Multi-cylinder hydraulic equipment data interaction system based on digital twin drive

Abstract

The invention discloses a multi-cylinder hydraulic equipment data interaction system based on digital twin drive, and relates to the technical field of industrial automation control. The problems that in the prior art, data acquisition and processing lack flexibility and pertinence, model construction and optimization are not perfect enough, and simulation optimization and real-time feedback are lacked are solved. Accurate perception and fault early warning of the equipment state are realized by optimizing the sensor layout and adjusting the acquisition frequency, the physical structure and the working principle of the equipment are accurately described by adopting a digital twin model, and the current and future running states of the equipment are scientifically evaluated and effectively predicted in combination with an evaluation index system of a state analysis unit. A basis is provided for advanced maintenance, the equipment fault risk is reduced, a digital twin model is used for simulating the implementation effect of a control strategy, a control instruction is optimized according to simulation evaluation, the execution effect is monitored in real time for dynamic adjustment, accurate control over equipment is ensured, the stability and reliability of equipment operation are improved, and the production efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of industrial automation control technology, and in particular to a multi-cylinder hydraulic equipment data interaction system based on digital twin drive. Background Art

[0002] Traditional multi-cylinder hydraulic equipment monitoring and control systems rely primarily on manual experience and simple sensor detection, failing to fully and in real time understand the equipment's operating status. Patent application number CN118455440A discloses a digital twin-driven interactive system for multi-cylinder hydraulic presses. This system includes: a multi-cylinder hydraulic press parametric modeling module that simplifies the multi-cylinder hydraulic press structure and completes the twin model; a real-time data acquisition module that acquires information to be collected, such as pressure and displacement; a data preprocessing module that primarily includes data cleaning, integration, transformation, and reduction; a multi-cylinder hydraulic press twin drive module that enables deep real-time data interaction between the hydraulic press's virtual twin and the physical entity, completing the construction of an end-edge-cloud interactive model; and a parameter adaptation module that implements the twin model's parameter adaptive correction process to predict the behavior of the physical model. This patent application addresses the inability to perform stress analysis, metal fatigue analysis, and real-time monitoring on physical multi-cylinder hydraulic presses. It also addresses the high cost and risk associated with verifying control algorithm experiments.

[0003] Although the above patent application uses digital twin technology to optimize some functions, the following problems still exist:

[0004] In the existing technology, there is a lack of dynamic adjustment mechanism for data collection frequency, data collection and processing lack flexibility and pertinence, and the digital twin model cannot be updated efficiently, making it difficult to quickly and accurately reflect the actual state changes of the equipment, reducing the accuracy and reliability of the model. It is even more impossible to discover possible problems with the control strategy in advance, making it difficult to achieve precise control of the equipment and continuous and stable operation. Summary of the Invention

[0005] The purpose of the present invention is to provide a multi-cylinder hydraulic equipment data interaction system based on digital twin drive, which can realize comprehensive monitoring, intelligent analysis and precise control of multi-cylinder hydraulic equipment, improve the operating efficiency and reliability of the equipment, reduce production costs, and solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The multi-cylinder hydraulic equipment data interaction system based on digital twin drive includes:

[0008] The data acquisition module is configured to deploy sensors at key locations of the multi-cylinder hydraulic equipment to collect operating data of the multi-cylinder hydraulic equipment in real time, and to adjust the frequency of data collection based on the equipment's operating status and changing trends;

[0009] A twin model construction module is configured to construct a digital twin model of the multi-cylinder hydraulic equipment, analyze the physical structure and working principle of the multi-cylinder hydraulic equipment based on the collected multi-cylinder hydraulic equipment operation data, and obtain the equipment status information of the multi-cylinder hydraulic equipment;

[0010] The interactive control module is configured to determine whether there is an abnormality in the multi-cylinder hydraulic equipment based on the analysis results of the digital twin model. If there is an abnormality, a control instruction is generated according to a preset control strategy and the control instruction is sent to the actuator of the multi-cylinder hydraulic equipment.

[0011] Furthermore, the data acquisition module also includes:

[0012] A sensor optimization unit is configured to analyze the importance and relevance of data from various parts of the multi-cylinder hydraulic equipment based on the structural characteristics and operating characteristics of the multi-cylinder hydraulic equipment, determine key installation locations of the sensors, and optimize the layout of the sensors;

[0013] A data collection frequency adjustment unit is configured to monitor the equipment operating status of the multi-cylinder hydraulic equipment in real time and adjust the preset data collection frequency according to the changing trend of the equipment operating status;

[0014] The equipment monitoring unit is configured to collect operating environment data of the multi-cylinder hydraulic equipment and provide equipment failure warning based on the correlation between the operating environment data and the operating data.

