Deep Sparse Representation Classification for Aeroengine Inter-shaft Bearing Fault Diagnosis

Renhe Yao, Hongkai Jiang, Yunpeng Liu, Xin Wang, Haidong Shao, Wenxin Jiang

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

Fault diagnosis of aero-engine inter-shaft bearing under variable operating conditions poses a significant challenge in the industry. Existing sparse classification methods with shallow architectures suffer from insufficient fault feature extraction and interference removal capabilities with limited training samples, resulting in low diagnostic accuracies. To address this issue, this study introduces an approach termed deep sparse representation classification (DSRC). DSRC seamlessly integrates multiple layers for dictionary learning and sparse coding. In the initial phase, the dictionary learning layer is employed to acquire the Fisher discriminative sparse representation information, while the sparse coding layer is utilized to eliminate interfering components and simultaneously enhance sparsity. The incorporation of a weight matrix, guided by a high-energy atom selection strategy, links the upward and downward processes of dictionary learning and sparse coding. Subsequently, the frequency-weighted energy operator kurtosis-based feature vectors are extracted from the reconstructed signals of the newly acquired dictionary and coding coefficients. Ultimately, these discriminative feature vectors are directly input into a straightforward classifier for intelligent fault diagnosis. DSRC is applied to an aero-engine inter-shaft bearing fault data under multiple speeds. Results demonstrate that it can effectively realize discriminative fault feature extraction and high-precision automatic fault identification.

源语言英语
主期刊名2024 IEEE International Conference on Prognostics and Health Management, ICPHM 2024
出版商Institute of Electrical and Electronics Engineers Inc.
167-173
页数7
ISBN(电子版)9798350374476
DOI
出版状态已出版 - 2024
活动2024 IEEE International Conference on Prognostics and Health Management, ICPHM 2024 - Spokane, 美国
期限: 17 6月 202419 6月 2024

出版系列

姓名2024 IEEE International Conference on Prognostics and Health Management, ICPHM 2024

会议

会议2024 IEEE International Conference on Prognostics and Health Management, ICPHM 2024
国家/地区美国
Spokane
时期17/06/2419/06/24

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