Solenoid valve health state intelligent monitoring and quantitative evaluation method and system for complex electromechanical hydraulic system

Abstract

The invention belongs to the technical field of health monitoring of complex mechanical-electrical-hydraulic systems, and discloses an intelligent monitoring and quantitative evaluation method and system for the health state of an electromagnetic valve for a complex mechanical-electrical-hydraulic system. The method comprises the following steps: checking, screening, sequencing and the like are carried out on collected electromagnetic valve data of the complex mechanical-electrical-hydraulic system to remove invalid data, and a foundation is laid for further analysis; the method comprises the following steps: after preprocessing original data, dividing a data set into a plurality of data sets under a single Mach number working condition; aiming at data sets under different working conditions, performing fusion analysis on multi-dimensional data signals by adopting a multi-dimensional data fusion algorithm, such as a Gaussian mixture model (GMM), a self-organizing mapping model (SOM), principal component analysis (PCA), a local linear embedding algorithm (LLE) and the like; partial characteristics of the electromagnetic valve are obtained, and health state indexes of the equipment are screened from the characteristics; and in combination with expert experience knowledge, fitting the selected health state indexes by using a corresponding algorithm to obtain the full-life-cycle health state indexes of the electromagnetic valve of the complex electromechanical hydraulic system, and when the multiple health indexes of the equipment all reach a threshold value, determining that the equipment is about to have a fault.

Description

Technical Field

[0001] The present invention belongs to the technical field of health status monitoring and evaluation of electro-mechanical-hydraulic systems, and particularly relates to an intelligent monitoring and quantitative evaluation method and system for the health status of solenoid valves in complex electro-mechanical-hydraulic systems. Background Art

[0002] With the rapid development of modern industrial and transportation fields, electro-mechanical-hydraulic systems have been widely used in various complex mechanical equipment, especially in the fields of aviation, rail transit, automobiles, etc. The electro-mechanical-hydraulic system controls the working state of the hydraulic or pneumatic transmission system through key components such as solenoid valves to ensure the efficient operation and reliability of the system. In these systems, the solenoid valve plays a crucial role, and its health status directly affects the stability and safety of the entire system.

[0003] Taking the wheel brake system as an example, during the braking process of an aircraft, the solenoid valve is responsible for precisely controlling the pressure of the brake hydraulic system, thereby adjusting the braking force and response speed to ensure that the aircraft can stop smoothly and in a timely manner. Abnormal working conditions of the solenoid valve can lead to slow braking response, over-braking or complete failure, and even cause accidents in severe cases. Therefore, real-time monitoring and quantitative evaluation of the health status of solenoid valves can effectively prevent equipment failures and ensure the reliability and safety of electro-mechanical-hydraulic systems.

[0004] Currently, the health status monitoring technology of solenoid valves still faces some challenges. Traditional monitoring methods usually rely on periodic manual inspections or single physical signal monitoring, and cannot reflect the health status of solenoid valves in real time and comprehensively. With the development of intelligent technologies, health monitoring and evaluation technologies based on big data and artificial intelligence have gradually become an effective way to solve this problem. By combining sensor technology, data acquisition and processing algorithms, it is possible to integrate multiple functions such as operation monitoring, diagnostic prediction, health management, maintenance and repair of solenoid valves for complex electro-mechanical-hydraulic systems, providing an important basis for fault prevention and maintenance decision-making of complex electro-mechanical-hydraulic systems.

[0005] The present invention proposes an intelligent monitoring and quantitative evaluation method for the health status of solenoid valves in complex electro-mechanical-hydraulic systems, aiming to improve the operation reliability of solenoid valves in complex electro-mechanical-hydraulic systems, especially in the application of wheel brake systems. By real-time monitoring the working state of solenoid valves, potential fault risks can be identified in advance to ensure the efficient and safe operation of the system. Summary of the Invention

[0006] In view of the problems existing in the prior art, the present invention provides an intelligent monitoring and quantitative evaluation method for the health status of solenoid valves in complex electro-mechanical-hydraulic systems.

[0007] The present invention is implemented as follows. An intelligent monitoring and quantitative evaluation method for the health status of solenoid valves in complex electro-mechanical-hydraulic systems includes:

[0008] Step 1: Examine, screen, sort, etc. the working data of the solenoid valves in the collected complex electro-mechanical-hydraulic systems to remove invalid data, laying a foundation for further analysis;

[0009] Step 2: Preprocess the original data and divide the data set into data sets under various single Mach number conditions;

[0010] Step 3: For the data sets under different conditions, adopt a multi-dimensional data fusion algorithm to perform fusion analysis on the multi-dimensional data signals;

[0011] Step 4: Obtain some characteristics of the solenoid valves in the complex electro-mechanical-hydraulic systems and screen the health status indicators of the equipment from the characteristics;

[0012] Step 5: Combine expert experience and knowledge, use the selected health status indicators in the corresponding algorithm for fitting to obtain the health status indicators of the entire life cycle of the solenoid valves in the complex electro-mechanical-hydraulic systems. When multiple health indicators of the equipment reach the threshold, the equipment is about to fail.

