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| Presentation | 2022-09-16 15:45 Study of Data Collection System for Ultrasonic Waves Based Anomaly Detection of Mechanical Equipment Rio Shigyo, Daiki Nobayashi, Kazuya Tsukamoto, Mitsunori Mizumachi, Takeshi Ikenaga (KIT)  IA2022-32 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Status checks of mechanical equipment are typically being conducted by workers (manpower). However, since the check timing is limited (i.e., periodic check), the delay of anomaly detection could be the check interval at the maximum. Furthermore, the financial cost and the effort could be extremely high. Since some abnormalities typically appear in the operating sound, we have proposed an IoT system that collects the operating sound automatically for anomaly detection. However, its detection performance could be degraded where the environmental noises (e.g., bird call and car engines) generated around the equipment are mixed with the operation sound. In this paper, we focus on the ultrasonic component whose frequency is higher than that of the audible sound and propose a new system that collects the ultrasonic data effectively. Through experiments, we demonstrated that the ultrasonic components appears in the operating sounds, irrespective of the environmental noise and their data can be effectively abstracted by utilizing filters and be decreased by FLAC compression technology. Finally, we have shown that it may be possible to estimate the operating status based on the amount of the compressed data size. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | IoT / Ultrasonic Waves / Anomaly Detection / File Compression / Data Transfer / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 185, IA2022-32, pp. 97-102, Sept. 2022. | |
| Paper # | IA2022-32 | |
| Date of Issue | 2022-09-08 (IA) | |
| 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 | IA2022-32 |
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| Conference Information | |
| Committee | IA CQ MIKA |
| Conference Date | 2022-09-15 - 2022-09-16 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hokkaido Citizens Actives Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Wireless Communications Quality, 6G, IoT, Cross layer Technologies, Internet Operation and Management, etc. |
| Paper Information | |
| Registration To | IA |
| Conference Code | 2022-09-IA-CQ-MIKA |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Study of Data Collection System for Ultrasonic Waves Based Anomaly Detection of Mechanical Equipment |
| Sub Title (in English) | |
| Keyword(1) | IoT |
| Keyword(2) | Ultrasonic Waves |
| Keyword(3) | Anomaly Detection |
| Keyword(4) | File Compression |
| Keyword(5) | Data Transfer |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Rio Shigyo |
| 1st Author's Affiliation | Kyushu Institute of Technology (KIT) |
| 2nd Author's Name | Daiki Nobayashi |
| 2nd Author's Affiliation | Kyushu Institute of Technology (KIT) |
| 3rd Author's Name | Kazuya Tsukamoto |
| 3rd Author's Affiliation | Kyushu Institute of Technology (KIT) |
| 4th Author's Name | Mitsunori Mizumachi |
| 4th Author's Affiliation | Kyushu Institute of Technology (KIT) |
| 5th Author's Name | Takeshi Ikenaga |
| 5th Author's Affiliation | Kyushu Institute of Technology (KIT) |
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| Speaker | Author-1 |
| Date Time | 2022-09-16 15:45:00 |
| Presentation Time | 25 minutes |
| Registration for | IA |
| Paper # | IA2022-32 |
| Volume (vol) | vol.122 |
| Number (no) | no.185 |
| Page | pp.97-102 |
| #Pages | 6 |
| Date of Issue | 2022-09-08 (IA) |
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