Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression
Top Cited Papers
- 1 July 2014
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Instrumentation and Measurement
- Vol. 64 (1), 52-62
- https://doi.org/10.1109/tim.2014.2330494
Abstract
The detection, diagnostic, and prognostic of bearing degradation play a key role in increasing the reliability and safety of electrical machines, especially in key industrial sectors. This paper presents a new approach that combines the Hilbert-Huang transform (HHT), the support vector machine (SVM), and the support vector regression (SVR) for the monitoring of ball bearings. The proposed approach uses the HHT to extract new heath indicators from stationary/nonstationary vibration signals able to tack the degradation of the critical components of bearings. The degradation states are detected by a supervised classification technique called SVM, and the fault diagnostic is given by analyzing the extracted health indicators. The estimation of the remaining useful life is obtained by a one-step time-series prediction based on SVR. A set of experimental data collected from degraded bearings is used to validate the proposed approach. The experimental results show that the use of the HHT, the SVM, and the SVR is a suitable strategy to improve the detection, diagnostic, and prognostic of bearing degradation.Keywords
Funding Information
- European Regional Development Fund through the MainPreSI Project within the framework of the European Territorial Cooperation Program
This publication has 29 references indexed in Scilit:
- Time-Frequency Manifold as a Signature for Machine Health DiagnosisIEEE Transactions on Instrumentation and Measurement, 2012
- Models for Bearing Damage Detection in Induction Motors Using Stator Current MonitoringIEEE Transactions on Industrial Electronics, 2008
- EMD-Based Signal FilteringIEEE Transactions on Instrumentation and Measurement, 2007
- Hilbert–Huang Transform-Based Vibration Signal Analysis for Machine Health MonitoringIEEE Transactions on Instrumentation and Measurement, 2006
- Wear detection in gear system using Hilbert-Huang transformJournal of Mechanical Science and Technology, 2006
- Three-phase Induction Motor Operation Trend Prediction Using Support Vector Regression for Condition-based MaintenancePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Knowledge-base system approach to power electronic systems fault diagnosisPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- AN ANALYTICAL MODEL FOR THE PREDICTION OF THE VIBRATION RESPONSE OF ROLLING ELEMENT BEARINGS DUE TO A LOCALIZED DEFECTJournal of Sound and Vibration, 1997
- Supervised neural networks for the classification of structuresIEEE Transactions on Neural Networks, 1997
- The Nature of Statistical Learning TheoryPublished by Springer Science and Business Media LLC ,1995