[0013] Another object of the present invention is to provide an intelligent monitoring and quantitative evaluation system for the health status of solenoid valves in complex electro-mechanical-hydraulic systems, including:

[0014] Data acquisition module: A total of 5 vibration sensors are arranged on the solenoid valves in the complex electro-mechanical-hydraulic systems, namely a three-axis vibration sensor, a zero-point unidirectional vibration sensor, a three-point unidirectional vibration sensor, a six-point unidirectional vibration sensor, and a nine-point unidirectional vibration sensor, and their specifications are all 1000g range and the frequency response is 0.5 - 10000Hz;

[0015] Data preprocessing module: Data preprocessing refers to examining, screening, sorting, etc. the data of the solenoid valves in the collected complex electro-mechanical-hydraulic systems to remove invalid data, laying a foundation for further analysis;

[0016] Multi-dimensional data fusion module: For the data sets under different conditions, adopt a multi-dimensional data fusion algorithm, such as Gaussian mixture model (GMM), self-organizing mapping model (SOM), principal component analysis (PCA), locally linear embedding algorithm (LLE), etc., to perform fusion analysis on the multi-dimensional data signals and obtain some characteristics of the solenoid valves in the complex electro-mechanical-hydraulic systems;

[0017] Intelligent monitoring and quantitative evaluation module for the health status of solenoid valves in complex electro-mechanical-hydraulic systems: Combine expert experience and knowledge, use the selected health status indicators in the corresponding algorithm for fitting to obtain the health status indicators of the entire life cycle of the solenoid valves.

[0018] Another object of the present invention is to provide a computer device, which includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor executes the steps of the intelligent monitoring and quantitative evaluation method for the health status of the solenoid valve in the complex electro-mechanical-hydraulic system.

[0019] Another object of the present invention is to provide a computer-readable storage medium storing a computer program. When the computer program is executed by the processor, the processor executes the steps of the intelligent monitoring and quantitative evaluation method for the health status of the solenoid valve in the complex electro-mechanical-hydraulic system.

[0020] Another object of the present invention is to provide an information data processing terminal for implementing the intelligent monitoring and quantitative evaluation system for the health status of the solenoid valve in the complex electro-mechanical-hydraulic system.

[0021] Combined with the above technical solutions and solved technical problems, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0022] First, based on the collected working data of the solenoid valve in the complex electro-mechanical-hydraulic system, and performing data preprocessing on the collected data. For data sets under different working conditions, a multi-dimensional data fusion algorithm is used to fuse and analyze multi-dimensional data signals, obtain some characteristics of the solenoid valve in the complex electro-mechanical-hydraulic system, screen the health status indicators of the equipment from the characteristics, and combine expert experience and knowledge. The selected health status indicators are fitted using corresponding algorithms to achieve the intelligent monitoring and quantitative evaluation of the overall solenoid valve system in the complex electro-mechanical-hydraulic system.

[0023] The present invention realizes the intelligent monitoring and quantitative evaluation of the overall solenoid valve system in the complex machine liquid system through data collection, data preprocessing, multi-dimensional data fusion, then screening the health status indicators of the equipment from the characteristics, and finally combining expert experience and knowledge. Outstanding achievements have been made in other aspects of the research on solenoid valves in complex electro-mechanical systems, but there are relatively few studies in the field of intelligent monitoring and quantitative evaluation of the health status of solenoid valves in complex electro-mechanical-hydraulic systems. Especially for solenoid valve equipment in complex electro-mechanical-hydraulic systems under different working conditions, there is still a lack of effective health status monitoring and evaluation technologies. Therefore, this paper aims to explore an intelligent monitoring and quantitative evaluation method for the health status of solenoid valves in complex electro-mechanical-hydraulic systems to improve the accurate prediction ability of the health status monitoring and evaluation of complex electro-mechanical-hydraulic systems under different working conditions.

