A novel health indicator developed using filter-based feature selection algorithm for the identification of rotor defects

Anil Kumar, Gandhi Cp, Xiaoyang Liu, Yi Liu, Yuqing Zhou, Rajesh Kumar and Jiawei Xiang

Journal of Risk and Reliability, 2022, vol. 236, issue 4, 529-541

Abstract: In this work, a novel health indicator is developed for the identification of rotor defects. The indicator is developed by extracting features from vibration data acquired from horizontal and vertical directions of rotors. A total of 38 features were initially extracted from time-domain signal, frequency-domain signal, and time–frequency representation. Out of many features, six most important features were selected using filter-based feature selection process. Thereafter, important features were fused together using manifold learning to develop health indicator. The developed indicator is used to identify misalignments (angular misalignment and parallel misalignment), rub, and unbalance. The major benefit of the proposed method is that it not only indicates the presence of defect in the rotor but also indicates the severity of defect. The experimental study presented in this article justifies that the proposed method is sensitive to the increasing levels of horizontal and angular misalignment and unbalance. The developed indicator is sensitive enough to indicate the presence of rub.

Keywords: Health indicator; features selection; rotor defect; online-diagnostic; manifold learning (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:236:y:2022:i:4:p:529-541

DOI: 10.1177/1748006X20916953

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