[0015] Furthermore, the acquisition frequency adjustment unit specifically includes:

[0016] Acquire the collected operating data, extract key features based on the data type of the operating data, and integrate the operating data according to the extracted key features to obtain a pressure operating data group, a displacement operating data group, an oil temperature operating data group, and an oil flow operating data group of the multi-cylinder hydraulic equipment;

[0017] Based on the target values of the pressure operation data group, displacement operation data group, oil temperature operation data group, and oil flow operation data group, the target values are compared with the preset threshold range of each data group, and the equipment operation status and change trend of the multi-cylinder hydraulic equipment are judged in combination with the data fluctuation range of each data group;

[0018] According to the judgment results of the equipment operation status and change trend, the corresponding data collection frequency adjustment strategy is generated to adjust the operation data collection frequency of the multi-cylinder hydraulic equipment.

[0019] Furthermore, the frequency of data collection for multi-cylinder hydraulic equipment operation is adjusted, specifically including:

[0020] extracting target values of the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group;

[0021] Extracting preset threshold ranges corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group;

[0022] Comparing the target values of the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group with their corresponding preset threshold ranges, and obtaining standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group, wherein the standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group are parameter values used to represent the data fluctuation range of each data group;

[0023] Comparing the standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group with a preset standard deviation threshold;

[0024] When there is no data group whose standard deviation value exceeds the preset standard deviation threshold, the frequency of collecting operating data of the multi-cylinder hydraulic equipment is not adjusted;

[0025] When there is a data group whose standard deviation value exceeds the preset standard deviation threshold, the data group whose standard deviation value exceeds the preset standard deviation threshold is selected as the target data group;

[0026] The standard deviation values corresponding to the target data group are used for weighted averaging to obtain the comprehensive standard deviation value corresponding to the target data group;

[0027] The frequency of collecting operating data of the multi-cylinder hydraulic equipment is adjusted using the comprehensive standard deviation value corresponding to the target data group.

[0028] Furthermore, the frequency of collecting operating data of the multi-cylinder hydraulic equipment is adjusted using the comprehensive standard deviation value corresponding to the target data group, specifically including:

[0029] Retrieve the comprehensive standard deviation value corresponding to the target data group;

[0030] Retrieve the maximum allowable standard deviation value corresponding to each data group included in the target data group;

[0031] Obtaining an average value of the maximum allowable standard deviation corresponding to the target data group using the maximum allowable standard deviation value corresponding to each data group included in the target data group;

[0032] Performing a ratio processing on the comprehensive standard deviation value corresponding to the target data group and the average value of the maximum allowable standard deviation corresponding to the target data group to obtain a standard deviation ratio coefficient corresponding to the target data group;

[0033] The standard deviation ratio coefficient corresponding to the target data group is used to adjust the frequency of multi-cylinder hydraulic equipment operation data collection.

[0034] Furthermore, the twin model construction module specifically includes:

[0035] a model building unit configured to build a basic digital twin model of the multi-cylinder hydraulic equipment based on the design drawings and physical characteristics of the multi-cylinder hydraulic equipment, so as to describe the working principle of the multi-cylinder hydraulic equipment;

[0036] a data fusion unit configured to update state variables and initial parameters of the basic digital twin model of the multi-cylinder hydraulic equipment based on the acquired and collected operating data and the basic digital twin model;

[0037] The state analysis unit is configured to establish an equipment state evaluation index system, extract key features of the equipment operation state based on the output results of the updated digital twin model of the multi-cylinder hydraulic equipment, and judge the equipment operation state of the multi-cylinder hydraulic equipment based on the key features and evaluation indicators.

[0038] Furthermore, the status analysis unit establishes an equipment status evaluation indicator system, specifically including:

[0039] Obtain historical operating data of multi-cylinder hydraulic equipment under different working conditions and health states, perform feature extraction on the historical operating data, and obtain the initial feature set of the equipment operating status based on the extraction results;

[0040] Extract key features related to the evaluation indicators from the initial feature set and integrate them into a key feature subset, determine the equipment status evaluation indicator category, and establish labels;

[0041] Based on the digital twin model of multi-cylinder hydraulic equipment, the attribute information of each key component of the multi-cylinder hydraulic equipment, the structural information of the equipment, and the preset working mode information are obtained to determine the weight value of each key component in the overall operation of the equipment;

[0042] According to the weight value of each key component, corresponding quantitative standards and grading thresholds are set for each evaluation indicator, and a corresponding relationship between the indicator level and the equipment operating status is established.

[0043] Furthermore, the state analysis unit further includes:

[0044] Obtain the current output results from the digital twin model, including the real-time operating data of each cylinder's pressure, displacement, oil temperature, and oil flow, as well as the equipment operating status judgment results of the multi-cylinder hydraulic equipment;

[0045] Combine the historical operating data of multi-cylinder hydraulic equipment, arrange them in time series, and construct a time series dataset;

[0046] Extract dynamic features of time series data sets based on sliding window technology, detect data distribution of time series data sets, and determine key features in time series data sets based on the equipment status evaluation index system;

[0047] The operating data of multi-cylinder hydraulic equipment is predicted based on the time series prediction model. According to the prediction results and combined with the equipment status evaluation index system, the equipment operating status of the multi-cylinder hydraulic equipment at the future moment is judged.