[0024] Second, the present invention proposes an intelligent monitoring and quantitative evaluation method for the health status of solenoid valves used in complex electro-mechanical-hydraulic systems. By using technologies and algorithms such as signal processing and machine learning, the respective advantages are fully utilized to select the health status indicators of solenoid valves. At the same time, combined with the relevant expert experience and knowledge, the fault alarm thresholds of the health status indicators of solenoid valves used in electro-mechanical-hydraulic systems are obtained, so as to evaluate the health status of complex electro-mechanical-hydraulic systems in real time and accurately. In the field of solenoid valves used in complex electro-mechanical-hydraulic systems, the intelligent monitoring and quantitative evaluation method for the health status of solenoid valves proposed by the present invention has strong innovation and practicability.

[0025] Third, by real-time monitoring the working state of the solenoid valve and using advanced data analysis and intelligent algorithms, the present invention evaluates the health status of the solenoid valve, thereby improving the reliability, stability and safety of the system. The solenoid valve is one of the key components in complex electro-mechanical-hydraulic systems, and its health status directly affects the operating performance and safety of the entire system. Through real-time monitoring and health assessment, potential fault risks can be identified early, avoiding system shutdowns or accidents caused by solenoid valve failures, and realizing the integration of multiple functions such as operation monitoring, diagnostic prediction, health management, maintenance and repair of solenoid valves used in complex electro-mechanical-hydraulic systems. For application fields with extremely high safety requirements such as aviation, rail transit, and automotive braking systems, the present invention can effectively improve the reliability and safety of the system, reduce the probability of failures and the losses caused by sudden failures, and ensure the safety of equipment and personnel. From the perspective of commercial value, the technical solution of the present invention is not only applicable to traditional hydraulic and pneumatic systems, but also can be widely applied to multiple fields such as rail transit, aerospace, intelligent manufacturing, and automotive electronics, with broad market prospects. Especially in complex electro-mechanical-hydraulic control systems, the health status evaluation and fault warning system of solenoid valves can provide accurate data support in various environments, providing intelligent health management solutions for multiple industries. Therefore, the present invention has strong market expansion potential and can provide sustainable technical services for related industries.

[0026] Currently, the health status monitoring of solenoid valves mostly relies on manual inspections or monitoring methods based on single physical quantities. These methods cannot monitor the working state of solenoid valves in real time and continuously, and it is difficult to accurately evaluate the risk of performance degradation or potential failures. Traditional monitoring methods cannot detect early faults or performance degradation in time, easily leading to equipment failure and system shutdown, especially in fields with high safety requirements. The present invention integrates multiple sensors for real-time data acquisition, and processes and analyzes the data through intelligent algorithms to provide a real-time health status evaluation of the solenoid valve. This technology breaks through the limitations of traditional single monitoring methods, can provide comprehensive and accurate health monitoring for complex electro-mechanical-hydraulic systems, and solves the problem of real-time monitoring of the health status of solenoid valves. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is the flowchart of the intelligent monitoring and quantitative evaluation method for the health state of the solenoid valve used in the complex electro-mechanical-hydraulic system provided by the embodiment of the present invention.

[0028] Figure 2 It is the specific flowchart of the intelligent monitoring and quantitative evaluation method for the health state of the solenoid valve used in the complex electro-mechanical-hydraulic system provided by the embodiment of the present invention.

[0029] Figure 3 It is the overall technical route of the intelligent monitoring and quantitative evaluation of the health state of the solenoid valve used in the complex electro-mechanical-hydraulic system provided by the embodiment of the present invention.

[0030] Figure 4 They are the partial statistical characteristics of the solenoid valve used in the complex electro-mechanical-hydraulic system.

[0031] Figure 5 They are the changes of the health state indicators during the whole life cycle of the solenoid valve used in the complex electro-mechanical-hydraulic system.

[0032] Figure 6 It is the structural block diagram of the intelligent monitoring and quantitative evaluation system for the health state of the solenoid valve used in the complex electro-mechanical-hydraulic system provided by the embodiment of the present invention. Specific Embodiments

[0033] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the following further elaborates on the present invention in combination with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0034] For the intelligent monitoring and quantitative evaluation method of the health state of the solenoid valve used in the complex electro-mechanical-hydraulic system described in this embodiment, the operation data of the solenoid valve is first obtained through the data acquisition module. Specifically, five vibration sensors are arranged on the solenoid valve, including a three-axis vibration sensor, a zero-point single-direction vibration sensor, a three-point single-direction vibration sensor, a six-point single-direction vibration sensor, and a nine-point single-direction vibration sensor. The measuring ranges of these sensors are all 1000 grams, and the frequency response range covers 0.5 to 10000 Hz, which can accurately capture the vibration characteristics of the solenoid valve under different working conditions. The vibration data collected by the sensors in real time is transmitted to the data preprocessing module as the original input for subsequent analysis.

