] Example 8 The embodiment of the present invention provides a performance analysis method for a hydraulic support for a coal mine, which determines the fault coefficient of each component on each fault propagation path, including: Based on the performance data of the hydraulic support, several failure modes and failure data of the hydraulic support, and the failure propagation path, the failure-related data of each component on each failure path is determined; Determine the nonlinear coupling coefficient between the components based on the output result of the coupling relationship model between the components; The fault coefficient of each component on each fault propagation path is determined based on the fault-related data of each component on each fault path and the nonlinear coupling coefficient between the components: ;in, is the failure coefficient of the i-th component on the g-th fault path, is the failure probability of the i-th component on the g-th fault path under the m-th fault mode, is the fault severity of the i-th component on the g-th fault path under the m-th fault mode, is the weight factor of the i-th component on the g-th fault path under the m-th fault mode, is the nonlinear coupling coefficient between the i-th component and the j-th component on the g-th fault path, is the preset maximum coupling coefficient, is the preset reference fault coefficient, n is the number of components on the g-th fault path, is the state coefficient of the i-th component on the g-th fault path, is the preset time influence coefficient, is the number of failure modes.

[0053] In this embodiment, the fault severity is used to measure the impact of a fault on system operation under a certain fault mode, and the range is usually [0,1]. The larger the value, the more serious the impact of the fault. For example: 0.2: slight impact, no immediate maintenance required; 0.8: severe impact, rapid repair required; In this embodiment, the nonlinear coupling coefficient is used to describe the fault correlation between two components, reflecting the nonlinear influence of the failure of one component on another component. When it is equal to 0, it means that there is no correlation between the two components; when it is greater than 0, it means that there is a positive influence (the failure of one component increases the failure probability of another component); In this embodiment, the preset maximum coupling coefficient is used to normalize the nonlinear coupling effect to ensure that the calculation results are controllable. It is usually determined through experiments or historical data; In this embodiment, the failure mode weight is used to describe the relative importance of a certain failure mode, and the weights of the impact of different modes on the failure coefficient can be adjusted according to the actual scenario. For example, for a hydraulic support, the weight of "hydraulic leakage" may be higher than that of "slight wear".

[0054] The beneficial effects of the above technical scheme are: by comprehensively considering the performance data of the hydraulic support, failure mode, fault propagation path and the nonlinear coupling relationship between components, a fault coefficient calculation method based on multi-dimensional factors is proposed, and parameters such as fault severity, weight factor and time influence are introduced to accurately quantify the status of each component on the fault propagation path, effectively reveal the complex fault coupling mechanism, and significantly improve the accuracy of the performance analysis of the hydraulic support and the fault diagnosis capability, providing an important reference for the safety and reliability of the coal mine support.

[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 performance analysis method for a hydraulic support for a coal mine, characterized in that: include: Step 1: Install a preset sensor network at key locations of the hydraulic support to collect real-time data of a preset type, and at the same time, collect environmental parameters of a preset type based on the preset sensors; Step 2: Build a hierarchical analysis logic model based on all collected data and obtain the model output results; Step 3: construct several physical analysis models based on the output results of the hierarchical analysis logic model, and then obtain the performance data of the hydraulic support based on the preset analysis method and the physical analysis model; Step 4: construct the fault propagation path between the components of the hydraulic support based on the performance data of the hydraulic support and the preset method, and determine the fault impact of each component of the hydraulic support; Step 5: Generate a performance analysis report of the hydraulic support based on the performance data of the hydraulic support and the impact of failures of each component.

2. The performance analysis method of a hydraulic support for coal mines according to claim 1, characterized in that: Build a hierarchical analysis logic model based on the fused data and obtain the model output results, including: Build a hierarchical logic model based on all collected data; The corresponding fuzzy logic rules of each main level are defined based on the preset definition method, and the relationship between the levels is analyzed through logical reasoning to output the results of the model.

3. The performance analysis method of a hydraulic support for coal mines according to claim 2, characterized in that: Build a hierarchical logic model based on all collected data, including: Conduct a first structural analysis on the hydraulic support, and determine the main layers of the hierarchical logic model based on the analysis results, including: equipment layer, environment layer, and interaction layer; Get the input variables and output variables of the device layer, environment layer and interaction layer respectively; Determine the modeling method for each main level based on the preset level-modeling method data table; Constructing analytical models for each major level based on the modeling approach, input variables, and output variables of each major level; Conduct interaction analysis on the device layer, environment layer and interaction layer to determine the interaction relationship between them; Determine the mapping rules between the device layer, the environment layer and the interaction layer based on the preset interaction relationship-mapping rule data table; The hierarchical logic model is determined based on the interaction relationship and mapping rules among the device layer, the environment layer and the interaction layer in combination with the analysis models of the device layer, the environment layer and the interaction layer.

