Bearing degradation prognosis using structural break classifier

Abstract

Prognostics based on machine condition monitoring data are one of the key elements of modern maintenance philosophies. Machinery health prognosis follows a sequential methodology inclusive of various processes ranging from data acquisition till remaining useful life estimation. Every step depicts distinct statistical features, which are helpful in estimating health state of a machine. In this investigation, bearing vibration data has been analyzed by utilizing the technique of structural break point regression. Constructed model is also employed to observe degradation of bearing in different regimes to estimate remaining useful life.