[0035] Next, the data preprocessing module performs processing operations such as auditing, screening, and sorting on the collected solenoid valve vibration data. Specifically, the module first audits the integrity and consistency of the data, and eliminates outliers or noise data that occur during the collection process. Subsequently, it screens out valid vibration signals and sorts the data according to time or other relevant criteria to ensure the continuity and accuracy of the data. Through these preprocessing steps, the system can effectively remove invalid data, ensuring that subsequent analysis is based on high-quality input data, thereby improving the reliability and accuracy of monitoring and evaluation.

[0036] After completing the data preprocessing, the system divides the preprocessed original dataset into datasets under various single Mach number operating conditions. The dataset under each operating condition represents the vibration characteristics of the solenoid valve under specific operating conditions. The purpose of this step is to classify and manage complex multi-condition data, facilitating the use of corresponding analysis algorithms for in-depth processing for different operating conditions. In this way, the system can more accurately capture and analyze the operating characteristics of the solenoid valve under different working states, improving the meticulousness and accuracy of health status monitoring.

[0037] Subsequently, the multi-dimensional data fusion module performs signal fusion analysis on the datasets under different operating conditions using a variety of multi-dimensional data fusion algorithms. Specifically, the system can select advanced multi-dimensional data processing technologies such as Gaussian mixture model (GMM), self-organizing map model (SOM), principal component analysis (PCA), and locally linear embedding algorithm (LLE) to fuse the collected multi-dimensional vibration signals. These algorithms can effectively extract the key feature information during the operation of the solenoid valve, reduce the data dimension, and remove redundant information, thereby obtaining the key feature indicators reflecting the health status of the solenoid valve. Through multi-dimensional data fusion, the system can more comprehensively and accurately reflect the operating state of the solenoid valve, providing a solid data foundation for subsequent health assessment.

[0038] After the feature extraction is completed, the intelligent monitoring and quantitative evaluation module for the health status of the solenoid valve in complex electro-mechanical-hydraulic systems combines expert experience and knowledge to perform fitting analysis on the selected health status indicators. The specific steps include using corresponding algorithms to perform mathematical fitting on the selected health status indicators to generate the health status indicators for the entire life cycle of the solenoid valve. These health status indicators can quantitatively reflect the operating health status of the solenoid valve during its entire service life. When multiple health indicators simultaneously reach the preset threshold, the system determines that the solenoid valve is about to fail. This determination process provides an important basis for equipment maintenance and fault prevention, ensuring the stable operation and efficient management of complex electro-mechanical-hydraulic systems.

[0039] Finally, when the system detects that the health status index of the solenoid valve reaches the failure threshold, it can promptly send out a warning signal to notify the maintenance personnel for inspection and replacement. This intelligent monitoring and evaluation process realizes the full-life cycle management of the health status of the solenoid valve, significantly improving the reliability and service life of the equipment. At the same time, through continuous data collection and analysis, the system has accumulated a large amount of operation data and health status information, providing valuable reference materials for future equipment optimization and performance improvement. Generally speaking, through the integration of advanced data processing and analysis technologies, the present invention realizes the efficient, accurate, and intelligent health status monitoring and quantitative evaluation of the solenoid valve in complex electro-mechanical-hydraulic systems, meeting the high standards of modern industrial equipment management requirements.

[0040] As Figure 1 shown, a method for intelligent monitoring and quantitative evaluation of the health status of a solenoid valve for a complex electro-mechanical-hydraulic system provided by an embodiment of the present invention includes the following steps:

[0041] S101, perform processing such as auditing, screening, and sorting on the collected solenoid valve data to remove invalid data;

[0042] S102, preprocess the original data and divide the data set into data sets under various single Mach number working conditions;

[0043] S103, for the data sets under different working conditions, adopt a multi-dimensional data fusion algorithm to perform fusion analysis on multi-dimensional data signals;

[0044] S104, after the multi-dimensional data signal fusion, obtain some characteristics of the solenoid valve in the complex electro-mechanical-hydraulic system, and then screen the health status indicators of the equipment from the characteristics;

[0045] S105, combine expert experience and knowledge to obtain the full-life cycle health status indicators of the solenoid valve in the complex electro-mechanical-hydraulic system. When multiple health indicators of the equipment reach the threshold, the equipment is about to fail.

