Bearing life prediction based on vibration signals: A case study and lessons learned

This paper presents the Professional-category winning algorithm of bearing Remaining Useful Life (RUL) prediction for the 2012 IEEE PHM challenge problem. The algorithm consists of extraction of bearing characteristic frequency features with envelop analysis, fault detection with PCA, and two RUL prediction strategies to address the scenarios when the bearing faults have and have not been detected. The paper will go through various aspects to investigate the challenge problem, synthesize modeling strategies, and summarize the lessons learned from this bearing life prediction case study.