WCSE

Application of Principal Component Analysis to Aircraft Integrated Condition Monitoring and Assessment

Abstract— Principal component analysis (PCA) is a multivariate statistics technique that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. The aircraft integrated condition index is the important parameter to measure the aviation maintenance support capability. It is indispensable to scientifically analyze aircraft condition index data and to make scientific decisions on aviation maintenance to improve maintenance support capability. Aircraft integrated condition involves a large number of indexes, which is more difficult to monitor and evaluate. This paper presents a method of aircraft integrated condition monitoring and evaluation based on principal component analysis model, then gives its mathematic model and algorithm steps in detail. This method integrates multiple indexes by principal component analysis, uses the cumulative variance contribution rate to identify the principal component variables, and turns many index questions into less overall targets. To extract the most important information from the original data eliminates the information redundancy between the samples, and reduces the index dimension, so that the aircraft integrated condition monitoring and evaluation problems are simplified. The practical applications and results analysis show that the PCA-based method is feasible and effective for aircraft integrated condition monitoring and assessment.

Index Terms— principal component analysis, aircraft integrated condition, monitoring and assessment, eigenvector and eigenvalue

Yanming Yang, Youbao Ding
Qingdao Campus, Naval Aeronautical and Astronautical University, CHINA
Yingjian Liu
Department of Computer Science and Technology, Ocean University of China, CHINA

ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.17Xsrc="http://www.wcse.org/uploadfile/2019/0823/20190823055609629.png" style="width: 120px; height: 68px;" />[Download]

Cite: Yanming Yang, Yingjian Liu, Youbao Ding, "Application of Principal Component Analysis to Aircraft Integrated Condition Monitoring and Assessment," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 1124-1128, Beijing, 25-27 June, 2017.