April 23, 2024, 4:43 a.m. | Mingxuan Gao, Min Wang, Maoyin Chen

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.13941v1 Announce Type: cross
Abstract: Deep learning has shown the great power in the field of fault detection. However, for incipient faults with tiny amplitude, the detection performance of the current deep learning networks (DLNs) is not satisfactory. Even if prior information about the faults is utilized, DLNs can't successfully detect faults 3, 9 and 15 in Tennessee Eastman process (TEP). These faults are notoriously difficult to detect, lacking effective detection technologies in the field of fault detection. In this …

abstract amplitude arxiv autoencoder cs.ai cs.lg cs.sy current deep learning detection eess.sy ensemble feature however information networks performance power prior type

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