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Fatigue life prediction of wire rope based on grey particle filter method under small sample condition
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College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin, 150001, P. R. China
Research Institute 704, China Shipbuilding Industry Corporation, CSIC, Shanghai, 200031, P. R. China
Publication date: 2021-09-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(3):454–467
  • Using high-cycle small sample to predict lowcycle life meets engineering needs.
  • Using the grey model to obtain the stress-life curve can reduce test costs.
  • The grey particle filter method is proposed to improve the accuracy of P-S-N curve.
  • The grey particle filter method is robustness for predicting wire rope’s life.
The fatigue life prediction of wire ropes has two main characteristics: a large test sample size and uncertain factors. In this paper, based on the small number of wire rope fatigue life data, the grey particle filter method has been used to realize the fatigue life prediction of wire rope under different load conditions. First, the GOM(1,1) model is constructed and the reliability life data of wire rope is predicted under small sample size. Then, P-S-N curve of the dangerous part is determined by combining the equivalent alternating stress of the dangerous part of the wire rope during the fatigue test. Subsequently, the particle filter method is used to modify P-S-N curve. Finally, the fatigue life prediction model of wire rope is obtained based on fatigue damage accumulation, which realized the fatigue life prediction under different load conditions, and the results were compared with that from the test. The results show that the proposed method is effective and has high accuracy in wire rope fatigue life prediction under single, combined loading conditions and small sample size.
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