The electric actuator's fault diagnosis based on date fusion technology

Abstract

The application of multisensor data fusion is more useful than the single sensor when describing, analyzing, and processing the system's question; it can deal with various uncertainty relationship and the relation among various data sources. This chapter takes the electric actuator as the research object, and puts forward a kind of fault diagnosis method called fusion fault diagnosis method. The two-step fusion diagnosis model of neural network and Dempater–Shafer (D–S) Evidence Theory is given against the complexity and multiplicity when the fault of control system happens; the fault detection laboratory platform is erected based on the data fusion through the analysis of the electric actuator's principle and typical faults, and on this basis, the fault of the electric actuator is diagnosed by the experiment and computer simulation. This method overcomes the uncertainty of the neural network fault diagnosis and improves the accuracy of system diagnosis. The experiment result verifies the method's validity.