A solenoid valve self-diagnosis and self-repair control system

Abstract

The application relates to a solenoid valve self-diagnosis and self-repair control system, which comprises a data acquisition module, a fault diagnosis module and a self-repair module; the data acquisition module comprises a sensor group and data preprocessing; the sensor group comprises a current sensor, a pressure sensor, a temperature sensor and a position sensor; the working signals of the solenoid valve are collected in real time through the sensor group; the data of the sensor group is firstly subjected to filtering and preprocessing to remove noise and abnormal data; the fault diagnosis module performs fault diagnosis; the self-repair module automatically triggers a self-repair strategy when the fault diagnosis module confirms that a fault exists; and the control system module uses a feedback control algorithm to ensure that the solenoid valve is always kept in an optimal working state by adjusting a control signal in real time. The application overcomes the problem that a traditional control system cannot repair faults in real time by introducing intelligent diagnosis and self-repair control technology.

Description

Technical Field

[0001] This invention relates to the field of solenoid valve control technology, specifically to a solenoid valve self-diagnosis and self-repair control system. Background Technology

[0002] Solenoid valves are widely used in automated control systems, especially in hydraulic and pneumatic fields, where they play a crucial control role. However, during long-term operation, solenoid valves are often affected by various factors, such as valve core jamming, solenoid coil damage, and seal aging, leading to malfunctions. These malfunctions are often difficult to detect in a timely manner using traditional detection methods, and once they occur, they may cause system downtime, performance degradation, or safety hazards. Existing solenoid valve monitoring technologies mainly rely on external sensors or periodic maintenance, but these methods suffer from problems such as delayed fault detection, inability to repair in real time, and insufficient diagnosis of complex faults. Traditional solenoid valve control systems lack intelligent fault diagnosis and repair functions, and cannot effectively guarantee the long-term reliability and stability of solenoid valves.

[0003] Therefore, there is still room for improvement in existing solenoid valve technology. Summary of the Invention

[0004] To address the aforementioned shortcomings, the purpose of this invention is to provide a solenoid valve control system with self-diagnosis and self-repair functions, thereby achieving higher operational reliability, reducing downtime, and improving the overall efficiency of the automated control system, thus solving the existing technical problems.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A solenoid valve self-diagnosis and self-repair control system, the system comprising: Data acquisition module: The data acquisition module includes a sensor group and data preprocessing. The sensor group includes a current sensor, a pressure sensor, a temperature sensor, and a position sensor. The working signal of the solenoid valve is acquired in real time through the sensor group. The data from the sensor group is first filtered and preprocessed to remove noise and abnormal data. Fault Diagnosis Module: The fault diagnosis module performs fault diagnosis. During the diagnosis process, the fault diagnosis module accepts input from the sensor group and compares the historical data and normal operating condition data of the solenoid valve. Through data fusion technology, it uses neural networks to diagnose the potential fault types of the solenoid valve. Decision and Repair Module: Includes a self-repair module and a control system module, wherein, Self-repair module: When the fault diagnosis module confirms the existence of a fault, the self-repair module automatically triggers the self-repair strategy; Control system module: Based on the fault diagnosis results and self-repair strategy, the control system module dynamically adjusts the working control strategy of the solenoid valve; the control system module uses feedback control algorithm to ensure that the solenoid valve always maintains the optimal working state by adjusting the control signal in real time.

[0006] According to the solenoid valve self-diagnosis and self-repair control system described in the embodiments of this application, the system further includes: Execution module: includes solenoid valve actuator, which ensures the continuous and reliable operation of the solenoid valve; Data transmission module: The data acquisition module, fault diagnosis module, decision-making and repair module, and execution module exchange data through the industry standard communication protocol of the data transmission module; the data transmission module ensures the real-time performance and stability of the data acquisition module, fault diagnosis module, decision-making and repair module, and execution module.

[0007] According to the embodiments of this application, the solenoid valve self-diagnosis and self-repair control system includes a sensor group comprising a current sensor, a pressure sensor, a temperature sensor, and a position sensor.

[0008] According to the solenoid valve self-diagnosis and self-repair control system described in the embodiments of this application, the self-repair control strategy adopts an adaptive PID control algorithm, the formula of which is: Wherein, the current error of the solenoid valve is e(t), and the system's repair control signal is u(t). These are the proportional, integral, and differential gain coefficients, respectively, and e(t) is the error signal of the solenoid valve.

[0009] According to the solenoid valve self-diagnosis and self-repair control system described in the embodiments of this application, the system employs fuzzy control to address nonlinear problems in solenoid valve control; in fuzzy control, decisions are made through fuzzy inference formulas: Where e(t) is the current error, Δe(t) is the rate of change of the error, and f is the fuzzy inference function.

