Journal
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 65, Issue 9, Pages 2046-2054Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2016.2570398
Keywords
Anomaly detection; bearing; extended Kalman filter (EKF); fault prognosis; remaining useful life (RUL); vibrational signal
Funding
- National Natural Science Foundation of China [51505424, 51275474]
- Zhejiang Provincial Natural Science Foundation of China [LY15E050019, LZ12E05002]
- Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China [ICT1443]
Ask authors/readers for more resources
In this paper, a new bearing anomaly detection and fault prognosis method is proposed. The method detects bearing anomalies and then predicts its remaining useful life (RUL). To achieve these two goals, an autoregressive model, which is used to filter out fault-unrelated signals, is derived according to healthy bearing vibrational signals. A health index is developed to indicate bearing health conditions. Anomalies of bearings are detected by choosing an appropriate threshold with the aid of a Box-Cox transformation. A nonlinear model is built to track the bearings' degradation process and an extended Kalman filter is designed to model adaptation and RUL prediction. Finally, PRONOSTIA bearing data are used to demonstrate the effectiveness of the proposed method.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available