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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 / / /  
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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) 
Topics (in Japanese) (See Japanese page) 
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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)  
Keyword(1) IoT  
Keyword(2) Ultrasonic Waves  
Keyword(3) Anomaly Detection  
Keyword(4) File Compression  
Keyword(5) 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  
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 2022-10-31 10:30:00 
Presentation Time 45 minutes 
Registration for RISING 
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