[0010] According to the embodiments of this application, the solenoid valve self-diagnosis and self-repair control system uses an adaptive PID control algorithm and a fuzzy control algorithm to enable the solenoid valve to intelligently adjust its operating parameters when facing complex working conditions.

[0011] This application addresses the limitations of existing solenoid valve control systems, such as lag in fault diagnosis and repair, poor real-time performance, and reliance on external sensors. It provides a solenoid valve self-diagnosis and self-repair control system that monitors and analyzes the solenoid valve's operating status in real time, promptly identifies potential faults, and automatically repairs them, reducing system downtime and improving the solenoid valve's reliability and adaptability. Compared to existing technologies, this application overcomes the problem of traditional control systems being unable to repair faults in real time by introducing intelligent diagnostic and self-repair control technology, ensuring that the solenoid valve maintains optimal operating condition under complex working conditions.

[0012] Due to the adoption of the above technical features, this invention has the following advantages and positive effects compared with the prior art: First, this application overcomes the problem that traditional control systems cannot repair faults in real time by introducing intelligent diagnostic and self-repair control technologies; Second, this application ensures that the solenoid valve always maintains optimal operating condition under complex working conditions.

[0013] Of course, implementing any specific embodiment of the present invention does not necessarily have all of the above technical effects at the same time. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the solenoid valve self-diagnosis and self-repair control system of this application. Detailed Implementation

[0015] The following describes several preferred embodiments of the present invention in detail with reference to the accompanying drawings, but the present invention is not limited to these embodiments. The present invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of the present invention. To provide the public with a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments, but those skilled in the art will fully understand the present invention without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of the present invention, well-known methods, processes, procedures, elements, etc., are not described in detail.

[0016] Please refer to Figure 1 To address the problems of delayed fault diagnosis and difficult repair in existing solenoid valves, this application proposes a self-diagnostic and self-repair control system for solenoid valves. This system achieves continuous and reliable operation of the solenoid valve through a close integration of fault diagnosis, real-time repair, and adaptive control strategies.

[0017] This application provides a solenoid valve self-diagnosis and self-repair control system, the system comprising: 1. A data acquisition module: the data acquisition module includes a sensor group and data preprocessing, the sensor group including a current sensor, a pressure sensor, a temperature sensor, and a position sensor; the working signal of the solenoid valve is acquired in real time through the sensor group, the sensor group monitoring parameters including current, pressure, temperature, and position; the data from the sensor group is first filtered, noise and abnormal data are removed through the data preprocessing.

[0018] 2. Fault Diagnosis Module: The fault diagnosis module performs fault diagnosis. During the diagnosis process, the module receives input from the sensor group and compares the historical data and normal operating condition data of the solenoid valve to ensure high accuracy of the diagnosis results. The fault diagnosis module is responsible for real-time monitoring of the solenoid valve's operating status and analyzing data collected from the current sensor, pressure sensor, temperature sensor, and position sensor. Through data fusion technology, it comprehensively analyzes various monitoring signals and uses neural networks to diagnose potential fault types of the solenoid valve.

[0019] 3. Decision and Repair Module: This module includes a self-repair module and a control system module. The self-repair module automatically triggers a self-repair strategy when the fault diagnosis module confirms a fault. Specific repair measures include adjusting control parameters (such as current and valve core position) to restore the solenoid valve to its normal operating state. If the solenoid coil malfunctions, the system adjusts the current; if the valve core is stuck, the system adjusts the valve core position or changes the valve opening to restore normal flow. The control system module dynamically adjusts the solenoid valve's operating control strategy based on the fault diagnosis results and the self-repair strategy. This module not only adjusts the control signal when a fault occurs but also optimizes the control signal during normal operation, improving response speed and accuracy. The control system module utilizes a feedback control algorithm to ensure the solenoid valve always remains in its optimal operating state by adjusting the control signal in real time.

[0020] 4. Execution module: including a solenoid valve actuator, which performs the continuous and reliable operation of the solenoid valve.

[0021] 5. Data transmission module: The data acquisition module, fault diagnosis module, decision-making and repair module, and execution module exchange data through the industrial standard communication protocol of the data transmission module; the data transmission module ensures the real-time performance and stability of the data acquisition module, fault diagnosis module, decision-making and repair module, and execution module. When a fault occurs, the control system can obtain fault diagnosis information in a short time and process and respond accordingly.

[0022] Preferably, the sensor group of this application includes a current sensor, a pressure sensor, a temperature sensor, and a position sensor.

