Presentation 2024-03-12
Data Analysis and Visualization Method for Equipment Anomaly Detection by Using Acoustic Data
Koichiro Kawano, Nobayashi Daiki, Tsukamo Kazuya, Mizumachi Mitsunori, Ikenaga Takeshi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Manual inspections of general equipment present many challenges in terms of manpower, time, and labor costs. In addition, the timing gap between inspections and breakdowns makes proper maintenance difficult, which can have a negative impact on the stable operation of equipment. In order to solve these problems, this study develops a system to record the driving noise of hydraulic pumps in substations over a long period of time and visualize the data. At the same time, we will analyze the correlation between hydraulic pump operation time and weather data, and verify whether we can determine safe operation time ranges and predictive signs of failure from the results. This will contribute to the stable operation of equipment and provide a means to achieve appropriate maintenance without relying on manual inspections. To evaluate the effectiveness of the system, a series of operations from data collection, analysis, and visualization were verified for 11 hydraulic pumps, and the safe operating range of the equipment was estimated from the results of correlation analysis, linear regression analysis, and residual analysis.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) IoT / Acoustic Data / Anomaly Detection / Visualization
Paper # SITE2023-82,IA2023-88
Date of Issue 2024-03-05 (SITE, IA)

Conference Information
Committee IA / SITE / IPSJ-IOT
Conference Date 2024/3/12(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Miyakojima City Future Creation Center
Topics (in Japanese) (See Japanese page)
Topics (in English) Internet and Information Ethics Education, etc.
Chair Toyokazu Akiyama(Kyoto Sangyo Univ.) / Takushi Otani(Kibi International Univ.)
Vice Chair Yusuke Sakumoto(Kwansei Gakuin Univ.) / Toshiki Watanabe(NEC) / Yuichiro Hei(KDDI) / Soichiro Morishita(Cyber Agent) / Takeo Tatsumi(Open Univ. of Japan)
Secretary Yusuke Sakumoto(Osaka Univ.) / Toshiki Watanabe(Kogakuin Univ.) / Yuichiro Hei(Kyushu Inst. of Tech.) / Soichiro Morishita(NRI-Secure) / Takeo Tatsumi(Fukuoka Inst. of Tech.)
Assistant Daisuke Kotani(Kyoto Univ.) / Ryo Nakamura(Fukuoka Univ.) / Ryo Nakamura(Univ. of Tokyo) / Yusuke Kaneko(Japan Research Institute) / Rodriguez Samudio Ruben Enrique(Waseda Univ.)

Paper Information
Registration To Technical Committee on Internet Architecture / Technical Committee on Social Implications of Technology and Information Ethics / Special Interest Group on Internet and Operation Technology
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Data Analysis and Visualization Method for Equipment Anomaly Detection by Using Acoustic Data
Sub Title (in English)
Keyword(1) IoT
Keyword(2) Acoustic Data
Keyword(3) Anomaly Detection
Keyword(4) Visualization
1st Author's Name Koichiro Kawano
1st Author's Affiliation Kyushu Institute of Technology(KIT)
2nd Author's Name Nobayashi Daiki
2nd Author's Affiliation Kyushu Institute of Technology(KIT)
3rd Author's Name Tsukamo Kazuya
3rd Author's Affiliation Kyushu Institute of Technology(KIT)
4th Author's Name Mizumachi Mitsunori
4th Author's Affiliation Kyushu Institute of Technology(KIT)
5th Author's Name Ikenaga Takeshi
5th Author's Affiliation Kyushu Institute of Technology(KIT)
Date 2024-03-12
Paper # SITE2023-82,IA2023-88
Volume (vol) vol.123
Number (no) SITE-421,IA-422
Page pp.pp.86-91(SITE), pp.86-91(IA),
#Pages 6
Date of Issue 2024-03-05 (SITE, IA)