[0046] A system for intelligent monitoring and quantitative evaluation of the health status of a solenoid valve in a complex electro-mechanical-hydraulic system as described in claim 1 provided by an embodiment of the present invention, characterized in that the system for intelligent monitoring and quantitative evaluation of the health status of the solenoid valve in the complex electro-mechanical-hydraulic system includes:

[0047] Data acquisition module: A total of 5 vibration sensors are arranged on the solenoid valve of the complex electro-mechanical-hydraulic system, namely a three-axis vibration sensor, a zero-point unidirectional vibration sensor, a three-point unidirectional vibration sensor, a six-point unidirectional vibration sensor, and a nine-point unidirectional vibration sensor, and their specifications are all 1000g range and the frequency response is 0.5~10000Hz;

[0048] Data preprocessing module: Data preprocessing refers to the processing of the collected solenoid valve data, such as auditing, screening, sorting, etc., to remove invalid data and lay a foundation for further analysis;

[0049] Multidimensional data fusion module: For datasets under different working conditions, multidimensional data fusion algorithms are adopted, such as Gaussian mixture model (GMM), self-organizing mapping model (SOM), principal component analysis (PCA), locally linear embedding algorithm (LLE), etc., to fuse and analyze multidimensional data signals and obtain some characteristics of the solenoid valve for complex electro-hydraulic systems;

[0050] Intelligent monitoring and quantitative evaluation module for the health status of solenoid valves for complex electro-hydraulic systems: Combining expert experience and knowledge, the selected health status indicators are fitted using corresponding algorithms to obtain the health status indicators of the solenoid valve throughout its life cycle.

[0051] A computer device provided by an embodiment of the present invention, the computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electro-hydraulic systems.

[0052] A computer-readable storage medium provided by an embodiment of the present invention, storing a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electro-hydraulic systems.

[0053] An information data processing terminal provided by an embodiment of the present invention, the information data processing terminal is used to implement the system for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electro-hydraulic systems.

[0054] As Figure 2 shown, the specific steps of a method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electro-hydraulic systems provided by an embodiment of the present invention are as follows:

[0055] S1: Collect raw data from sensors;

[0056] S2: Process the collected solenoid valve data, such as auditing, screening, sorting, etc., to remove invalid data and lay a foundation for further analysis;

[0057] S3: Preprocess the raw data and divide the dataset into datasets under various single Mach number working conditions;

[0058] S4: For datasets under different working conditions, adopt a multidimensional data fusion algorithm to fuse and analyze multidimensional data signals;

[0059] S5: After the multi-dimensional data signals are fused, some characteristics of the solenoid valve in the complex electro-mechanical-hydraulic system are obtained. After analysis and comparison, health indicators are selected.

[0060] S6: Combining expert experience and knowledge, corresponding algorithms are used to fit the selected health state indicators to obtain the health state indicators of the solenoid valve throughout its life cycle.

[0061] S7: Monitor and evaluate the health condition of the solenoid valve in the complex hydraulic system. When multiple health indicators of the equipment reach the threshold, the equipment is about to fail.

[0062] The technical effects of the present invention will be described in detail below in combination with tests.

[0063] In the application embodiment of the present invention, a vibration sensor is used to collect the working data of the solenoid valve in the complex electro-mechanical-hydraulic system. First, the collected solenoid valve data is processed such as auditing, screening, sorting, etc. to remove invalid data, laying a foundation for further analysis. After preprocessing the original data, the data set is divided into data sets under various single Mach number working conditions. For the data sets under different working conditions, a multi-dimensional data fusion algorithm is adopted to perform fusion analysis on the multi-dimensional data signals. After the multi-dimensional data is fused, some characteristics of the solenoid valve in the complex electro-mechanical-hydraulic system are obtained. After analyzing and comparing the above characteristics, health indicators are selected. Combining expert experience and knowledge, the selected health state indicators are fitted with corresponding algorithms to obtain the health state indicators of the solenoid valve throughout its life cycle. When multiple health indicators of the working equipment reach the threshold, the equipment is about to fail.

[0064] Through analysis, the characteristics of the solenoid valve with a degradation trend are obtained. In order to avoid the influence of vibration time on the characteristics, after analyzing and comparing the characteristics, 4 characteristics, namely, the kurtosis factor of the X-radial vibration acceleration, the peak factor of the X-radial vibration acceleration, the kurtosis factor of the Y-axial vibration acceleration, and the pulse factor of the Y-axial vibration acceleration, are selected as the characteristics for the next health state evaluation. Combining expert experience and knowledge, the selected health state indicators are fitted with corresponding algorithms to obtain the change of the health state indicators of the solenoid valve throughout its life cycle as Figure 5 shown. Among them, the kurtosis factor of the X-radial vibration is less than 7.61e-05, the peak factor of the X-radial vibration is less than 17.74, the kurtosis factor of the Y-axial vibration is greater than 2.92e-16 and the pulse factor of the Y-axial vibration is greater than 0.08. When the vibration signal of the solenoid valve does not meet the above conditions, the solenoid valve is about to fail.

