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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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| Vydáno v: | Sensors (Basel) |
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| Hlavní autoři: | , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
MDPI
2019
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| Témata: | |
| On-line přístup: | 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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