Electric and Hydraulic Servo Actuator Fault Diagnosis Based on Genetic Optimization Neural Network

Abstract

To resolve the complexity and uncertainty between the fault portent and the causes of electric and hydraulic actuator, a fault diagnosis model base on neural network arithmetic for actuator is designed. The genetic optimization arithmetic is used to initialize the value of weight and bias to improve the search efficiency and global convergence of the network. The simulation result indicate the feasibility and validity of the method based on genetic neural network model to diagnose the faults of electric and hydraulic servo actuator.