A novel order spectrum-based Vold-Kalman filter bandwidth selection scheme for fault diagnosis of gearbox in offshore wind turbines

被引:49
|
作者
Feng, Ke [1 ]
Ji, J. C. [1 ]
Wang, Kesheng [2 ]
Wei, Dongdong [3 ]
Zhou, Chengning [4 ]
Ni, Qing [1 ]
机构
[1] Univ Technol Sydney, Sch Mech & Mechatron Engn, Sydney, NSW 2007, Australia
[2] Univ Elect Sci & Technol China, Sch Mech & Elect Engn, Chengdu 611731, Peoples R China
[3] Univ Alberta, Dept Mech Engn, Edmonton, AB T6G 1H9, Canada
[4] Nucl Power Inst China, Shenzhen, Peoples R China
关键词
Offshore wind turbines; Vold -Kalman filter order tracking; Characteristic vibrations; Bandwidth; Condition monitoring process; Planetary gearbox; PLANETARY GEARBOX; TRACKING; VIBRATION;
D O I
10.1016/j.oceaneng.2022.112920
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Vold-Kalman order tracking filter is an effective technique for dealing with non-stationary vibrations which offshore wind turbines often encounter. It has a unique capability to extract and track the time waveforms of harmonics in short transients without phase bias, and this capability is beneficial to the condition monitoring of offshore wind turbines. In general, the accuracy of the tracking results of the Vold-Kalman filer for condition monitoring is heavily dependent on the selection of filter bandwidth. A fixed filter bandwidth becomes prob-lematic when processing different types of signals under varying operating conditions. Significant errors may arise in the tracking, rendering the condition monitoring of offshore wind turbines unreliable. To address this issue, this paper proposes a novel scheme for Vold-Kalman filter bandwidth selection to guarantee the consis-tency and accuracy of the offshore wind turbine condition monitoring process, ensuring reliable fault diagnosis. A numerical model is used to evaluate the effectiveness of the proposed bandwidth selection scheme first. Then the proposed scheme is further validated through the offshore wind turbine planetary gearbox datasets, together with the demonstration of the fault diagnosis capability of the filtered results.
引用
收藏
页数:14
相关论文
共 12 条
  • [1] Application of Spectral kurtosis and Vold-Kalman Filter Based Order Tracking in wind turbine gearbox fault diagnosis
    Jiang Hong
    We Guangrui
    Zhang Xiangfeng
    Shi Yongfang
    Xu Bin
    2017 9TH INTERNATIONAL CONFERENCE ON MODELLING, IDENTIFICATION AND CONTROL (ICMIC 2017), 2017, : 49 - 53
  • [2] A novel generalized Vold-Kalman filtering for wind turbine fault diagnosis
    Liu, Dongdong
    Cui, Lingli
    Chen, Jiahui
    OCEAN ENGINEERING, 2024, 308
  • [3] A novel adaptive bandwidth selection method for Vold-Kalman filtering and its application in wind turbine planetary gearbox diagnostics
    Feng, Ke
    Ji, J. C.
    Ni, Qing
    STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2023, 22 (02): : 1027 - 1048
  • [4] Time-frequency analysis based on Vold-Kalman filter and higher order energy separation for fault diagnosis of wind turbine planetary gearbox under nonstationary conditions
    Feng, Zhipeng
    Qin, Sifeng
    Liang, Ming
    RENEWABLE ENERGY, 2016, 85 : 45 - 56
  • [5] Application of Vold-Kalman filter and higher order energy separation to fault diagnosis of planetary gearbox under time-varying conditions
    Qin, Si-Feng
    Feng, Zhi-Peng
    Liang, Ming
    Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2015, 28 (05): : 839 - 845
  • [6] Time-Frequency demodulation analysis via Vold-Kalman filter for wind turbine planetary gearbox fault diagnosis under nonstationary speeds
    Feng, Zhipeng
    Zhu, Wenying
    Zhang, Dong
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2019, 128 : 93 - 109
  • [7] A fault diagnosis method of planetary gearbox under variable speed condition using Vold-Kalman filter and Laplacian score
    Li, Yongbo
    Wang, Xianzhi
    Liu, Zhiliang
    Si, Shubin
    2018 IEEE INTERNATIONAL CONFERENCE ON PROGNOSTICS AND HEALTH MANAGEMENT (ICPHM), 2018,
  • [8] Fault Diagnosis of Rolling Bearing Under Speed Fluctuation Condition Based on Vold-Kalman Filter and RCMFE
    Li, Yongbo
    Wei, Yu
    Feng, Ke
    Wang, Xianzhi
    Liu, Zhenbao
    IEEE ACCESS, 2018, 6 : 37349 - 37360
  • [9] Bearing fault diagnosis of BLDC motor using Vold-Kalman order tracking filter under variable speed condition
    Niu, Jiahao
    Lu, Siliang
    Liu, Yongbin
    Wang, Qunjing
    PROCEEDINGS OF THE 2019 14TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2019), 2019, : 2379 - 2383
  • [10] Order spectrum analysis enhanced by surrogate test and Vold-Kalman filtering for rotating machinery fault diagnosis under time-varying speed conditions
    Chen, Xiaowang
    Feng, Zhipeng
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2021, 154