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<p>Identifying stiffness and damping is vital to predict bearing fault. These two parameters change with working conditions, but in the dynamic model are assumed to be constant and are often calculated empirically and approximately. In this paper, for the first time, the stiffness and damping are identified for various working conditions using the differential evolution algorithm. The dynamic model is established to obtain simulation responses. They are then combined with experimental responses to obtain the values of the stiffness and damping using the differential evolution algorithm. This process is repeated for various working conditions. It is shown that the identified stiffness and damping change with bearing loads and speeds, and therefore assuming them as constant values in the model decrease accuracy.</p>

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Stiffness and damping identification for bearings using differential evolution algorithm

  • 期刊论文

  • 发表日期：

    2026年2月9日

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  • Guangan Ren,
  • Kai Zhang,
  • Yingxuan Li,
  • Shulei Wang,
  • Xupeng Ou,
  • Shuzhi Gao

摘要

Identifying stiffness and damping is vital to predict bearing fault. These two parameters change with working conditions, but in the dynamic model are assumed to be constant and are often calculated empirically and approximately. In this paper, for the first time, the stiffness and damping are identified for various working conditions using the differential evolution algorithm. The dynamic model is established to obtain simulation responses. They are then combined with experimental responses to obtain the values of the stiffness and damping using the differential evolution algorithm. This process is repeated for various working conditions. It is shown that the identified stiffness and damping change with bearing loads and speeds, and therefore assuming them as constant values in the model decrease accuracy.