摘要
针对工程实际中具有复杂结构的随机转子系统,考虑轴承支撑、陀螺力矩、不平衡激励对转子系统振动特性的影响,将有限元法和人工神经网络技术相结合,得到随机响应与基本随机变量之间的显性表达式。在已知基本随机变量的前四阶矩的情况下,根据随机转子系统最大不平衡响应的振动峰值不超过许用振动峰值的关系准则,定义了随机系统的振动可靠性模式,给出了可靠性灵敏度计算公式,研究了工作参数的随机性对转子系统振动可靠性的影响并进行排序,得到了系统可靠度对基本随机变量均值和方差的灵敏度。研究结果表明,在转子的工作转速范围内,工作转速和中压缸左轴承的性能参数是振动最主要的影响因素,在实际使用过程中需严格控制和监视这些工作参数的变化。
Aiming at the random rotor system with complex constructure in practical engineering,taking the influence of bearing,gyroscopic moment and mass unbalance on vibration characteristics of rotor system as considerable factor,the explicit relationship expression between random response and original random variables was obtained by integrating Finite Element Method（FEM） and Artificial Neural Network（ANN） technique.According to the assumption that the maximum amplitude peak of unbalance response should be no more than the allowable amplitude peak,the reliability mode was defined,and the formula of reliability-based sensitivity was given under the condition that the first four moments of basic random variables was known.The effect of working parameter′s randomness on rotor system vibration＇s reliability was studied,and the sensitivity of reliability to the mean value and variance of original random variables was obtained.The results indicated that the working speed and performance parameters of intermediate-pressure compressor left bearing were main influencing factors of vibration.In practical working process,the changes of these parametes should be control and monitor strictly.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2012年第1期149-155,共7页
Computer Integrated Manufacturing Systems
基金
国家科技重大专项资助项目(2010ZX04014-014)
国家自然科学基金资助项目(50875039)
国家科技支撑计划资助项目(2009BAG12A02-A07-2)~~
关键词
转子系统
振动
可靠性
灵敏度
神经网络
有限元
rotor system
vibration
reliability
sensitivity
artificial neural network
finite element method
