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A Lighted Deep Convolutional Neural Network Based Fault Diagnosis of Rotating Machinery
To improve the fault diagnosis performance for rotating machinery, an efficient, noise-resistant end-to-end deep learning (DL) algorithm is proposed based on the advantages of the wavelet packet transform in vibration signal processing (the capability to extract multiscale information and more spect...
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| Pubblicato in: | Sensors (Basel) |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6566980/ https://ncbi.nlm.nih.gov/pubmed/31137616 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19102381 |
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