Assessment of rolling element bearing degradation based on Dynamic Time Warping, kernel ridge regression and support vector regression

• Published in: Applied acoustics Vol. 208; p. 109389
• Main Authors: Kumar, Prem Shankar, Laha, S.K., Kumaraswamidhas, L.A.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.06.2023
• Subjects: Confidence value (CV); Degradation assessment; Dynamic Time Warping (DTW); Kernel Ridge Regression (KRR); Rolling Element Bearings; Rolling Element Bearings; Dynamic Time Warping (DTW); Confidence value (CV); Kernel Ridge Regression (KRR); Degradation assessment
• ISSN: 0003-682X; 1872-910X
• DOI: 10.1016/j.apacoust.2023.109389

[Display omitted] •A novel health indicator based on Dynamic Time Warping (DTW) is proposed for bearing degradation trend estimation.•Four degradation stages are recognized by using the CV and CV change rate.•Prediction of degradation trend is based on DTW-KRR and DTW-SVR.•Performance of DTW-KRR and DTW-SVR prediction are efficiently estimated by accuracy based metrics. An accurate and reliable forecast for fault/degradation trend has an enormous significance in predictive maintenance of industrial systems. Prognosis of bearing is essential for efficient implementation of condition based maintenance of rotating machinery to prevent sudden/unexpected breakdown. The Dynamic Time Warping (DTW) algorithm is proposed for the first time for bearing prognosis assessment and health trend prediction of rolling element bearing. The Dynamic Time Warping based value is then applied to obtain a Confidence Value (CV) to standardize the degradation process. The range of the parameter CV is zero to unity. The various degradation stages are recognized by using CV and the fault frequencies are obtained from the envelop spectrum. Further, the Kernel Ridge Regression (KRR) and Support Vector Regression (SVR) methodologies are applied on the DTW feature to forecast the bearing degradation trend. The effectiveness of DTW-KRR and DTW-SVR is analyzed by various accuracy metrics. The present study shows that the DTW and DTW-SVR are effective tools for bearing health degradation assessment and prognosis of rolling element bearing.