| アイテムタイプ |
学術雑誌論文 = Journal Article(1) |
| 公開日 |
2024-01-12 |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| タイトル |
|
|
タイトル |
Study of Ultrasonic Data Collection System for Anomaly Detection for Mechanical Equipment |
|
言語 |
en |
| その他のタイトル |
|
|
その他のタイトル |
Study of Ultrasonic Data Collection System for Anomaly Detection on Mechanical Equipment |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 著者 |
Shigyo, Rio
野林, 大起
塚本, 和也
水町, 光徳
池永, 全志
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
loT-based acoustic data collection systems have been proposed for detecting anomalies in equipment. However, such systems do not work well in outdoor environments due to interference caused by various sound sources (e.g., wildlife sounds and traffic noise). Outdoor noise has unique frequency characteristics, with energy localized in the low-frequency domain. In contrast, mechanical equipment such as motors mainly generates harmonics, including ultrasonic components, during operation. This paper proposes a noise-robust ultrasonic data collection system for outdoor use. To reduce the size of collected data, which increases in proportion to the sampling frequency, the proposed system uses bandpass filtering and data compression. |
|
言語 |
en |
| 備考 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
The 2022 International Conference on Computational Science and Computational Intelligence (CSCI 2022), December 14-16, 2022, Las Vegas, USA |
|
言語 |
en |
| 書誌情報 |
en : 2022 International Conference on Computational Science and Computational Intelligence (CSCI)
p. 1237-1238,
発行日 2023-08-25
|
| 出版社 |
|
|
出版者 |
IEEE |
| DOI |
|
|
関連タイプ |
isVersionOf |
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1109/CSCI58124.2022.00222 |
| ISSN |
|
|
収録物識別子タイプ |
EISSN |
|
収録物識別子 |
2769-5654 |
| ISSN |
|
|
収録物識別子タイプ |
PISSN |
|
収録物識別子 |
2769-5670 |
| 著作権関連情報 |
|
|
権利情報 |
Copyright (c) 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
loT |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Ultrasonic Anomaly Detection |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Noise Robustness |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
File Compression |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
Data Transfer |
| 会議記述 |
|
|
|
会議名 |
The 2022 International Conference on Computational Science and Computational Intelligence (CSCI 2022) |
|
|
言語 |
en |
|
|
開始年 |
2022 |
|
|
開始月 |
12 |
|
|
開始日 |
14 |
|
|
終了年 |
2022 |
|
|
終了月 |
12 |
|
|
終了日 |
16 |
|
|
開催地 |
Las Vegas |
|
|
言語 |
en |
|
開催国 |
USA |
| 出版タイプ |
|
|
出版タイプ |
AM |
|
出版タイプResource |
http://purl.org/coar/version/c_ab4af688f83e57aa |
| 査読の有無 |
|
|
値 |
yes |
| 研究者情報 |
|
|
URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/81_ja.html |
csci2022-cr-shigyo.pdf (569 KB)
