行星齿轮系故障特征多目标进化选择方法  

Multi-objective Evolutionary Selection Method for Planetary Gear Trains Fault Feature

作　　者：黄海安[1] 王友仁[1] 孙灿飞[1,2] 陈伟 王俊[1] HUANG Haian;WANG Youren;SUN Canfei;CHEN Wei;WANG Jun(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Shanghai Aero Measurement ＆ Control Technology Research Institute,Shanghai 201601,China)

机构地区：[1]南京航空航天大学自动化学院,江苏南京210016 [2]上海航空测控技术研究所,上海201601

出　　处：《机械制造与自动化》2018年第4期13-16,43,共5页Machine Building & Automation

基　　金：航空科学基金项目(2013ZD52055);国家商用飞机制造工程技术研究中心创新基金项目(SAMC14-JS-15-051);研究生创新基地(实验室)开发基金项目(kfjj20160305)

摘　　要：针对行星齿轮箱复杂故障难以辨识问题,提出一种基于遗传算法的行星齿轮系多目标故障特征优选方法。从振动信号中提取多域故障特征,建立了多域故障特征优选数学模型,将特征选择问题转化为多目标优化问题;采用遗传算法求解得到最优特征子集。实验表明,该方法对高维故障特征具有较好的降维性能,能有效选择高质量的故障特征子集,使得故障诊断性能明显提高。Because it is hard to identify complex fault in planetary gearbox,this paper proposes a new method based on genetic algorithm which is used to extract the fault signals from vibration,establishes the mathematical optimization model for multi-domain fault features,changes the feature selection problem into multi-objective optimization problem and then uses the genetic algorithm to get the optimal feature subset. The experimental results show that the proposed method has a better dimensionality reduction performance for complex fault features,and can be used to effectively select a high quality fault feature subset,thus improving the effect the of fault diagnosis obviously.

关 键 词：故障辨识 特征选择 遗传算法 行星齿轮箱 

分 类 号：TH132.425[机械工程—机械制造及自动化] TP391[自动化与计算机技术—计算机应用技术]