Research on the Method of Rotary Machinery Fault Diagnosis based on PCA and DBN
In: IOP Conference Series: Materials Science and Engineering, Jg. 1043 (2021), Heft 2, S. 022044
academicJournal
Zugriff:
Aiming at the difficulty of complex vibration signal transmission path, great influence of different sensor positions on diagnosis results and difficulty in feature extraction of rotary machinery fault diagnosis, a new fault diagnosis method based on Principal Component Analysis (PCA) and Deep Belief Network (DBN) is proposed. The framework of the method is constructed. The theory of PCA and DBN are introduced. And the validity and superiority of the proposed method are verified by the experimental data of typical rotary machinery.
Titel: |
Research on the Method of Rotary Machinery Fault Diagnosis based on PCA and DBN
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Autor/in / Beteiligte Person: | Li, H P ; Qi, Zh L ; Hu, J P ; Zhang, X Y |
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Zeitschrift: | IOP Conference Series: Materials Science and Engineering, Jg. 1043 (2021), Heft 2, S. 022044 |
Veröffentlichung: | IOP Publishing, 2021 |
Medientyp: | academicJournal |
ISSN: | 1757-8981 |
DOI: | 10.1088/1757-899x/1043/2/022044 |
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