[0048] Furthermore, the twin model building module also includes:

[0049] a model parameter updating unit configured to compare the real-time acquired operating data with the output data of the digital twin model during the operation of the multi-cylinder hydraulic equipment, dynamically update the model parameters using the latest acquired operating data based on the comparison results, and adjust the weights and values of the parameters in the digital twin model;

[0050] The model evaluation unit is configured to perform reliability evaluation on the digital twin model based on the comparison results of the actually collected operation data and the data output by the digital twin model, and determine whether optimization and training are needed.

[0051] Furthermore, the interactive control module further includes:

[0052] The generated control instructions are input into the digital twin model, which simulates the operating status of the equipment after the control strategy is implemented. During the simulation, the digital twin model adjusts its own state variables and parameters according to the control instructions.

[0053] Based on the simulation results, evaluate whether the key performance indicators of the multi-cylinder hydraulic equipment have returned to normal ranges, and check whether new potential problems have emerged during the simulation process;

[0054] Determine whether the current control strategy and control instructions need to be optimized based on the simulation evaluation results, and send the optimized control instructions to the actuator of the multi-cylinder hydraulic equipment based on the judgment results;

[0055] Monitor the execution status of the actuator and the actual operating status of the multi-cylinder hydraulic equipment in real time, compare the changes in the equipment status before and after executing the control instructions, and judge the actual execution effect of the control strategy.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] By optimizing the sensor layout and adjusting the acquisition frequency, comprehensive equipment operation and environmental data are collected to achieve accurate perception of equipment status and fault warning. The digital twin model is used to accurately describe the physical structure and working principle of the equipment. Combined with the evaluation index system of the status analysis unit, the current and future operating status of the equipment is scientifically evaluated and effectively predicted, providing a basis for advance maintenance and reducing the risk of equipment failure. The interactive control module uses the digital twin model to simulate the implementation effect of the control strategy, optimize the control instructions based on the simulation evaluation, and monitor the execution effect in real time for dynamic adjustment to ensure precise equipment control, improve the stability and reliability of equipment operation, and ultimately improve production efficiency, reduce maintenance costs, and enhance the adaptability of equipment under complex working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a module diagram of the multi-cylinder hydraulic equipment data interaction system based on digital twin drive of the present invention. DETAILED DESCRIPTION

[0059] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only 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 making creative efforts are within the scope of protection of the present invention.

[0060] In order to solve the technical problems in existing technologies, such as the lack of flexibility and pertinence in data collection and processing, the imperfect model construction and optimization, the lack of simulation optimization and real-time feedback, and the inability to detect possible problems in the control strategy in advance, it is difficult to achieve precise control and continuous stable operation of the equipment. Figure 1 , this embodiment provides the following technical solutions:

[0061] The multi-cylinder hydraulic equipment data interaction system based on digital twin drive includes:

[0062] The data acquisition module is configured to deploy sensors at key locations of the multi-cylinder hydraulic equipment to collect real-time operating data of the multi-cylinder hydraulic equipment, including the pressure, displacement, oil temperature, and oil flow of each cylinder. The module also performs pre-processing on the collected operating data, such as denoising and filtering, to improve data quality. Furthermore, the module adjusts the frequency of operating data collection based on the equipment's operating status and changing trends. The module also includes:

[0063] The sensor optimization unit is configured to analyze the importance and relevance of data from various parts of the multi-cylinder hydraulic equipment based on its structural and operating characteristics, such as cylinder layout and connection method, hydraulic pipeline routing and branching, key component location and function, working cycle and action sequence, and load variation patterns. This unit then determines the key sensor installation locations and optimizes the sensor layout to ensure comprehensive and accurate collection of key data.

[0064] The data acquisition frequency adjustment unit is configured to monitor the operating status of the multi-cylinder hydraulic equipment in real time and adjust the preset data acquisition frequency according to the changing trend of the equipment operating status. When the equipment operating status is stable, the acquisition frequency is appropriately reduced to reduce the data processing volume; when the equipment operating status fluctuates abnormally or is in a critical working stage, the acquisition frequency is increased to obtain detailed data in a timely manner;

[0065] An equipment monitoring unit is configured to collect operating environment data of the multi-cylinder hydraulic equipment, including temperature and humidity, dust concentration, and electromagnetic interference intensity of the space where the equipment is located. The unit then issues an early warning of equipment failure based on the correlation between the operating environment data and the operating data. For example, if high humidity is detected and the water content in the equipment oil is increasing, the unit issues an early warning to indicate a potential risk of equipment corrosion.

[0066] A twin model construction module is configured to construct a digital twin model of the multi-cylinder hydraulic equipment, including the geometry and connection relationships of each cylinder. It analyzes the physical structure and working principle of the multi-cylinder hydraulic equipment based on the collected operating data of the multi-cylinder hydraulic equipment and obtains the equipment status information of the multi-cylinder hydraulic equipment.

[0067] The interactive control module is configured to determine whether there are any abnormalities in the multi-cylinder hydraulic equipment based on the analysis results of the digital twin model. If there are any abnormalities, it generates control instructions according to the preset control strategy and sends the control instructions to the actuators of the multi-cylinder hydraulic equipment to achieve precise control of the equipment, such as adjusting the working pressure, displacement and other parameters of each cylinder to ensure stable operation of the equipment.

