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| Presentation | 2021-12-03 13:00 [Tutorial Lecture] A study of anomalous sound detection using autoencoder for quality determination and condition diagnosis Takashi Sudo, Yasuhiro Kanishima, Hiroyuki Yanagihashi (Toshiba)  SIS2021-25 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In the quality inspection of the product manufacture in a mass-production line or the apparatus preservation for production facility, the inspectors or maintenance staff hear with their ears a sound of operation which occurs from a subject of inspection, and quality judging or state diagnosis is performed to depend on experience or intuition. To save manpower and improve the accuracy of the inspection, anomalous sound detection which performs quality judging or state diagnosis by unsupervised learning using autoencoder which inputted the sound signal acquired by acoustic sensor (microphone) and edge device is studied. The combination of two kinds of objective of detection and two kinds of sound of operation can divide roughly the problem setup of anomalous sound detection into four patterns. Two kinds of objective of detection are detection of sudden anomaly in quality judging of the product manufacture and early detection of deterioration in state diagnosis of production facility. Two kinds of sound of operation are stationary operational sound and non-stationary operational sound. In a quality judging for non-stationary operational sound, this lecture introduces a convolutional autoencoder with a segmentation method that detects the section in which the device operates from the sound signal using trigger detection and template matching detection to improve an accuracy and reduce computational load. In addition, this lecture introduces a noise-robust learning method of distinguishing between deterioration-related sounds and normal sounds for a variational autoencoder to early detect deterioration trends of operating sound. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | anomalous sound detection / autoencoder / detection of sudden anomaly / detection of deterioration / segmentation / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 284, SIS2021-25, pp. 20-25, Dec. 2021. | |
| Paper # | SIS2021-25 | |
| Date of Issue | 2021-11-26 (SIS) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | SIS2021-25 |
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| Conference Information | |
| Committee | SIS |
| Conference Date | 2021-12-03 - 2021-12-03 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SIS |
| Conference Code | 2021-12-SIS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A study of anomalous sound detection using autoencoder for quality determination and condition diagnosis |
| Sub Title (in English) | |
| Keyword(1) | anomalous sound detection |
| Keyword(2) | autoencoder |
| Keyword(3) | detection of sudden anomaly |
| Keyword(4) | detection of deterioration |
| Keyword(5) | segmentation |
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| Keyword(8) | |
| 1st Author's Name | Takashi Sudo |
| 1st Author's Affiliation | Toshiba Corporation (Toshiba) |
| 2nd Author's Name | Yasuhiro Kanishima |
| 2nd Author's Affiliation | Toshiba Corporation (Toshiba) |
| 3rd Author's Name | Hiroyuki Yanagihashi |
| 3rd Author's Affiliation | Toshiba Corporation (Toshiba) |
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| Speaker | Author-1 |
| Date Time | 2021-12-03 13:00:00 |
| Presentation Time | 40 minutes |
| Registration for | SIS |
| Paper # | SIS2021-25 |
| Volume (vol) | vol.121 |
| Number (no) | no.284 |
| Page | pp.20-25 |
| #Pages | 6 |
| Date of Issue | 2021-11-26 (SIS) |
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