东北大学学报:自然科学版 ›› 2020, Vol. 41 ›› Issue (2): 217-222.DOI: 10.12068/j.issn.1005-3026.2020.02.012

• 机械工程 • 上一篇    下一篇

采煤机截割部扭矩轴的动态可靠性分析

杨周1, 姜超1, 张义民2, 姜红猛1   

  1. (1. 东北大学 机械工程与自动化学院, 辽宁 沈阳110819; 2. 沈阳化工大学 机械工程学院, 辽宁 沈阳110142)
  • 收稿日期:2019-03-08 修回日期:2019-03-08 出版日期:2020-02-15 发布日期:2020-03-06
  • 通讯作者: 杨周
  • 作者简介:杨周(1979-),女,辽宁鞍山人,东北大学副教授; 张义民(1958-),男,吉林长春人,沈阳化工大学教授,博士生导师,教育部“长江学者奖励计划”特聘教授.冯明杰(1971-), 男, 河南禹州人, 东北大学副教授; 王恩刚(1962-), 男, 辽宁沈阳人, 东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金联合基金资助项目(U1710119).

Dynamic Reliability Analysis of Torque Shaft in Cutting Part of Coal Mining Machines

YANG Zhou1, JIANG Chao1, ZHANG Yi-min2, JIANG Hong-meng1   

  1. 1. School of Mechanical Engineering & Automation, Northeastern University, Shenyang 110819, China;2. School of Mechanical Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China.
  • Received:2019-03-08 Revised:2019-03-08 Online:2020-02-15 Published:2020-03-06
  • Contact: JIANG Chao
  • About author:-
  • Supported by:
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摘要: 考虑结构和材料等随机参数对零件动态可靠性的影响,避免轴系产生共振,利用Workbench软件建立扭矩轴参数化有限元模型.用模态分析法求解前六阶固有频率和临界转速,并与传递矩阵法比较,证明了结构和转速设计的合理性.结合谐响应分析,说明共振失效应考虑一阶固有频率.通过响应面设计和拉丁超立方抽样法完成对扭矩轴结构、材料参数的抽样,运用BP神经网络拟合一阶固有频率的功能函数,并求解随机参数的可靠性灵敏度.采用一次二阶矩法(FOSM)计算轴在特定转速下的可靠度,并用Monte-Carlo模拟法(MCS)进行了验证,说明转速设计较为可靠.通过灵敏度分析,明确了对扭矩轴动态可靠性影响最大的因素,为轴的稳健优化设计奠定基础.

关键词: 扭矩轴, 有限元, BP神经网络, 可靠度, 可靠性灵敏度

Abstract: The Workbench software was used to establish a parametric finite element model of the torque shaft. Through modal analysis and comparison with the transfer matrix method, the first six orders of natural frequency and corresponding limit speed were obtained to verify the rationality of the structure and speed design. The harmonic response analysis illustrated that resonance invalidation should consider the first natural frequency. In addition, the response surface design and Latin superpower square sampling methods were used to realize the sampling analysis of the structure and material parameters. The BP neural network technology was used to fit the functions of first order natural frequency, solving the reliability sensitivity of each random parameter. The first order second moment and Monte-Carlo simulation were used to calculate the reliability at a specific speed and to find out the biggest influencing factor on the dynamic reliability, thus laying a foundation for the robust optimization design of shaft.

Key words: torque shaft, finite element, BP neural network, reliability, reliability sensitivity

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