[0023] Preferably, the self-repair control strategy employs an adaptive PID control algorithm, the formula of which is: Wherein, the current error of the solenoid valve is e(t), and the system's repair control signal is u(t). These are the proportional, integral, and differential gain coefficients, respectively, and e(t) is the error signal of the solenoid valve.

[0024] Furthermore, the system employs fuzzy control to address the nonlinearity issues in solenoid valve control; in fuzzy control, decisions are made using fuzzy inference formulas. Where e(t) is the current error, Δe(t) is the rate of change of the error, and f is the fuzzy inference function.

[0025] The working principle of this application is explained below: The system performs fault diagnosis and repair according to the following process during operation: 1. Real-time data acquisition: The solenoid valve's operating signals are acquired in real time through sensors, which monitor parameters including current, pressure, temperature, and position. This sensor data is first filtered and preprocessed to remove noise and abnormal data.

[0026] Fault Diagnosis and Analysis: The pre-processed data is transmitted to the fault diagnosis module. This module uses a neural network to analyze the data and identify potential fault types in the solenoid valve. By comparing historical operating conditions with current operating data, the fault diagnosis module can accurately identify whether the solenoid valve has a fault and pinpoint the specific fault type (such as valve core jamming, solenoid coil failure, seal failure, etc.).

[0027] Automatic Repair and Control Adjustment: Once the fault diagnosis module confirms a fault, the system will activate the self-repair module. Depending on the fault type, the system will adjust the control signal of the solenoid valve. For example, if the valve core is stuck, the system will increase the drive voltage to adjust the valve core position; if the solenoid coil temperature is too high, the system will automatically reduce the current to prevent further damage. After adjustment, the control system module continues to monitor the status of the solenoid valve to ensure it returns to normal operation.

[0028] 2. Control System Module (Optimization and Continuous Monitoring): After the repair is complete, the control system module will optimize the operating parameters of the solenoid valve to ensure its optimal performance and notify the solenoid valve actuator in the execution module to ensure the continuous and reliable operation of the solenoid valve. Simultaneously, the system continues to monitor the solenoid valve's operating data in real time to ensure the reliability and stability of the solenoid valve throughout its entire lifespan.

[0029] 3. Fault diagnosis and self-repair function Fault Diagnosis Function: The fault diagnosis module analyzes the solenoid valve's operating signals using data fusion technology to identify faults and determine their types. By comparing normal operating conditions with historical data, the module can accurately diagnose faults in the shortest possible time. Especially with multi-dimensional sensor data input, algorithms can identify potential minor faults, providing early warnings and reducing downtime.

[0030] Self-healing function: When the system detects a fault, the self-healing module immediately activates and takes appropriate corrective measures. For example, if an abnormal current occurs, the system will automatically adjust the drive current; if the valve core position is offset, the system will adjust the valve core drive signal. In this way, the system can repair faults in a timely manner, avoiding the impact of faults on the overall system operation.

[0031] Adaptive control strategies, algorithms, and repair strategies: The self-repair control strategy of this invention employs an advanced adaptive PID control algorithm. Assuming the current error of the solenoid valve is e(t), the system's repair control signal u(t) is given by the following formula:

[0032] in, Here, represents the proportional, integral, and derivative gain coefficients, respectively, and e(t) represents the error signal of the solenoid valve (e.g., valve core position error or flow error). This formula enables the solenoid valve's control signal to quickly return to normal operation through real-time analysis and adjustment of the error.

[0033] In addition to adaptive PID control, the system also employs fuzzy control to address the nonlinearity issues in solenoid valve control. In fuzzy control, the system makes decisions using the following fuzzy inference formula: Where e(t) is the current error, Δe(t) is the rate of change of the error, and f is the fuzzy inference function, which adjusts the control signal based on the actual operating state and empirical rules. Fuzzy control is suitable for nonlinear control problems of solenoid valves and can maintain system stability in complex operating environments.

[0034] 4. Data transmission and communication The data transmission module ensures efficient and stable data exchange between modules, especially in the event of a fault, enabling timely transmission of fault diagnosis information to the control system module. The data transmission module employs industry-standard communication protocols (such as Modbus RTU or CAN) to guarantee data real-time performance and accuracy. Through efficient data exchange, the system can complete fault detection, repair, and control adjustments in the shortest possible time, ensuring the long-term stable operation of the solenoid valve.

[0035] In summary, this application has the following beneficial effects. (1) Real-time fault diagnosis and repair: This application can monitor the working status of the solenoid valve in real time and identify potential faults in a timely manner through intelligent fault diagnosis algorithms, avoiding the downtime or performance degradation caused by delayed fault detection in traditional control systems. The self-repair module can start quickly after a fault occurs, automatically adjust control parameters or take repair measures to ensure that the solenoid valve can resume normal operation in the shortest possible time.

