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基于Kriging模型的液压柱塞泵可靠性灵敏度分析
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NSFC-辽宁联合基金(U1708254);国家重点研发计划重点专项(2019FB2000009)


Reliability Sensitivity Analysis for Hydraulic Piston Pump Based on Kriging Model
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    摘要:

    液压柱塞泵作为液压系统的核心动力元件,其能量转换效率很大程度上决定了整个液压系统的性能和可靠性,而目前采用的能量转换效率模型多为确定性数值模型,没有考虑参数随机性的影响,无法真实反映柱塞泵的实际运行状态。提出了基于Kriging模型的柱塞泵总效率建模方法,选用柱塞泵总效率为可靠性失效判据,分别采用改进一次二阶矩法和Monte-Carlo数值仿真法对柱塞泵总效率进行可靠性和可靠性灵敏度分析。分析结果表明:Kriging模型采用少量的样本模拟的总效率模型具有较高的精度,模拟结果可以获取全面的柱塞泵效率特性;运行工况条件对柱塞泵总效率可靠性灵敏度具有重大影响,不同工况下灵敏度具有较大差异。提出的方法可推广至其他液压泵总效率模型的建立及可靠性灵敏度分析。

    Abstract:

    As the core power component of hydraulic system,the energy conversion efficiency of hydraulic piston pump largely determines the performance and reliability of the whole hydraulic system.At present,most of the energy conversion efficiency models used are deterministic numerical models,which do not consider the influence of parameter randomness,and can not truly reflect the actual operation state of piston pump.The overall efficiency modeling method of the piston pump based on Kriging model was proposed.Taking the overall efficiency of the piston pump as the reliability failure criterion,the reliability and reliability sensitivity for the overall efficiency of the piston pump were analyzed by the advanced first order and second moment method and the Monte-Carlo numerical simulation method,respectively.The results show that the overall efficiency model simulated by the Kriging model with a small number of samples has a higher accuracy,which can obtain the comprehensive overall efficiency characteristics of the piston pump.The operating conditions have a great influence on the reliability sensitivity for the overall efficiency of the piston pump,and the sensitivity varies greatly under different operating conditions.The presented method can be extended to the establishment of overall efficiency models and reliability sensitivity analysis of other hydraulic pumps.

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杜尊令,张义民.基于Kriging模型的液压柱塞泵可靠性灵敏度分析[J].润滑与密封,2022,47(5):16-22.
DU Zunling, ZHANG Yimin. Reliability Sensitivity Analysis for Hydraulic Piston Pump Based on Kriging Model[J]. Lubrication Engineering,2022,47(5):16-22.

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  • 在线发布日期: 2022-06-30
  • 出版日期: 2022-05-15