[0068] In this embodiment, by deploying sensors at key locations of multi-cylinder hydraulic equipment, equipment operation data and environmental data can be collected comprehensively and accurately. The digital twin model constructed based on the data reflects the equipment status in real time, enabling timely judgment and precise control of equipment abnormalities, ensuring stable equipment operation, and improving the reliability and safety of equipment operation. By establishing an equipment status evaluation index system and combining historical and real-time data, the current operating status of the equipment can be scientifically evaluated, and the future operating status of the equipment can be effectively predicted, potential problems can be discovered in advance, and maintenance plans can be formulated in advance, reducing equipment downtime, reducing maintenance costs, and improving the overall operating efficiency of the equipment. During the control process, the control strategy is simulated and evaluated through the digital twin model, and dynamic adjustments are made based on the actual execution effect to form an efficient feedback mechanism, continuously improving the accuracy and effectiveness of equipment control, adapting to complex and changing working scenarios, and enhancing the adaptability and stability of the equipment.

[0069] In this embodiment, the acquisition frequency adjustment unit specifically includes:

[0070] Acquire the collected operating data, extract key features based on the data type of the operating data, and integrate the operating data according to the extracted key features to obtain a pressure operating data group, a displacement operating data group, an oil temperature operating data group, and an oil flow operating data group of the multi-cylinder hydraulic equipment;

[0071] In this embodiment, for pressure operation data, key features such as pressure mean, peak value, and fluctuation range are extracted; for displacement operation data, features such as displacement change rate and maximum displacement value are extracted; for oil temperature operation data, features such as oil temperature change trend and maximum oil temperature are extracted; for oil flow operation data, features such as flow stability and average flow are extracted;

[0072] Based on the target values of the pressure operation data group, displacement operation data group, oil temperature operation data group, and oil flow operation data group, the target values are compared with the preset threshold range of each data group, and the equipment operation status and change trend of the multi-cylinder hydraulic equipment are judged in combination with the data fluctuation range of each data group;

[0073] Based on the judgment results of the equipment operation status and change trend, the corresponding data collection frequency adjustment strategy is generated to adjust the operation data collection frequency of multi-cylinder hydraulic equipment;

[0074] In this embodiment, when the target value of a data group exceeds a preset threshold range, or the data fluctuation range exceeds a certain standard, it is determined that the multi-cylinder hydraulic equipment may be in an abnormal state. The changing trend of each data group over a period of time is analyzed, such as a continuous increase in pressure or a sharp increase in oil temperature, to determine the development direction of the operating state of the multi-cylinder hydraulic equipment, whether it is tending to be stable, the abnormality is aggravated, or it is about to enter a critical working stage; when the equipment operating state is stable and the target values of each data group are within the preset threshold range, the data fluctuation is small, and the data collection frequency of each data group is appropriately reduced to reduce the amount of data processing. When the equipment operating state fluctuates abnormally, one or more data groups exceed the threshold range and the fluctuation is large, or the equipment is in a critical working stage, the collection frequency is increased to 2-3 times the original frequency to obtain detailed data in a timely manner and accurately grasp the equipment status.

[0075] Alternatively, use the following adjustment strategy to adjust the frequency of data collection that has already been run;

[0076] Specifically, adjust the frequency of data collection for multi-cylinder hydraulic equipment operation, including:

[0077] extracting target values of the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group;

[0078] Extracting preset threshold ranges corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group;

[0079] Comparing the target values of the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group with their corresponding preset threshold ranges, and obtaining standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group, wherein the standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group are parameter values used to represent the data fluctuation range of each data group;

[0080] Comparing the standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group with a preset standard deviation threshold;

[0081] When there is no data group whose standard deviation value exceeds the preset standard deviation threshold, the frequency of collecting operating data of the multi-cylinder hydraulic equipment is not adjusted;

[0082] When there is a data group whose standard deviation value exceeds the preset standard deviation threshold, the data group whose standard deviation value exceeds the preset standard deviation threshold is selected as the target data group;

[0083] The standard deviation values corresponding to the target data group are used for weighted averaging to obtain the comprehensive standard deviation value corresponding to the target data group;

[0084] The frequency of collecting operating data of the multi-cylinder hydraulic equipment is adjusted using the comprehensive standard deviation value corresponding to the target data group.

