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| Presentation | 2018-03-20 09:00 [Poster Presentation] Anomaly Detection by Reconstructing Features from Subsampled Audio Signals Yohei Kawaguchi (Hitachi)  EA2017-161 SIP2017-170 SP2017-144 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We aim to reduce the cost of sound monitoring for maintain machinery by reducing the sampling rate, i.e., sub-Nyquist sampling. Monitoring based on sub-Nyquist sampling requires two sub-systems: a sub-system on-site for sampling machinery sounds at a low rate and a sub-system off-site for detecting anomalies from the subsampled signal. This paper proposes a feature reconstruction method for enabling anomaly detection from the subsampled signal. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | machine condition monitoring / sub-Nyquist sampling / neural network / long short-term memory (LSTM) / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 516, SIP2017-170, pp. 323-327, March 2018. | |
| Paper # | SIP2017-170 | |
| Date of Issue | 2018-03-12 (EA, SIP, SP) | |
| ISSN | Print edition: ISSN 0913-5685 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 | EA2017-161 SIP2017-170 SP2017-144 |
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| Conference Information | |
| Committee | SIP EA SP MI |
| Conference Date | 2018-03-19 - 2018-03-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Speech, Engineering/Electro Acoustics, Signal Processing, and Related Topics [SIP, EA, SP]/ Medical Image Engineering, Analysis, Recognition, etc. [MI] |
| Paper Information | |
| Registration To | SIP |
| Conference Code | 2018-03-SIP-EA-SP-MI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Anomaly Detection by Reconstructing Features from Subsampled Audio Signals |
| Sub Title (in English) | |
| Keyword(1) | machine condition monitoring |
| Keyword(2) | sub-Nyquist sampling |
| Keyword(3) | neural network |
| Keyword(4) | long short-term memory (LSTM) |
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| 1st Author's Name | Yohei Kawaguchi |
| 1st Author's Affiliation | Hitachi, Ltd. (Hitachi) |
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| Speaker | Author-1 |
| Date Time | 2018-03-20 09:00:00 |
| Presentation Time | 90 minutes |
| Registration for | SIP |
| Paper # | EA2017-161, SIP2017-170, SP2017-144 |
| Volume (vol) | vol.117 |
| Number (no) | no.515(EA), no.516(SIP), no.517(SP) |
| Page | pp.323-327 |
| #Pages | 5 |
| Date of Issue | 2018-03-12 (EA, SIP, SP) |
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