Paper Abstract and Keywords |
Presentation |
2022-10-31 10:30
[Poster Presentation]
Study of Data Collection System for Anomaly Detection by Ultrasonic Components of Mechanical Equipment Operating Sounds Rio Shigyo, Daiki Nobayashi, Kazuya Tsukamoto, Mitsunori Mizumachi, Takeshi Ikenaga (KIT) |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Status checks of mechanical equipment are typically being conducted by workers (manpower) at the actual place. 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, outdoor operating sounds have the problem of containing various noises in the audible range (e.g., bird call and car engines). In this paper, we avoid audible noise and 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. |
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Conference Information |
Committee |
RISING |
Conference Date |
2022-10-31 - 2022-11-02 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Kyoto Terrsa (Day 1), and Online (Day 2, 3) |
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Paper Information |
Registration To |
RISING |
Conference Code |
2022-10-RISING |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Study of Data Collection System for Anomaly Detection by Ultrasonic Components of Mechanical Equipment Operating Sounds |
Sub Title (in English) |
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IoT |
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Ultrasonic Waves |
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Anomaly Detection |
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File Compression |
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Data Transfer |
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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 |
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Kyushu Institute of Technology (KIT) |
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Takeshi Ikenaga |
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Kyushu Institute of Technology (KIT) |
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Author-1 |
Date Time |
2022-10-31 10:30:00 |
Presentation Time |
45 minutes |
Registration for |
RISING |
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