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FATIGUE LIFE OPTIMIZATION FOR GEAR CRITICAL ACTUATION SYSTEMS BY LOAD SPECTRUM SYNTHESIS AND AN ALGORITHM FOR S-N-R CURVE GENERATION.

机译:基于载荷谱综合的齿轮临界驱动系统疲劳寿命优化及S-N-R曲线生成算法。

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摘要

The purpse of this project is to develop a method to synthesize the load spectrum for a gear critical machine in order to obtain its maximum life capability. An algorithm able to predict the fatigue life of any cyclic load based on a few known S-N curves is developed first. This algorithm can also generate the S-N curve of any stress ratio. The following two advantages are identified for this algorithm: (1) It imposes minimum restraints to the shape of the constant life curves in the constant life diagram. (2) All the constant life curves and S-N curves generated by this algorithm pass through their data points. These two features improve the accuracy of te life prediction for cyclic loads. Therefore, this algorithm is not only developed for the usage in this project, but it also can be very useful for general fatigue analysis, espcially for cumulative damage problems.;Computer programs are developed for the above algorithms. This can greatly reduce the problem solving time and enhance the applicability of the two algorithms.;A second algorithm is then developed to synthesize the load spectrum of gear critical machinery to maximize the machine life capability. Based on the author's knowledge, this type of work has not been done in a systematic way before.
机译:该项目的目的是开发一种方法,以合成齿轮关键机器的载荷谱,从而获得其最大使用寿命。首先开发了一种能够基于一些已知的S-N曲线预测任何循环载荷的疲劳寿命的算法。该算法还可以生成任何应力比的S-N曲线。该算法具有以下两个优点:(1)在恒定寿命图中,对恒定寿命曲线的形状施加了最小限度的约束。 (2)该算法生成的所有恒定寿命曲线和S-N曲线均通过其数据点。这两个功能提高了循环载荷寿命预测的准确性。因此,该算法不仅是为本项目开发的,而且对于一般疲劳分析,特别是对于累积损伤问题,也非常有用。;为上述算法开发了计算机程序。这样可以大大减少解决问题的时间,提高两种算法的适用性。然后,开发了第二种算法来合成齿轮关键机械的载荷谱,以最大化机器的使用寿命。根据作者的知识,以前尚未以系统的方式完成此类工作。

著录项

  • 作者

    OYOUNG, SHIO-PING PHILIP.;

  • 作者单位

    University of Missouri - Columbia.;

  • 授予单位 University of Missouri - Columbia.;
  • 学科 Applied Mechanics.
  • 学位 Ph.D.
  • 年度 1982
  • 页码 389 p.
  • 总页数 389
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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