Fault detection and diagnosis of linear bearing in auto core adhesion mounting machines based on condition monitoring

被引：0
|
作者：
Chommuangpuck, Prathan [1 ,2 ]
Wanglomklang, Thanasak [1 ]
Srisertpol, Jiraphon [1 ]
机构：
[1] School of Mechanical Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand
[2] Western Digital Thailand Co. Ltd., Phra Nakhon Si Ayutthaya, Thailand
来源：
Systems Science and Control Engineering | 2021年 / 9卷 / 01期
关键词：
This research was supported by the Research and Researcher for Industry (RRI) under the Thailand Research Fund (TRF). It offers a scholarship for PhD students at Suranaree University of Technology (SUT) through [grant number PHD60I0043];
D O I：
暂无
中图分类号：
学科分类号：
摘要：
23
引用
收藏
页码：290 / 303
相关论文
共 50 条
  • [31] Bearing fault diagnosis of a mine stone crasher by vibration condition monitoring technique
    Ahmadi, H.
    Mollazade, K.
    Research Journal of Applied Sciences, Engineering and Technology, 2009, 1 (03) : 112 - 115
  • [32] Implementation of Envelope Analysis on a Wireless Condition Monitoring System for Bearing Fault Diagnosis
    Feng, Guo-Jin
    Gu, James
    Zhen, Dong
    Aliwan, Mustafa
    Gu, Feng-Shou
    Ball, Andrew D.
    INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING, 2015, 12 (01) : 14 - 24
  • [33] Fault Diagnosis and Condition Monitoring of Bearing Using Multisensory Approach Based Fuzzy-Logic Clustering
    Pazouki, E.
    Choi, S.
    2015 IEEE INTERNATIONAL ELECTRIC MACHINES & DRIVES CONFERENCE (IEMDC), 2015, : 1412 - 1418
  • [34] Linear Bearing Fault Detection in Operational Condition Using Artificial Neural Network
    Lawbootsa, Siwanu
    Chommaungpuck, Prathan
    Srisertpol, Jiraphon
    AMCSE 2018 - INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, COMPUTATIONAL SCIENCE AND SYSTEMS ENGINEERING, 2019, 24
  • [35] Condition monitoring and fault diagnosis strategy of railway point machines using vibration signals
    Yongkui Sun
    Yuan Cao
    Haitao Liu
    Weifeng Yang
    Shuai Su
    Transportation Safety and Environment, 2023, 5 (02) : 27 - 34
  • [36] A novel industrial wireless sensor network for condition monitoring and fault diagnosis of electrical machines
    School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Australia
    Aust. J. Electr. Electron. Eng., 2013, 4 (505-514):
  • [37] Condition monitoring and fault diagnosis strategy of railway point machines using vibration signals
    Sun, Yongkui
    Cao, Yuan
    Liu, Haitao
    Yang, Weifeng
    Su, Shuai
    TRANSPORTATION SAFETY AND ENVIRONMENT, 2023, 5 (02)
  • [38] Transfer fault diagnosis of bearing installed in different machines using enhanced deep auto-encoder
    He Zhiyi
    Shao Haidong
    Jing Lin
    Cheng Junsheng
    Yang Yu
    MEASUREMENT, 2020, 152
  • [39] Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding
    Wang, Xiang
    Zheng, Yuan
    Zhao, Zhenzhou
    Wang, Jinping
    SENSORS, 2015, 15 (07) : 16225 - 16247
  • [40] CLASS INCREMENTAL FAULT DETECTION AND DIAGNOSIS WITH UNLABELED CONDITION MONITORING DATA
    Peng, Xiaomeng
    Jin, Xiaoning
    Duan, Shiming
    Sankavaram, Chaitanya
    PROCEEDINGS OF THE ASME 2020 15TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE (MSEC2020), VOL 2B, 2020,
12345