IDENTIFICATION OF MACHINE FAULT CONDITIONS

被引：0
|
作者：
Tkac, Jozef [1 ]
Macalak, Jaroslav [1 ]
机构：
[1] Univ Trencin, Fac Mechatron, Trencin 91150, Slovakia
来源：
AIM 09, INTERNATIONAL SYMPOSIUM: ADVANCES IN MECHATRONICS 2009 | 2010年
关键词：
Identification; vibration analysis;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Vibration analysis has been used for the identification of machine fault conditions. The specific characteristics of the vibration spectrum are associated with common fault conditions. The spectral components reflect the rotational frequency in the spectrum and indicate the degree of imbalance and fault conditions. This paper demonstrates the presence of a machine defect and an identification of a vibration feature.
引用
收藏
页码：51 / 58
页数：8
相关论文
共 50 条
  • [1] Fault Detection and Identification on Pneumatic Production Machine
    Dobossy, Barnabas
    Formanek, Martin
    Stastny, Petr
    Spacil, Tomas
    MODELLING AND SIMULATION FOR AUTONOMOUS SYSTEMS (MESAS 2021), 2022, 13207 : 39 - 60
  • [2] A prospective study on anesthesia machine fault identification
    Larson, Eric R.
    Nuttall, Gregory A.
    Ogren, Brian D.
    Severson, Dean D.
    Wood, Sarah A.
    Torsher, Laurence C.
    Oliver, William C.
    Marienau, Mary E. Shirk
    ANESTHESIA AND ANALGESIA, 2007, 104 (01): : 154 - 156
  • [3] Differential fault location identification by machine learning
    Baksi, Anubhab
    Sarkar, Santanu
    Siddhanti, Akhilesh
    Anand, Ravi
    Chattopadhyay, Anupam
    CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY, 2021, 6 (01) : 17 - 24
  • [4] Bearing Fault Identification Using Machine Learning and Adaptive Cascade Fault Observer
    Piltan, Farzin
    Kim, Jong-Myon
    APPLIED SCIENCES-BASEL, 2020, 10 (17):
  • [5] Feature Identification With Compressive Measurements for Machine Fault Diagnosis
    Du, Zhaohui
    Chen, Xuefeng
    Zhang, Han
    Miao, Huihui
    Guo, Yanjie
    Yang, Boyuan
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2016, 65 (05) : 977 - 987
  • [6] Fault Identification of Rotor Machine Based on Optimized Method
    郭丹
    卢文秀
    陈真勇
    褚福磊
    Tsinghua Science and Technology, 2004, (03) : 249 - 253
  • [7] Feature Identification with Compressive Measurements for Machine Fault Diagnosis
    Du, Zhaohui
    Chen, Xuefeng
    Zhang, Han
    2015 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC), 2015, : 588 - 593
  • [8] Fault Identification of Photovoltaic Array Based on Machine Learning Classifiers
    Badr, Mohamed M.
    Hamad, Mostafa S.
    Abdel-Khalik, Ayman S.
    Hamdy, Ragi A.
    Ahmed, Shehab
    Hamdan, Eman
    IEEE ACCESS, 2021, 9 : 159113 - 159132
  • [9] Induction Motor Fault Identification using Support Vector Machine
    Okpo, Ekom E.
    Le Roux, Peet F.
    Nnachi, Agha F.
    2023 6TH INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY AND POWER ENGINEERING, REPE 2023, 2023, : 168 - 174
  • [10] Induction machine fault identification using particle swarm algorithms
    Ethny, S. A.
    Acarnley, P. P.
    Zahawi, B.
    Giaouris, D.
    2006 IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONIC, DRIVES AND ENERGY SYSTEMS, VOLS 1 AND 2, 2006, : 1020 - +
12345