中国机械工程

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卫星动量轮轴承摩擦力矩性能可靠性动态预测

夏新涛1,2;陈向峰1;叶亮3   

  1. 1.河南科技大学机电工程学院,洛阳,471003
    2.河南科技大学机械装备先进制造河南省协同创新中心,洛阳,471003
    3.西北工业大学机电学院, 西安,710072
  • 出版日期:2019-06-10 发布日期:2019-06-11
  • 基金资助:
    国家自然科学基金资助项目(51475144);
    河南省自然科学基金资助项目(162300410065)

Dynamic Prediction of Friction Torque Performance Reliability for Satellite Momentum Wheel Bearings

XIA Xintao1,2;CHEN Xiangfeng1;YE Liang3#br#   

  1. 1.School of Mechatronics Engineering,Henan University of Science and Technology,Luoyang,Henan,471003
    2.Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province,Henan University of Science and Technology,Luoyang,Henan,471003
    3.School of Mechanical Engineering, Northwestern Polytechnical University,Xi'an,710072
  • Online:2019-06-10 Published:2019-06-11

摘要: 基于灰置信水平、自助-最小二乘法和最大熵原理建立动态预测模型,并应用于卫星动量轮轴承摩擦力矩性能可靠性的动态预测。首先,对摩擦力矩原始数据分组得到样本,并选定本征样本,提出了由灰置信水平求解各样本变异强度的新方法,进而求得各样本可靠度的实际值;其次,将紧邻的5个样本变异强度融入自助-最小二乘法线性拟合得到拟合系数,由最大熵原理得到下一个样本的变异强度预测值和上下区间;然后,持续更新紧邻的5个变异强度,得到各样本可靠度的预测值和上下区间,最终实现滚动轴承摩擦力矩性能可靠性的动态预测。试验结果表明,恒转速条件下可靠度预测误差均小于4.1%,变转速条件下可靠度预测误差不超过9.4%,充分验证了所提出动态预测模型的可行性和正确性。

关键词: 灰置信水平, 自助-最小二乘法, 最大熵原理, 可靠性, 动态预测

Abstract: Based on the gray confidence level, bootstrap-least square method and maximum entropy principle, a dynamic prediction model was established and applied to the dynamic prediction of friction torque performance reliability for the satellite momentum wheel bearings. Firstly, the original data of friction torques were grouped into samples, and the intrinsic sample was selected. Then, a new method was proposed to calculate the variation intensity of each sample by the gray confidence level, and the actual values of the reliability for each sample were obtained. The closest 5 variation intensities were integrated into the bootstrap-least square linear fitting to obtain the fitting coefficients, and then the prediction values and upper and lower intervals of the next sample variation intensity were obtained by the maximum entropy principle. By the closest 5 variation intensities continuously updated, the prediction values and upper and lower intervals of each sample reliability were obtained, and finally the dynamic predictions of friction torque performance reliability for the rolling bearings were realized. The testing results show that the reliability prediction errors are less than 4.1% under constant speed conditions and are at most 9.4% under variable speed conditions, which fully proves the feasibility and correctness of the proposed dynamic prediction model.

Key words: gray confidence level, bootstrap-least square method, maximum entropy principle, reliability, dynamic prediction

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