Keywords: sustainable manufacturing, product take-back, product reuse, remaining useful life, lifetime prediction, prognostics, condition monitoring, vibration analysis, washing machines, electric motors, constant percentage bandwidth, cepstrum analysis, envelope cepstrum, Weibull analysis, neural networks
Vibration-based approach to lifetime prediction of electric motors for reuse
This paper is concerned with lifetime prediction of components in washing machines. Vibration signals were measured on electric motors during an accelerated lifetime test ranging from 26.7 to 38.5 simulated years. Loose bearings have initiated air-gap eccentricity and rotor-to-stator rubbing, which resulted in a motor breakdown. Significant frequency bands were identified using a spectral comparison based on the constant percentage bandwidth (CPB) spectrum. Increasing trends were extracted from several vibration indicators, such as envelope cepstrum (EC) and a weighted integral of CPB differences. The EC is computed as the real cepstrum of the envelope signal obtained by demodulating the band identified by the CPB comparison. Hence the EC is more sensitive as it employs a priori information provided by historical data. The fault was first detected 9.7 years in advance and confirmed 5.3 years before the breakdown. The indicators can be integrated with a recent methodology based on Weibull analysis and neural network modelling.