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Wear Calculation-Based Degradation Analysis and Modeling for Remaining Useful Life Prediction of Ball Screw

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Listed:
  • Li Zhang
  • Hongli Gao
  • Dawei Dong
  • Guoqiang Fu
  • Qi Liu

Abstract

Ball screw is a kind of precise transmission element in drive system of machine tool. In this paper, the degradation model of ball screw is proposed based on wear calculation-based degradation analysis and experimental data-based validation. At first, fatigue wear is analyzed to be the predominant degradation mode of ball screw. The wear volume formula of ball screw is derived as the function of working load and stroke number. Secondly, the degradation rate of ball screw is analyzed to be affected by the total degradation and wear rate. Based on this finding, the degradation model of ball screw is theoretically derived as an exponential model by inputting wear volume formula. Thirdly, experimental data-based cross-validation method is proposed to validate the exponential degradation model. Determination coefficients are calculated to evaluate the fitting degree between the degradation model and real degradation path. Next, run-to-failure test of ball screw is carried out to collect experimental data in different working conditions. The average determination coefficient of different working conditions is calculated as 0.7848, which indicates that the proposed model can well fit the actual degradation path. In addition, the proposed model is applied to predict remaining useful life (RUL) of the tested ball screw by using collected data. RUL is estimated in a high and stable accuracy after 168000 strokes. For further validation, comparison with linear model is performed. All results show that the exponential degradation model is reasonable and correct in reflecting the degradation process of ball screw.

Suggested Citation

  • Li Zhang & Hongli Gao & Dawei Dong & Guoqiang Fu & Qi Liu, 2018. "Wear Calculation-Based Degradation Analysis and Modeling for Remaining Useful Life Prediction of Ball Screw," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-18, November.
  • Handle: RePEc:hin:jnlmpe:2969854
    DOI: 10.1155/2018/2969854
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