[0085] The technical effect of the above-mentioned technical solution is that by extracting target values and preset threshold ranges for operating data sets such as pressure, displacement, oil temperature, and oil flow, and comparing them, the fluctuations of each data set can be accurately analyzed and the corresponding standard deviation values calculated, thereby accurately representing the data fluctuation range. This helps accurately understand the changes in key parameters of multi-cylinder hydraulic equipment under different operating conditions, providing accurate data support for subsequent frequency adjustments. By comparing the standard deviation values of each data set with the preset standard deviation threshold, it is possible to determine whether the data fluctuations are abnormal. If a data set exceeds the threshold, the target data set is selected and its comprehensive standard deviation value is calculated, which is then used to adjust the operating data collection frequency. This adaptive adjustment method dynamically optimizes the data collection frequency based on the actual operating conditions of the equipment. When the data fluctuations are large, the collection frequency is increased to more accurately capture changes in the equipment's operating status. When the data fluctuations are small, the collection frequency is reduced to avoid unnecessary data collection and processing, thereby improving data collection efficiency and equipment performance. By monitoring and adjusting the data collection frequency in real time, potential problems in equipment operation can be promptly identified. Adjusting the collection frequency based on data fluctuations ensures that the collected data accurately reflects the equipment's operating status while preventing data redundancy or information loss due to excessively high or low collection frequencies. This helps improve data quality and effectiveness, providing a more reliable data foundation for equipment performance analysis, fault diagnosis, and optimized control, further enhancing overall equipment performance and operational efficiency.

[0086] Specifically, adjusting the frequency of collecting operating data of the multi-cylinder hydraulic equipment using the comprehensive standard deviation value corresponding to the target data group specifically includes:

[0087] Retrieve the comprehensive standard deviation value corresponding to the target data group;

[0088] Retrieve the maximum allowable standard deviation value corresponding to each data group included in the target data group;

[0089] Obtaining an average value of the maximum allowable standard deviation corresponding to the target data group using the maximum allowable standard deviation value corresponding to each data group included in the target data group;

[0090] Performing a ratio processing on the comprehensive standard deviation value corresponding to the target data group and the average value of the maximum allowable standard deviation corresponding to the target data group to obtain a standard deviation ratio coefficient corresponding to the target data group;

[0091] The standard deviation ratio coefficient corresponding to the target data group is used to adjust the frequency of collecting operating data of the multi-cylinder hydraulic equipment, wherein the adjusted frequency of collecting operating data is obtained by the following formula:

[0092] F=F base *[1+α*tanh(β*(xr))]

[0093] Where F represents the adjusted frequency of operation data collection; F base represents the operating data collection frequency before adjustment; α represents the adjustment amplitude coefficient, which controls the maximum amplitude of frequency change and has a value range of 0.5-1.6; β represents the curve steepness factor, which controls the response speed of frequency changes and has a value range of 2.2-3.1; x represents the standard deviation ratio coefficient corresponding to the target data set; and r represents the reference coefficient value corresponding to the operating data of multi-cylinder hydraulic equipment and has a value range of 0.3-0.8. The above formula uses the hyperbolic tangent function tanh, making the adjustment of the collection frequency nonlinear. Compared with linear adjustment, this allows for more flexible and precise adjustment of the collection frequency based on the standard deviation ratio coefficient x. When x is small, the frequency adjustment amplitude is small. When x increases to a certain level, the frequency adjustment amplitude increases, enabling faster response to increased fluctuations in equipment operating data, achieving adaptive adjustment, and optimizing data collection performance. The adjustment amplitude coefficient α, the curve steepness factor β, and r are limited to a certain range to ensure that the adjustment range and change trend of the collection frequency are within a controllable range. Avoid unreasonable collection frequency caused by excessive adjustment or too fast or too slow change speed, ensure that the collection frequency is always in the appropriate range, maintain stable and reliable operation of the equipment data collection system, and improve data collection quality and equipment operation performance indicators.

[0094] The technical effect of the above technical solution is that by calculating the ratio of the comprehensive standard deviation value corresponding to the target data set to the average value of the maximum allowable standard deviation (the standard deviation ratio coefficient), the operating data collection frequency can be dynamically and accurately adjusted according to the degree of fluctuation and deviation of the actual equipment operating data. When the data fluctuation is large, the collection frequency can be promptly increased to closely monitor the equipment status. When the fluctuation is small, the collection frequency can be appropriately reduced to avoid resource waste and improve data collection efficiency. The adjustment amplitude coefficient α controls the maximum amplitude of the frequency change, and the curve steepness factor β controls the response speed of the frequency change. Different values can adapt to different operating conditions and equipment characteristics. In complex and changing operating scenarios, the collection frequency adjustment is more flexible and adaptable, ensuring stable equipment operation while optimizing data collection results. Adjusting the collection frequency based on data fluctuations can proactively detect abnormal trends in equipment operation and promptly adjust monitoring intensity. This helps maintenance personnel identify potential faults in advance and take measures to prevent them. This ensures the safe and stable operation of multi-cylinder hydraulic equipment, reduces downtime and maintenance costs, and improves the overall performance and service life of the equipment.

[0095] In this embodiment, the twin model construction module specifically includes:

[0096] The model building unit is configured to construct a basic digital twin model of the multi-cylinder hydraulic equipment based on the design drawings (size specifications, material properties, connection methods, etc. of each cylinder) and physical properties of the multi-cylinder hydraulic equipment. The model is used to describe the precise geometry of each cylinder of the multi-cylinder hydraulic equipment, the connection relationship between components, and the working principle of the hydraulic system.