[0065] In the application embodiment of the present invention, the working data of the solenoid valve in the complex electro-mechanical-hydraulic system is obtained through a vibration sensor. First, the collected solenoid valve data is audited, screened, and sorted to remove invalid data and prepare for subsequent analysis. After data preprocessing, the original data is divided according to different Mach number working conditions, and for each working condition dataset, multi-dimensional data fusion technology is applied to integrate and analyze multi-dimensional signals. The fused data helps to extract relevant features of the solenoid valve. Through the analysis and comparison of these features, appropriate health indicators are selected, and combined with expert experience, the selected health indicators are fitted using a specific algorithm, and then the health status indicators of the entire life cycle of the solenoid valve are obtained. When multiple health indicators reach the set threshold during the operation of the equipment, it indicates that the equipment is about to fail.

[0066] Intelligent monitoring and quantitative evaluation of the health status of solenoid valves used in complex electro-mechanical-hydraulic systems bring the following benefits to complex electro-mechanical-hydraulic systems:

[0067] 1. Improve system safety: By real-time monitoring the health status of the solenoid valve, potential faults can be detected early, maintenance can be carried out in advance, and system downtime caused by sudden faults can be avoided, thus improving the overall reliability of the system.

[0068] 2. Optimize maintenance strategies: Intelligent monitoring technology can accurately evaluate the working status of the solenoid valve and predict its remaining useful life (RUL), thus helping to formulate a scientific predictive maintenance plan and avoid problems of over-maintenance or under-maintenance.

[0069] 3. Extend equipment life: Through regular health status evaluation, abnormal solenoid valves can be adjusted and repaired in time, reducing the risk of premature equipment damage and extending the service life of the solenoid valve and the entire electro-mechanical-hydraulic system.

[0070] 4. Reduce maintenance costs: Through intelligent monitoring, unnecessary manual inspections and fault handling can be reduced, saving maintenance costs. In addition, by reducing fault downtime and increasing equipment life, the overall operating costs can also be significantly reduced in the long term.

[0071] 5. Enhance safety: In electro-mechanical-hydraulic systems, solenoid valves usually undertake the function of controlling and regulating important fluids or gases. If a failure occurs, it will cause safety hazards. By real-time monitoring the health status of the solenoid valve, safety accidents caused by failures can be effectively prevented.

[0072] 6. Support intelligent and automated management: After integrating health status monitoring and quantitative evaluation methods, the electro-mechanical-hydraulic system can achieve more intelligent management. The automated system can automatically adjust the operation strategy according to the health assessment results and even perform autonomous maintenance.

[0073] 7. Real-time data analysis and decision support: Based on the data analysis of health status monitoring, the system can provide real-time feedback on the performance changes and potential problems of the solenoid valve, assisting maintenance personnel in making timely decisions and improving the decision-making efficiency and quality of the overall system.

[0074] 8. Improve system performance: Health status monitoring can ensure that the solenoid valve operates in the best state, avoiding performance degradation caused by aging or faults, thereby improving the working efficiency and stability of the entire electro-mechanical-hydraulic system.

[0075] In summary, through the intelligent monitoring and quantitative evaluation of the health status of the solenoid valve, timely alarm, automatic diagnosis, and scientific prediction of the faults of the solenoid valve equipment for complex electro-mechanical-hydraulic systems are realized, which can provide more efficient and accurate support for the optimization, maintenance, and operation of complex electro-mechanical-hydraulic systems.

[0076] Figure 4 Shows some statistical characteristics of the solenoid valve. After analyzing and comparing the characteristics, four characteristics, namely the kurtosis factor of the X-radial vibration acceleration, the peak factor of the X-radial vibration acceleration, the kurtosis factor of the Y-axial vibration acceleration, and the impulse factor of the Y-axial vibration acceleration, are selected as the characteristics for the next health status evaluation. Combining expert experience and knowledge, the selected health status indicators are fitted using corresponding algorithms to obtain the changes in the health status indicators of the solenoid valve throughout its life cycle as Figure 5 shown. Among them, the kurtosis factor of the X-radial vibration is less than 7.61e-05, the peak factor of the X-radial vibration is less than 17.74, the kurtosis factor of the Y-axial vibration is greater than 2.92e-16 and the impulse factor of the Y-axial vibration is greater than 0.08. When the vibration signal of the solenoid valve does not meet the above conditions, the solenoid valve is about to fail.

[0077] Example 1: Health monitoring of solenoid valves in petrochemical production lines

[0078] In petrochemical production lines, solenoid valves, as key control components, are widely used in the precise control and regulation of liquids and gases. To ensure the stable operation of the production line and the efficient operation of the equipment, this example applies the real-time state monitoring method of the power converter based on heterogeneous embedded digital twins of the present invention to conduct intelligent monitoring and quantitative evaluation of the health status of key solenoid valves in the production line.

