Title
New Condition-Based Monitoring and Fusion Approaches With a Bounded Uncertainty for Bearing Lifetime Prediction
Document Type
Article
Publication Date
5-1-2022
Publication Title
IEEE Sensors Journal
Volume
22
Issue
9
First Page
9078
Keywords
bearings, bounded uncertainty, Fusion approaches, lifetime prediction, wind farms
Last Page
9086
Abstract
Condition Monitoring (CM) is an essential element of securing reliable operating conditions of Wind Turbines (WT) in a wind farm. CM helps optimize maintenance by providing Remaining Useful Life (RUL) forecast. However, the expected RUL is not often reliable due to uncertainty associated with the prediction horizon. In this paper, we employ high-level fusion methods to expect the RUL of WT bearings. For this purpose, various features are extracted by vibration signals to capture deterioration paths. Then, a Bayesian algorithm is utilized to determine RUL for each selected feature. Eventually, high-level fusion schemes, including Hurwicz, Choquet integral, Ordered Weighted Averaging operator, are employed to integrate RUL numbers and lessen associated uncertainty in the prediction horizons. Besides, a pessimistic fusion strategy is driven to obtain a bounded uncertainty for the worst RUL prediction. The fusion methods are assessed by ten-year vibration signals of Canadian wind farms. Experimental results confirm accurate results with bounded uncertainty for high-level fusion approaches.
DOI
10.1109/JSEN.2022.3159624
ISSN
1530437X
E-ISSN
15581748
Recommended Citation
Kordestani, Mojtaba; Rezamand, Milad; Orchard, Marcos E.; Carriveau, Rupp; Ting, David S.K.; Rueda, Luis; and Saif, Mehrdad. (2022). New Condition-Based Monitoring and Fusion Approaches With a Bounded Uncertainty for Bearing Lifetime Prediction. IEEE Sensors Journal, 22 (9), 9078-9086.
https://scholar.uwindsor.ca/mechanicalengpub/62