As the core component of hydraulic control system, servo valve is widely used in aerospace, industrial automation, robot control and other fields. Its working state directly affects the control accuracy and stability of the system. In order to improve the reliability of the system and carry out fault diagnosis research, the fault simulation technology of servo valve has gradually become a research hotspot. This paper will discuss the realization method of servo valve fault simulation.
A, servo valve fault type analysis
Before fault simulation, it is necessary to make clear the common fault modes of servo valves. Mainly includes:
1. Mechanical sticking: the valve core is slow or stuck due to wear, impurity blockage or poor lubrication.
2. Leakage fault: internal leakage or external leakage causes system pressure drop and response delay.
3. Electrical failure: the coil is open-circuited, short-circuited or the input signal is abnormal, resulting in control failure.
4. Hysteresis and deterioration of nonlinear characteristics: the dynamic response of the servo valve becomes worse due to material fatigue or wear.
Second, the basic method of fault simulation
1. Physical simulation method
Physical simulation is to observe the influence on the system performance by artificially introducing faults (such as adding impurities and changing electrical parameters) in the actual servo valve. This method is intuitive and true, but there are some problems such as complicated operation, high cost and poor repeatability.
2. Mathematical modeling and simulation
Using MATLAB/Simulink, AMESim and other simulation software, the dynamic model of servo valve is established, and various fault parameter changes are introduced into the model, such as changing flow gain, adding dead zone and increasing leakage coefficient, so as to simulate the fault state. This method has the advantages of low cost, strong repeatability and easy analysis, and is the main research direction at present.
3. Data driven simulation
Machine learning models (such as neural network and support vector machine) are trained based on historical fault data, and virtual fault simulation is realized by simulating the input-output relationship in different fault states. This method is suitable for the reproduction of complex nonlinear behavior, especially when there is no accurate mathematical model.
Three, the key technology of fault simulation
1. High modeling accuracy is required: the servo valve is an electromechanical and hydraulic integrated element, and many coupling factors such as electromagnetism, machinery and fluid should be considered in modeling, and the accuracy of the model directly affects the authenticity of fault simulation.
2. Fault parameter setting: It is necessary to reasonably set the fault type and its parameter variation range according to the actual fault statistical data to ensure that the simulation results are close to reality.
3. Fault injection mechanism: Especially in the simulation system, how to design the fault injection module and realize the flexible control of fault occurrence time, type and intensity is a key technology.
Iv. application and prospect
Servo valve fault simulation can provide basic data for the development of fault diagnosis algorithm, which is helpful to improve the fault tolerance and maintenance efficiency of the system. In the future, with the development of digital twin technology and artificial intelligence, the intelligent fault simulation of servo valve will become possible, and the transition from “post-fault diagnosis” to “pre-fault prediction” will be realized.
tag
To sum up, servo valve fault simulation is an important means to ensure the reliability of hydraulic system. Combining physical experiment, mathematical modeling and data analysis, all kinds of fault states can be simulated comprehensively and efficiently, which lays a solid foundation for subsequent fault diagnosis and system optimization. With the continuous progress of related technologies, servo valve fault simulation will develop towards higher precision and stronger intelligence.