Health monitoring using support vector classification on an Auxiliary Power Unit

Abstract

Health monitoring has the challenge of monitoring the life of equipment and systems. To determine the health of systems and equipments, it is necessary to have an indication of the current state of the equipment and a health reference indicator. Often, such health reference indicator does not exist or it is not available to estimate the equipment's remaining useful life (RUL). This article presents a methodology that defines the equipment's health reference indicator using a data-driven classification technique and produces a degradation model to be used by the aircraft health monitoring systems. A One-Class Classifier based on Support Vector Machines estimates the region of nominal operation mode and detects abnormal behaviors that can characterize incipient failures. A dataset was collected during the operation of an aircraft Auxiliary Power Unit (APU) and it was used for testing the proposed methodology.