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Bearing condition monitoring based on shock pulse method and improved redundant lifting scheme

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Listed:
  • Zhen, Li
  • Zhengjia, He
  • Yanyang, Zi
  • Xuefeng, Chen

Abstract

Due to the widespread application of rolling element bearings, it is necessary to effectively monitor their health status. The shock pulse method (SPM) has been widely used as a quantitative method for bearing condition monitoring. However, the shock value indicating the bearing condition may be mistakenly estimated by direct demodulation in the SPM. To overcome this deficiency, a new approach based on improved redundant lifting scheme (IRLS) is proposed. The classical redundant lifting scheme is improved by adding the normalization factors to avoid error propagation of decomposition results, and the IRLS is applied to preprocess the bearing vibration signals. Then the maximum normalized shock value of detail signals in decomposition results is used as a measure of the bearing condition. The effectiveness of the proposed method is demonstrated by applying it to both simulated signals and practical bearing vibration signals under different conditions. The results show that the proposed method is effective for bearing condition monitoring.

Suggested Citation

  • Zhen, Li & Zhengjia, He & Yanyang, Zi & Xuefeng, Chen, 2008. "Bearing condition monitoring based on shock pulse method and improved redundant lifting scheme," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 318-338.
    • Handle: RePEc:eee:matcom:v:79:y:2008:i:3:p:318-338
    DOI: 10.1016/j.matcom.2007.12.004
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    Cited by:

    1. Mérigaud, Alexis & Ringwood, John V., 2016. "Condition-based maintenance methods for marine renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 53-78.
    2. Beganovic, Nejra & Söffker, Dirk, 2016. "Structural health management utilization for lifetime prognosis and advanced control strategy deployment of wind turbines: An overview and outlook concerning actual methods, tools, and obtained result," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 68-83.
    3. García Márquez, Fausto Pedro & Tobias, Andrew Mark & Pinar Pérez, Jesús María & Papaelias, Mayorkinos, 2012. "Condition monitoring of wind turbines: Techniques and methods," Renewable Energy, Elsevier, vol. 46(C), pages 169-178.

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