[0079] Install five vibration sensors on each key solenoid valve, including a triaxial vibration sensor and four unidirectional vibration sensors, which are located at different positions to comprehensively capture the vibration characteristics of the solenoid valve. The range of these sensors is 1000 grams, and the frequency response range is 0.5 to 10000 Hz, which can collect the vibration data of the solenoid valve under different working conditions in real time. The collected data is transmitted to the data preprocessing module through the data acquisition module for preliminary review, screening, and sorting, and invalid data is removed to ensure the accuracy of subsequent analysis.

[0080] The preprocessed dataset is divided into multiple subsets according to different single Mach number conditions. Subsequently, the multi-dimensional data fusion module uses algorithms such as Gaussian mixture model (GMM) and principal component analysis (PCA) to perform fusion analysis on the multi-dimensional vibration signals under each condition, and extracts key features reflecting the health status of the solenoid valve. These features are further screened as health status indicators to serve as the basis for quantitative evaluation.

[0081] The health status intelligent monitoring and quantitative evaluation module combines expert experience and knowledge, and uses fitting algorithms to analyze the selected health status indicators to generate health status indicators for the entire life cycle of the solenoid valve. When multiple health indicators reach the preset threshold simultaneously, the system determines that the solenoid valve is about to fail and issues a warning signal in a timely manner. Maintenance personnel arrange maintenance and replacement in advance according to the warning information to avoid production line shutdown caused by solenoid valve failure and ensure the continuity of the production process and the long-term stable operation of the equipment.

[0082] Embodiment 2: Monitoring of the solenoid valve control system in an autonomous vehicle

[0083] In an autonomous vehicle, solenoid valves are widely used in hydraulic systems and braking systems to precisely control hydraulic flow and braking force distribution. To improve the safety and reliability of the vehicle, this embodiment uses the real-time status monitoring method of the power converter based on heterogeneous embedded digital twins of the present invention to perform intelligent monitoring and quantitative evaluation of the health status of the solenoid valves in the autonomous vehicle.

[0084] Five vibration sensors are installed on each key solenoid valve, including a three-axis vibration sensor and four single-axis vibration sensors, which are installed at different positions of the solenoid valve respectively to comprehensively capture its vibration characteristics during operation. The range of these sensors is 1000 grams, and the frequency response range is 0.5 to 10000 Hz, which can collect the vibration data of the solenoid valve under different driving conditions in real time. The collected data is transmitted to the data preprocessing module through the data acquisition module for data review, screening and sorting to remove noise and outliers and ensure data quality.

[0085] The preprocessed dataset is divided into datasets of multiple single conditions according to different driving conditions of the vehicle (such as acceleration, braking, steering, etc.). The multi-dimensional data fusion module uses multi-dimensional data fusion algorithms such as self-organizing mapping model (SOM) and locally linear embedding algorithm (LLE) to deeply analyze the vibration signals under each condition and extracts key health features. These features are screened as health status indicators to serve as the basic data for subsequent quantitative evaluation.

[0086] The intelligent health status monitoring and quantitative evaluation module combines expert knowledge and historical data, and uses a fitting algorithm to analyze the selected health status indicators, generating the health status indicators of the solenoid valve throughout its life cycle. When multiple health indicators reach or exceed the set thresholds, the system automatically determines that the solenoid valve is about to fail and sends a warning signal to the driver through the in-vehicle display system. At the same time, the system transmits the fault warning information to the vehicle maintenance system to guide technicians to perform maintenance or replacement in a timely manner, ensuring the safety and stability of the autonomous vehicle during driving.

[0087] The above two embodiments demonstrate the specific applications of the present invention in different application scenarios. In a petrochemical production line and an autonomous vehicle respectively, through the real-time status monitoring method of the power converter based on heterogeneous embedded digital twins, the efficient, accurate and intelligent health status monitoring and quantitative evaluation of the solenoid valve are realized, improving the overall reliability and operation efficiency of the system.

[0088] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention by those skilled in the art within the technical scope disclosed by the present invention shall be covered by the protection scope of the present invention.

Claims

1. A method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electromechanical and hydraulic systems, characterized in that: The following steps are involved: Step 1: Review, filter, sort and process the collected solenoid valve data of complex electromechanical and hydraulic systems to remove invalid data; Step 2, after preprocessing the original data, the data set is divided into data sets under multiple single Mach number conditions; Step 3: For data sets of different working conditions, multidimensional data fusion algorithms, such as Gaussian mixture model, self-organizing map model, principal component analysis, and local linear embedding algorithm, are used to fuse and analyze multidimensional data signals; Step 4, obtaining some features of the solenoid valve used in the complex electromechanical and hydraulic system, and selecting the health status indicators of the equipment from the features; Step five: Combined with expert experience and knowledge, the selected health status indicators are fitted using the corresponding algorithm to obtain the health status indicators of the solenoid valve in the complex electromechanical and hydraulic system throughout its life cycle. When multiple health indicators of the equipment reach the threshold, the equipment is about to fail.

