DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yi, Wonjun | ko |
dc.contributor.author | Choi, Jung-Woo | ko |
dc.date.accessioned | 2022-11-01T13:00:32Z | - |
dc.date.available | 2022-11-01T13:00:32Z | - |
dc.date.created | 2022-10-28 | - |
dc.date.issued | 2022-10-25 | - |
dc.identifier.citation | 24th International Congress on Acoustics, ICA 2022 | - |
dc.identifier.uri | http://hdl.handle.net/10203/299224 | - |
dc.description.abstract | In-situ classification of faulty sounds is an important issue in machine health monitoring and diagnosis. However, in a noisy environment such as a factory, machine sound is always mixed up with environmental noises, and noise-only periods can exist when a machine is not in operation. Therefore, a deep neural network (DNN)-based fault classifier has to be able to distinguish noise from machine sound and be robust to mixed noises. To deal with these problems, we investigate on-site noise exposure (ONE) that exposes a DNN model to the noises recorded in the same environment where the machine operates. Like the outlier exposure technique, noise exposure trains a DNN classifier to produce a uniform predicted probability distribution against noise-only data. During inference, the DNN classifier trained by ONE outputs the maximum softmax probability as the noise score and determines the noise-only period. We mix machine sound and noises of the ToyADMOS2 dataset to simulate highly noisy data. A ResNet-based classifier trained by ONE is evaluated and compared with those trained by other out-of-distribution detection techniques. The test results show that exposing a model to on-site noises can make a model more robust than using other noises or detection techniques. | - |
dc.language | English | - |
dc.publisher | International Commission for Acoustics | - |
dc.title | On-site Noise Exposure technique for noise-robust machine fault classification | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 24th International Congress on Acoustics, ICA 2022 | - |
dc.identifier.conferencecountry | KO | - |
dc.identifier.conferencelocation | Hwabaek International Convention Center | - |
dc.contributor.localauthor | Choi, Jung-Woo | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.