A Novel Method for Remaining Useful Life Prediction of Bearing Based on Spectrum Image Similarity Measures

Abstract

Accurately predicting the remaining useful life (RUL) of bearing by analyzing vibration signals is challenging and meaningful. To address this issue, a novel method based on spectrum image similarity is proposed in this paper. First, spectrum images for the whole lifecycle data of reference bearings are obtained by performing fast Fourier transformation (FFT). Second, the similarity is calculated between the current monitored data of operating bearing and run-to-failure images of reference bearings. Then, the weights of reference bearings are derived based on the similarity measures. Finally, the RUL of the operating bearing is estimated with the weighted average of the RULs of referenced bearings. The proposed method is demonstrated based on 2012 PHM Data Challenge Competition data, which shows its effectiveness and practicality.