[0036] (2) Improve system reliability: By introducing adaptive PID control and fuzzy control algorithms, the solenoid valve can intelligently adjust its working parameters when facing complex working conditions, thereby improving the stability and reliability of the system under uncertain and variable working conditions.

[0037] (3) Reduced maintenance costs and downtime: Since this application has a self-repair function, the failure of the solenoid valve can be repaired in time in the early stage, reducing the reliance on manual maintenance, reducing equipment downtime and maintenance costs, and improving the overall operating efficiency of the system.

[0038] (4) Intelligent adaptive control: By combining machine learning and pattern recognition technology, this application can not only effectively detect faults, but also dynamically adjust the control strategy according to different working conditions, thereby improving the response speed and accuracy of the solenoid valve.

[0039] It should be noted that in the description of the embodiments of this application, the terms "front," "rear," "left," "right," "up," "down," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. The terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication between two elements. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific circumstances.

[0040] In summary, due to the adoption of the above technical features, the present invention has the following advantages and positive effects compared with the prior art: First, this application overcomes the problem that traditional control systems cannot repair faults in real time by introducing intelligent diagnostic and self-repair control technologies; Second, this application ensures that the solenoid valve always maintains optimal operating condition under complex working conditions.

[0041] The preferred embodiments of the invention are merely illustrative of the invention. They do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. These embodiments have been selected and specifically described in this specification to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to make good use of the invention. The invention is limited only by the claims and their full scope and equivalents. The above disclosures are merely preferred embodiments of the invention, but are not intended to limit it. Any equivalent changes and modifications made by those skilled in the art without departing from the spirit and essence of the invention should fall within the protection scope of the invention.

Claims

1. A self-diagnostic and self-repair control system for an electromagnetic valve, characterized in that, The system includes: Data acquisition module: The data acquisition module includes a sensor group and data preprocessing. The sensor group includes a current sensor, a pressure sensor, a temperature sensor, and a position sensor. The working signal of the solenoid valve is acquired in real time through the sensor group. The data from the sensor group is first filtered, noise and abnormal data are removed through the data preprocessing. Fault diagnosis module: The fault diagnosis module performs fault diagnosis. During the diagnosis process, the fault diagnosis module receives input from the sensor group and compares the historical data and normal operating data of the solenoid valve. Through data fusion technology, a neural network is used to diagnose the potential fault types of the solenoid valve. Decision and Repair Module: Includes a self-repair module and a control system module, wherein, Self-repair module: When the fault diagnosis module confirms the existence of a fault, the self-repair module automatically triggers the self-repair strategy; Control system module: Based on the fault diagnosis results and self-repair strategy, the control system module dynamically adjusts the working control strategy of the solenoid valve; the control system module uses a feedback control algorithm to ensure that the solenoid valve always remains in the optimal working state by adjusting the control signal in real time.

2. The solenoid valve self-diagnosis and self-repair control system as described in claim 1, characterized in that, The system also includes: Execution module: includes a solenoid valve actuator, which performs continuous and reliable operation of the solenoid valve; Data transmission module: The data acquisition module, the fault diagnosis module, the decision-making and repair module, and the execution module exchange data through the industry standard communication protocol of the data transmission module; the data transmission module ensures the real-time performance and stability of the data acquisition module, the fault diagnosis module, the decision-making and repair module, and the execution module.

3. The solenoid valve self-diagnosis and self-repair control system as described in claim 2, characterized in that, The sensor group includes a current sensor, a pressure sensor, a temperature sensor, and a position sensor.

4. The solenoid valve self-diagnosis and self-repair control system as described in claim 3, characterized in that, The self-repair control strategy employs an adaptive PID control algorithm, the formula of which is: Wherein, the current error of the solenoid valve is e(t), and the system's repair control signal is u(t). These are the proportional, integral, and differential gain coefficients, respectively, and e(t) is the error signal of the solenoid valve.

5. The solenoid valve self-diagnosis and self-repair control system as described in claim 4, characterized in that, The system employs fuzzy control to address the nonlinearity issues in solenoid valve control; the fuzzy control algorithm uses fuzzy inference formulas for decision-making. Where e(t) is the current error, Δe(t) is the rate of change of the error, and f is the fuzzy inference function.

6. The solenoid valve self-diagnosis and self-repair control system as described in claim 5, characterized in that, The adaptive PID control algorithm and fuzzy control algorithm are used to enable the solenoid valve to intelligently adjust its operating parameters when facing complex working conditions.

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