The research of spacecraft electrical characteristics identification and diagnosis using PCA feature extraction

Abstract

As most electronic system structure is complex and uncertain, this paper presents a new efficiency method for spacecraft electrical characteristics identification. PCA (Principal Component Analysis) feature extraction, offline FCM (Fuzzy C-means) clustering and online SVM (Support Vector Machine) classifier is introduced into the registration model. At first step of the algorithm, get an expert training set by FCM clustering method, then using PCA feature extraction to get principal component. After get expert training set and using PCA feature extraction for SVM classifier make this method fast and effective. These are the foundation of online spacecraft electrical characteristics identification. A series of spacecraft electrical characteristics data demonstrate that the proposed method is more accuracy than the traditional way.