[0097] A data fusion unit is configured to fuse the acquired operational data with the basic digital twin model to update the state variables and initial parameters of the basic digital twin model of the multi-cylinder hydraulic equipment, including determining the geometric parameters, material property parameters, flow coefficient, and pressure loss coefficient of each cylinder, so that the model can track operational changes of the equipment in real time;

[0098] The state analysis unit is configured to establish an equipment state evaluation index system, extract key features of the equipment operation state based on the output results of the updated digital twin model of the multi-cylinder hydraulic equipment, and judge the equipment operation state of the multi-cylinder hydraulic equipment based on the key features and evaluation indicators, and also includes:

[0099] Obtain the current output results from the digital twin model, including the real-time operating data of each cylinder's pressure, displacement, oil temperature, and oil flow, as well as the equipment operating status judgment results of the multi-cylinder hydraulic equipment;

[0100] Combine the historical operating data of multi-cylinder hydraulic equipment, arrange them in time series, and construct a time series dataset;

[0101] Using sliding window technology, the dynamic features of time series data sets are extracted. The average rate of change of each cylinder's pressure, displacement acceleration, and oil temperature fluctuation amplitude over a period of time are calculated to reflect the changing trend of the equipment's operating status. The data distribution of the time series data sets, such as mean, variance, and standard deviation, is detected. The key features of the time series data sets are determined based on the equipment status evaluation indicator system.

[0102] The operating data of multi-cylinder hydraulic equipment is predicted based on the time series prediction model. Based on the prediction results, the predicted values of parameters such as pressure, displacement, oil temperature, and oil flow of each cylinder at the future time are determined. In combination with the equipment status evaluation index system, the operating status of the multi-cylinder hydraulic equipment at the future time is judged.

[0103] In this embodiment, the status analysis unit establishes an equipment status evaluation indicator system, which specifically includes:

[0104] Obtain historical operating data of multi-cylinder hydraulic equipment under different working conditions and health states, including pressure, displacement, oil temperature, oil flow, and operating environment data of each cylinder, perform feature extraction on the historical operating data, and obtain the initial feature set of the equipment operating status based on the extraction results;

[0105] Extract key features related to the evaluation indicators from the initial feature set and integrate them into a key feature subset. Determine the categories of equipment status evaluation indicators and create labels, including pressure stability indicators, displacement accuracy indicators, oil temperature change rate indicators, oil cleanliness indicators, etc.

[0106] Based on the digital twin model of multi-cylinder hydraulic equipment, the attribute information of each key component of the multi-cylinder hydraulic equipment, the structural information of the equipment, and the preset working mode information are obtained to determine the weight value of each key component in the overall operation of the equipment;

[0107] Set corresponding quantitative standards and grading thresholds for each evaluation indicator based on the weight value of each key component, and establish a corresponding relationship between the indicator level and the equipment operating status. For example, the stable state corresponds to the normal level of the indicator, and the abnormal state corresponds to the mild, moderate or severe abnormal level of the indicator;

[0108] In this embodiment, the pressure stability index is divided into four levels according to the pressure fluctuation range: stable, mild fluctuation, moderate fluctuation and severe fluctuation, and corresponding pressure fluctuation percentage thresholds are set for each level.

[0109] In this embodiment, by extracting and integrating the key features of the operating data and intelligently adjusting the collection frequency according to the equipment operating status, the data processing efficiency is improved and resource waste is avoided. The status analysis unit establishes a comprehensive equipment status evaluation indicator system. Combining historical and real-time operating data, it can not only accurately judge the current operating status of the multi-cylinder hydraulic equipment, but also effectively predict the future status through the time series prediction model. It monitors the equipment from multiple dimensions and discovers potential problems in advance, providing strong support for preventive maintenance and fault warning of the equipment, and ensuring stable operation of the equipment.

[0110] In this embodiment, the twin model construction module also includes:

[0111] The model parameter update unit is configured to compare the real-time operating data acquired during the operation of the multi-cylinder hydraulic equipment with the output data of the digital twin model. Based on the comparison results, the model parameters are dynamically updated using the latest acquired operating data, adjusting the weights and values of each parameter in the digital twin model so that the digital twin model can more accurately reflect the real-time status of the equipment. For example, based on the actual changes in the pressure and displacement of each cylinder under different working conditions, the parameters related to the flow distribution and pressure loss of the hydraulic system in the digital twin model are dynamically adjusted to improve the accuracy of the model.

[0112] The model evaluation unit is configured to perform reliability evaluation on the digital twin model based on the comparison results of the actually collected operation data and the data output by the digital twin model, and determine whether optimization and training are needed.

[0113] In this embodiment, when the equipment is running, the real-time operating data is compared with the output of the digital twin model, and the model parameters are dynamically adjusted according to the differences. This can closely follow the actual state changes of the equipment and more accurately reflect the real-time situation of the equipment. It greatly improves the accuracy of the model and enhances the adaptability of the model to different working conditions, ensuring that the equipment operation can be effectively simulated under various complex working conditions. By conducting reliability assessment on the digital twin model, it is possible to promptly discover and resolve possible deviations or failures in the model, thereby ensuring the reliability and stability of the digital twin model.

