Use of the Principal Component Analysis for Classification of Aircraft Components Failure Conditions Using Vibrodiagnostics

Abstract

Safety and trouble-free operation are important factors that places aviation among the safest forms of transport. These parameters are achieved mainly by state-of-the-art diagnostic and maintenance programs and methods, which are constantly evolving and increasing their efficiency. The manuscript is focused on the use of a centrifugal blower, on which fault states were artificially simulated and subsequently analyzed by statistical methods not normally used in the field of vibrodiagnostics. The use of principal component analysis (PCA) method played a key role in evaluating the vibrodiagnostic signal of the measured device. The PCA method enabled the categorization of fault conditions and provided a unique view of diagnostic methods with reference to specific signals. The results of the presented research indicate the potential of the PCA method in practice and in the need to carry out further research for other fault conditions. The implementation of such a tool is a prerequisite for more effective determination of specific fault conditions and the use of the PCA method in vibrodiagnostics not only in aviation but also in general industry.