东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2016, Vol. 37 ›› Issue (10): 1426-1431.DOI: 10.12068/j.issn.1005-3026.2016.10.013

• 机械工程 • 上一篇    下一篇

采煤机摇臂系统行星轮系疲劳可靠性灵敏度设计

张义民， 王婷， 黄婧   

  1. (东北大学 机械工程与自动化学院， 辽宁 沈阳110819)
  • 收稿日期:2015-09-01 修回日期:2015-09-01 出版日期:2016-10-15 发布日期:2016-10-14
  • 通讯作者: 张义民
  • 作者简介:张义民(1958-)，男，吉林长春人，东北大学教授，博士生导师.
  • 基金资助:
    国家重点基础研究发展计划项目(2014CB046303)； 国家自然科学基金资助项目(51135003).

Fatigue Reliability-Based Sensitivity Design of Planet Gear for Shearer Rocker Arm System

ZHANG Yi-min， WANG Ting， HUANG Jing   

  1. School of Mechanical Engineering & Automation， Northeastern University， Shenyang 110819， China.
  • Received:2015-09-01 Revised:2015-09-01 Online:2016-10-15 Published:2016-10-14
  • Contact: ZHANG Yi-min
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摘要： 由于采煤机摇臂系统的行星轮系结构比较复杂，采用集中质量参数法对其进行有限元建模，分析行星轮与太阳轮的动态接触应力以确定其失效模式.主要考虑行星轮与太阳轮结构尺寸的随机性，利用BP神经网络的非线性映射功能，模拟得到疲劳寿命与随机参数的关系表达式.采用最大可能点摄动法进行可靠性设计.最后通过对行星轮与太阳轮的可靠性灵敏度设计，得到了各参数均值和方差对结构可靠性的影响情况.Monte-Carlo仿真试验验证了所提方法的正确性，为行星轮与太阳轮可靠性灵敏度设计提供了理论参考.

关键词: 行星轮与太阳轮, 有限元建模, BP神经网络, 最大可能点摄动法, 可靠性灵敏度设计

Abstract: As the planet gears structure of shearer rocker arm system is very complicated， a finite element model was built using the lumped-mass parameter method， and the dynamic contact stress of the planet gear and sun gear was analyzed to determine its failure mode. Considering the randomness of structural dimension for the planet gear and sun gear， a relational expression between the fatigue life and random parameters was obtained by using the nonlinear mapping function of BP neural network. The MPPPM was applied to the reliability design. The effect of the parameters’ mean and variance on the structure reliability was achieved by the planet gear and sun gear reliability-based sensitivity design.The simulation experiment using the Monte-Carlo showed the correctness of the as-proposed method， and provided a theoretical reference for the reliability-based sensitivity design of the planet gear and sun gear.

Key words: planet gear and sun gear, finite element model, BP neural network, MPPPM(most probable point perturbation method), reliability-based sensitivity design

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