[0114] In this embodiment, the interaction control module further includes:

[0115] The generated control instructions are input into the digital twin model, which simulates the equipment operating status after the control strategy is implemented. During the simulation, the digital twin model adjusts its own state variables and parameters according to the control instructions, such as changing the simulated values of each cylinder's pressure, displacement, oil temperature, and oil flow.

[0116] Based on the simulation results, the system evaluates whether key performance indicators of the multi-cylinder hydraulic equipment have returned to normal ranges, such as whether the pressure stability indicator has returned to a stable level and whether the displacement accuracy meets the preset standards. Furthermore, the system checks whether new potential problems have emerged during the simulation, such as whether the stress of certain components exceeds the safe range or whether it will cause abnormal fluctuations in other cylinders.

[0117] Determine whether the current control strategy and control instructions need to be optimized based on the simulation evaluation results, and send the optimized control instructions to the actuator of the multi-cylinder hydraulic equipment based on the judgment results;

[0118] Monitor the execution status of the actuator and the actual operating status changes of the multi-cylinder hydraulic equipment in real time, compare the changes in the equipment status before and after executing the control instructions, and judge the actual execution effect of the control strategy.

[0119] In this embodiment, by inputting control instructions into the digital twin model for simulation, the equipment operating status after the implementation of the control strategy is evaluated in advance, and the key performance indicators are comprehensively considered to determine whether they have returned to the normal range. This allows possible problems to be discovered and resolved before the actual execution of the control instructions, and optimizes the control strategy and instructions, greatly improving the reliability and effectiveness of the control strategy, avoiding damage to the equipment due to improper control, and monitoring the execution status and actual operating status changes of the equipment in real time. The control strategy can be adjusted in time according to the actual response of the equipment to achieve precise control of the multi-cylinder hydraulic equipment, ensure that the equipment operates in the expected state, and improve the stability and accuracy of the equipment operation. If the execution effect is poor or new problems arise, the control strategy can be adjusted in time to quickly handle abnormal situations in the equipment operation, effectively reducing the probability of equipment failure, enhancing the system's fault prevention and handling capabilities, and ensuring the continuous and stable operation of the equipment.

[0120] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive is characterized by: include: The data acquisition module is configured to deploy sensors at key locations of the multi-cylinder hydraulic equipment to collect operating data of the multi-cylinder hydraulic equipment in real time, and to adjust the frequency of data collection based on the equipment's operating status and changing trends; A twin model construction module is configured to construct a digital twin model of the multi-cylinder hydraulic equipment, analyze the physical structure and working principle of the multi-cylinder hydraulic equipment based on the collected multi-cylinder hydraulic equipment operation data, and obtain the equipment status information of the multi-cylinder hydraulic equipment; The interactive control module is configured to determine whether there is an abnormality in the multi-cylinder hydraulic equipment based on the analysis results of the digital twin model. If there is an abnormality, a control instruction is generated according to a preset control strategy and the control instruction is sent to the actuator of the multi-cylinder hydraulic equipment.

2. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 1 is characterized in that: The data acquisition module also includes: A sensor optimization unit is configured to analyze the importance and relevance of data from various parts of the multi-cylinder hydraulic equipment based on the structural characteristics and operating characteristics of the multi-cylinder hydraulic equipment, determine key installation locations of the sensors, and optimize the layout of the sensors; A data collection frequency adjustment unit is configured to monitor the equipment operating status of the multi-cylinder hydraulic equipment in real time and adjust the preset data collection frequency according to the changing trend of the equipment operating status; The equipment monitoring unit is configured to collect operating environment data of the multi-cylinder hydraulic equipment and provide equipment failure warning based on the correlation between the operating environment data and the operating data.

3. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 2 is characterized in that: The acquisition frequency adjustment unit specifically includes: Acquire the collected operating data, extract key features based on the data type of the operating data, and integrate the operating data according to the extracted key features to obtain a pressure operating data group, a displacement operating data group, an oil temperature operating data group, and an oil flow operating data group of the multi-cylinder hydraulic equipment; Based on the target values of the pressure operation data group, displacement operation data group, oil temperature operation data group, and oil flow operation data group, the target values are compared with the preset threshold range of each data group, and the equipment operation status and change trend of the multi-cylinder hydraulic equipment are judged in combination with the data fluctuation range of each data group; According to the judgment results of the equipment operation status and change trend, the corresponding data collection frequency adjustment strategy is generated to adjust the operation data collection frequency of the multi-cylinder hydraulic equipment.

4. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 3 is characterized in that: Adjust the frequency of data collection for multi-cylinder hydraulic equipment operation, including: extracting target values of the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group; Extracting preset threshold ranges corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group; Comparing the target values of the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group with their corresponding preset threshold ranges, and obtaining standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group, wherein the standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group are parameter values used to represent the data fluctuation range of each data group; Comparing the standard deviation values corresponding to the pressure operation data group, the displacement operation data group, the oil temperature operation data group, and the oil flow operation data group with a preset standard deviation threshold; When there is no data group whose standard deviation value exceeds the preset standard deviation threshold, the frequency of collecting operating data of the multi-cylinder hydraulic equipment is not adjusted; When there is a data group whose standard deviation value exceeds the preset standard deviation threshold, the data group whose standard deviation value exceeds the preset standard deviation threshold is selected as the target data group; The standard deviation values corresponding to the target data group are used for weighted averaging to obtain the comprehensive standard deviation value corresponding to the target data group; The frequency of collecting operating data of the multi-cylinder hydraulic equipment is adjusted using the comprehensive standard deviation value corresponding to the target data group.

5. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 4 is characterized in that: Adjusting the frequency of multi-cylinder hydraulic equipment operation data collection using the comprehensive standard deviation value corresponding to the target data group specifically includes: Retrieve the comprehensive standard deviation value corresponding to the target data group; Retrieve the maximum allowable standard deviation value corresponding to each data group included in the target data group; Obtaining an average value of the maximum allowable standard deviation corresponding to the target data group using the maximum allowable standard deviation value corresponding to each data group included in the target data group; Performing a ratio processing on the comprehensive standard deviation value corresponding to the target data group and the average value of the maximum allowable standard deviation corresponding to the target data group to obtain a standard deviation ratio coefficient corresponding to the target data group; The standard deviation ratio coefficient corresponding to the target data group is used to adjust the frequency of multi-cylinder hydraulic equipment operation data collection.

6. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 3 is characterized in that: Twin model building modules, including: a model building unit configured to build a basic digital twin model of the multi-cylinder hydraulic equipment based on the design drawings and physical characteristics of the multi-cylinder hydraulic equipment, so as to describe the working principle of the multi-cylinder hydraulic equipment; a data fusion unit configured to update state variables and initial parameters of the basic digital twin model of the multi-cylinder hydraulic equipment based on the acquired and collected operating data and the basic digital twin model; The state analysis unit is configured to establish an equipment state evaluation index system, extract key features of the equipment operation state based on the output results of the updated digital twin model of the multi-cylinder hydraulic equipment, and judge the equipment operation state of the multi-cylinder hydraulic equipment based on the key features and evaluation indicators.

7. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 6 is characterized in that: The status analysis unit establishes an equipment status evaluation indicator system, which specifically includes: Obtain historical operating data of multi-cylinder hydraulic equipment under different working conditions and health states, perform feature extraction on the historical operating data, and obtain the initial feature set of the equipment operating status based on the extraction results; Extract key features related to the evaluation indicators from the initial feature set and integrate them into a key feature subset, determine the equipment status evaluation indicator category, and establish labels; Based on the digital twin model of multi-cylinder hydraulic equipment, the attribute information of each key component of the multi-cylinder hydraulic equipment, the structural information of the equipment, and the preset working mode information are obtained to determine the weight value of each key component in the overall operation of the equipment; According to the weight value of each key component, corresponding quantitative standards and grading thresholds are set for each evaluation indicator, and a corresponding relationship between the indicator level and the equipment operating status is established.

8. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 7 is characterized in that: The state analysis unit further includes: Obtain the current output results from the digital twin model, including the real-time operating data of each cylinder's pressure, displacement, oil temperature, and oil flow, as well as the equipment operating status judgment results of the multi-cylinder hydraulic equipment; Combine the historical operating data of multi-cylinder hydraulic equipment, arrange them in time series, and construct a time series dataset; Extract dynamic features of time series data sets based on sliding window technology, detect data distribution of time series data sets, and determine key features in time series data sets based on the equipment status evaluation index system; The operating data of multi-cylinder hydraulic equipment is predicted based on the time series prediction model. According to the prediction results and combined with the equipment status evaluation index system, the equipment operating status of the multi-cylinder hydraulic equipment at the future moment is judged.

9. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 8, characterized in that: The twin model building module also includes: a model parameter updating unit configured to compare the real-time acquired operating data with the output data of the digital twin model during the operation of the multi-cylinder hydraulic equipment, dynamically update the model parameters using the latest acquired operating data based on the comparison results, and adjust the weights and values of the parameters in the digital twin model; The model evaluation unit is configured to perform reliability evaluation on the digital twin model based on the comparison results of the actually collected operation data and the data output by the digital twin model, and determine whether optimization and training are needed.

10. The multi-cylinder hydraulic equipment data interaction system based on digital twin drive according to claim 9, characterized in that: The interactive control module also includes: The generated control instructions are input into the digital twin model, which simulates the operating status of the equipment after the control strategy is implemented. During the simulation, the digital twin model adjusts its own state variables and parameters according to the control instructions. Based on the simulation results, evaluate whether the key performance indicators of the multi-cylinder hydraulic equipment have returned to normal ranges, and check whether new potential problems have emerged during the simulation process; Determine whether the current control strategy and control instructions need to be optimized based on the simulation evaluation results, and send the optimized control instructions to the actuator of the multi-cylinder hydraulic equipment based on the judgment results; Monitor the execution status of the actuator and the actual operating status of the multi-cylinder hydraulic equipment in real time, compare the changes in the equipment status before and after executing the control instructions, and judge the actual execution effect of the control strategy.

Images