A Comprehensive Evaluation Approach to Aviation Maintenance Support Ability Based on PCA

Abstract

Principal component analysis (PCA) is a multivariate statistical method for reducing dimensionality by using the correlation between the original variables and interpreting the original variables through a few linear combinations of the original variables. As one of most important statistical methods, PCA can not only turn many index questions into less overall targets, but also provide the comparatively objective weight. The aircraft state index is the important parameter to measure the aviation maintenance support capability. It is indispensable to scientifically analyze aircraft state index data and to make scientific decisions on aviation maintenance to improve maintenance support capability. This paper discusses on multivariate evaluation method of aviation maintenance support ability using PCA. The mathematic model and algorithm steps of PCA method are given in detail. The application of PCA in aircraft integrated condition assessment is analyzed by an example. And the results show that the PCA-based method is effective for the comprehensive evaluation of the aviation maintenance support ability.