A Low-Power Hierarchical CNN Hardware Accelerator for Bearing Fault Diagnosis

Author:

Liang Yu-Pei1ORCID,Hsu Yao-Shun1ORCID,Chung Ching-Che1ORCID

Affiliation:

1. Department of Computer Science and Information Engineering, Advanced Institute of Manufacturing With High-Tech Innovations, National Chung Cheng University, Chiayi, Taiwan

Funder

Ministry of Science and Technology of Taiwan

Advanced Institute of Manufacturing with High-tech Innovations

Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Reference28 articles.

1. Condition monitoring of bearing damage in electromechanical drive systems by using motor current signals of electric motors: A benchmark data set for data-driven classification;Lessmeier

2. A new rotating machinery fault diagnosis method based on the time series transformer;Jin;arXiv:2108.12562,2021

3. Performance of Envelope Demodulation for Bearing Damage Detection on CWRU Accelerometric Data: Kurtogram and Traditional Indicators vs. Targeted a Posteriori Band Indicators

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