4. The performance analysis method of a hydraulic support for coal mines according to claim 3, characterized in that: Get the input variables and output variables of the device layer, environment layer, and interaction layer respectively, including: Performing a second structural analysis on the hydraulic support to obtain component characteristics of the hydraulic support; Determine the input variables of the equipment layer based on the real-time data collected by the preset sensor network and the component characteristics of the hydraulic support; Determine the device layer output variable based on a preset formula and the device layer input variable; Determine input variables of the environmental layer based on environmental parameters of a preset type collected by a preset sensor; Determine the output variables of the environment layer based on the preset environment model and the input variables of the environment layer; Determine the input variables of the interaction layer based on the output variables of the device layer and the output variables of the environment layer; The output variables of the interaction layer are determined based on several preset models.

5. The performance analysis method of a hydraulic support for coal mines according to claim 1, characterized in that: Based on the output results of the hierarchical analysis logic model, several physical analysis models are constructed, and then the performance data of the hydraulic support is obtained based on the preset analysis method and the physical analysis model, including: Extract key parameters related to hydraulic support performance from the output of the hierarchical logic model; Based on key parameters related to the performance of the hydraulic support and several preset physical modeling methods, a physical analysis model corresponding to each preset physical modeling method is constructed; Obtaining the analysis method corresponding to the physical analysis model based on the preset model-analysis method data table; Based on all physical analysis models and the analysis method corresponding to each physical analysis model, the performance of the hydraulic support is analyzed to obtain the performance data of the hydraulic support.

6. The performance analysis method of a hydraulic support for coal mines according to claim 4, characterized in that: Based on the performance data of the hydraulic support and the preset method, the fault propagation path between the components of the hydraulic support is constructed, and the fault impact of each component of the hydraulic support is determined, including: Acquire the properties of each component of the hydraulic support, and build a mechanical model for each component based on the properties of each component of the hydraulic support; Determine the coupling relationship between the hydraulic support components based on the properties of each component of the hydraulic support and a preset algorithm; Construct a coupling relationship model between components based on the coupling relationship between hydraulic support components; Determine and establish a time series diagram of fault propagation based on the output results of the mechanical models of all components, the coupling relationship model between components, and the performance data of the hydraulic support; Determine the fault propagation path based on the output results of the coupling relationship model between components, the time series diagram of fault propagation, and the preset analysis method; Obtain and analyze the historical failure data of the hydraulic support to determine several failure modes and failure data of the hydraulic support; Determine the failure coefficient of each component on each fault propagation path based on the performance data of the hydraulic support, a number of failure modes and failure data of the hydraulic support, and the failure propagation path; The fault impact of each component on each fault path is obtained based on the fault coefficient of each component on each fault propagation path and a preset path-coefficient-fault condition database.

7. The performance analysis method of a hydraulic support for coal mines according to claim 5, characterized in that: Failure modes, including: mechanical failure mode, hydraulic failure mode and electronic failure mode.

8. The performance analysis method of a hydraulic support for coal mines according to claim 5, characterized in that: Determine the failure coefficient of each component on each fault propagation path, including: Based on the performance data of the hydraulic support, several failure modes and failure data of the hydraulic support, and the failure propagation path, the failure-related data of each component on each failure path is determined; Determine the nonlinear coupling coefficient between the components based on the output result of the coupling relationship model between the components; The fault coefficient of each component on each fault propagation path is determined based on the fault-related data of each component on each fault path and the nonlinear coupling coefficient between the components: ;in, is the failure coefficient of the i-th component on the g-th fault path, is the failure probability of the i-th component on the g-th fault path under the m-th fault mode, is the fault severity of the i-th component on the g-th fault path under the m-th fault mode, is the weight factor of the i-th component on the g-th fault path under the m-th fault mode, is the nonlinear coupling coefficient between the i-th component and the j-th component on the g-th fault path, is the preset maximum coupling coefficient, is the preset reference fault coefficient, n is the number of components on the g-th fault path, is the state coefficient of the i-th component on the g-th fault path, is the preset time influence coefficient, is the number of failure modes.

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