2. The method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electromechanical and hydraulic systems according to claim 1, characterized in that: The step one comprises: Review the collected solenoid valve vibration data to ensure the integrity and consistency of the data; Eliminate outliers or noise data generated during the acquisition process; The filtered valid vibration signals are sorted according to time or other relevant criteria.

3. The method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electromechanical and hydraulic systems according to claim 1, characterized in that: The second step comprises: The preprocessed raw data set is classified according to different single Mach number conditions; An independent data subset is established for each working condition to facilitate subsequent processing using the corresponding analysis algorithm.

4. The method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electromechanical and hydraulic systems according to claim 1, characterized in that: The step three comprises: Gaussian mixture model is used to model the probability distribution of multidimensional vibration signals; Use the self-organizing map model to perform topological mapping on multidimensional data; Reduce data dimensions and extract main features through principal component analysis; A locally linear embedding algorithm is applied to preserve the local structure information of the data.

5. The method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electromechanical and hydraulic systems according to claim 1, characterized in that: The fourth step comprises: Extract key features from the multi-dimensional features obtained by fusion analysis; Filter out key indicators that reflect the health status of equipment based on preset standards; Form a set of indicators for health status assessment.

6. The method for intelligent monitoring and quantitative evaluation of the health status of solenoid valves for complex electromechanical and hydraulic systems according to claim 1, characterized in that: The step five comprises: Use regression algorithm to mathematically fit the selected health status indicators; Generate health status indicators for the entire life cycle of the solenoid valve; When multiple health status indicators reach preset thresholds at the same time, it is determined that the solenoid valve is about to fail.

7. An intelligent monitoring and quantitative evaluation system for the health status of solenoid valves used in complex electromechanical and hydraulic systems, characterized in that: include: The data acquisition module is used to arrange five vibration sensors on the solenoid valve of the complex electromechanical hydraulic system, including a three-axis vibration sensor, a zero-point unidirectional vibration sensor, a three-point unidirectional vibration sensor, a six-point unidirectional vibration sensor, and a nine-point unidirectional vibration sensor, each with a measuring range of 1000 grams and a frequency response range of 0.5 to 10,000 Hz; The data preprocessing module is used to review, filter, sort and process the collected solenoid valve data to remove invalid data; The multidimensional data fusion module is used to perform fusion analysis on multidimensional data signals for data sets of different working conditions using multidimensional data fusion algorithms, such as Gaussian mixture model, self-organizing map model, principal component analysis, local linear embedding algorithm, etc.; The intelligent monitoring and quantitative evaluation module for the health status of solenoid valves used in complex electromechanical and hydraulic systems is used to combine expert experience and knowledge, fit the selected health status indicators using corresponding algorithms, and generate health status indicators for the entire life cycle of the solenoid valve.

8. The intelligent monitoring and quantitative evaluation system for the health status of solenoid valves for complex electromechanical and hydraulic systems according to claim 1, characterized in that: The data acquisition module comprises: a three-axis vibration sensor; a zero-point unidirectional vibration sensor; a three-point unidirectional vibration sensor; a six-point unidirectional vibration sensor; A nine-point unidirectional vibration sensor.

9. The intelligent monitoring and quantitative evaluation system for the health status of solenoid valves for complex electromechanical and hydraulic systems according to claim 1, characterized in that: The multidimensional data fusion algorithm adopted by the multidimensional data fusion module is selected from one or more of a Gaussian mixture model, a self-organizing map model, a principal component analysis, and a local linear embedding algorithm.

10. The intelligent monitoring and quantitative evaluation system for health status of solenoid valves for complex electromechanical and hydraulic systems according to claim 1, characterized in that: The intelligent monitoring and quantitative evaluation module for the health status of solenoid valves for complex electromechanical and hydraulic systems includes: A health status indicator screening unit is used to screen out key indicators reflecting the health status of the solenoid valve from the multi-dimensional features obtained by fusion analysis; A health status index fitting unit is used to perform mathematical fitting on the selected health status index using a corresponding algorithm to generate a health status index for the entire life cycle of the solenoid valve; The fault determination unit is used to determine that the solenoid valve is about to fail when multiple health status indicators reach preset thresholds at the same time.

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