现代制造工程Issue(5)：162-167,6.DOI:10.16731/j.cnki.1671-3133.2017.05.029
基于BP-AdaBoost的耦合碰摩故障特征识别研究
Research on the feature recognition of the coupled rub impact fault based on BP-AdaBoost
摘要
Abstract
The BP neural network,used in the study of fault diagnosis for rotating machinery,is easy to fall into local minima,and then the global optimal solution could not be obtained,that results in a poor classification and recognition rate of couple rub impact fault.Based on the analysis of an Empirical Mode Decomposition (EMD) method and a BP-AdaBoost method,puts forward a new algorithm of fault identification combined with the advantages of them above.First of all,an Empirical Mode Decomposition (EMD) method is used to decompose vibration signal from the rotor,for the aim of removing background noise signal,so the fault feature of rub impact signal of rotor system is obtained.Then a BP-AdaBoost model is used for the recognition of three kinds of different conditions.The analysis results on the experiments data show that the recognition rate of this new method is better than that of a single BP neural network.关键词
耦合碰摩/故障特征/经验模态分解/BP-AdaboostKey words
coupling rubbing/fault features/Empirical Mode Decomposition (EMD)/BP-Adaboost分类
信息技术与安全科学引用本文复制引用
卢艳军,刘毅..基于BP-AdaBoost的耦合碰摩故障特征识别研究[J].现代制造工程,2017,(5):162-167,6.基金项目
航空科学基金项目(2012ZD54013) （2012ZD54013）
辽宁省教育厅科技项目(L2013070) （L2013070）
