Condition Monitoring of Refrigeration Compressor Using Sound Signal Based on Convolutional Neural Networks

被引：0
|
作者：
Kuendee, Punyisa [1 ]
机构：
[1] Siam Univ, Grad Sch Engn, Dept Engn Management, 38 Phet Kasem Rd, Bangkok, Thailand
来源：
3RD INTERNATIONAL CONFERENCE ON BIG DATA AND INTERNET OF THINGS (BDIOT 2019) | 2018年
关键词：
Refrigeration compressor; Streaming sound data; Internet of things; Machine learning; Convolutional neural networks; MACHINE;
D O I：
10.1145/3361758.3361772
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, the condition monitoring of refrigeration compressor used in ice making factory at Chonburi, Thailand is investigated. The streaming sound data collected from designed circuit with IoT technology is proposed. The 6-channel FFT spectrum training dataset with target dataset is introduced and used as input features for machine learning approaches such as ANN and CNN. In preliminary study, the target conditions are classified into 3 classes namely run open valve, run close valve and stop. The classification result demonstrates that the accuracy provided by ANN and CNN methods have similar values at approximately 99% in this study with comparison and evaluation.
引用
收藏
页码：105 / 109
页数：5
相关论文
共 50 条
  • [31] Rotating machine condition monitoring using neural networks
    McCormick, AC
    Nandi, AK
    TRENDS IN NDE SCIENCE AND TECHNOLOGY - PROCEEDINGS OF THE 14TH WORLD CONFERENCE ON NDT (14TH WCNDT), VOLS 1-5, 1996, : 1845 - 1848
  • [32] Tool condition monitoring (TCM) using neural networks
    Tien-I Liu
    Bob Jolley
    The International Journal of Advanced Manufacturing Technology, 2015, 78 : 1999 - 2007
  • [33] Epileptic Signal Detection Using Quilted Synchrosqueezing Transform Based Convolutional Neural Networks
    Villazana, Sergio
    Montilla, Guillermo
    Eblen, Antonio
    Maldonado, Carlos
    COMPUTACION Y SISTEMAS, 2021, 25 (02): : 269 - 286
  • [34] An Intelligence-Based Model for Condition Monitoring Using Artificial Neural Networks
    Jenab, K.
    Rashidi, K.
    Moslehpour, S.
    INTERNATIONAL JOURNAL OF ENTERPRISE INFORMATION SYSTEMS, 2013, 9 (04) : 43 - 62
  • [35] Paramps: Convolutional neural networks based on tensor decomposition for heart sound signal analysis and cardiovascular disease diagnosis
    Duan, Lin
    Yang, Lidong
    Guo, Yong
    SIGNAL PROCESSING, 2025, 227
  • [36] Vibration-based Condition Monitoring in Wind Turbine Gearbox Using Convolutional Neural Network
    Amin, Abdelrahman
    Bibo, Amin
    Panyam, Meghashyam
    Tallapragada, Phanindra
    2022 AMERICAN CONTROL CONFERENCE, ACC, 2022, : 3777 - 3782
  • [37] AGRICULTURAL HARVESTER SOUND CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORKS AND SPECTROGRAMS
    Khorasani, Nioosha E.
    Thomas, Gabriel
    Balocco, Simone
    Mann, Danny
    APPLIED ENGINEERING IN AGRICULTURE, 2022, 38 (02) : 455 - 459
  • [38] SOUND SOURCE LOCALIZATION IN A MULTIPATH ENVIRONMENT USING CONVOLUTIONAL NEURAL NETWORKS
    Ferguson, Eric L.
    Williams, Stefan B.
    Jin, Craig T.
    2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2018, : 2386 - 2390
  • [39] Lung Sound Classification Using Snapshot Ensemble of Convolutional Neural Networks
    Truc Nguyen
    Pernkopf, Franz
    42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20, 2020, : 760 - 763
  • [40] A Binaural Sound Localization System using Deep Convolutional Neural Networks
    Xu, Ying
    Afshar, Saeed
    Singh, Ram Kuber
    Wang, Runchun
    van Schaik, Andre
    Hamilton, Tara Julia
    2019 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2019,
12345