Research on health assessment method for power supply element of avionics electronic

Power module is the core component of the integrated modular avionics system, which directly affects the reliability and stability of the integrated avionics system. Prognostics and Health Management (PHM) technique is proposed and used to solve the problem of fault diagnosis and failure prediction for key components of power module. However, the predicted values of the characteristic parameters obtained by the prediction algorithm such as support vector machine and Gaussian regression algorithm can't directly reflect the health status of the analog circuitry. In this paper a general health assessment method for power module is proposed. By using statistical analysis and wavelet packet decomposition, fault feature is extracted. Through process of principal component analysis, dimensionality of feature vector is reduced. Then employing the average Euclidean distance evaluates the health status of the power module. We take the power supply element in avionics system as an example, using the method above which successfully realizes converting the slight change process in the early fault to an obvious change in Euclidean distance. And the size of Euclidean distance is applied to evaluate the health status of the power supply element.