北京交通大学学报2017，Vol.41Issue(5)：10-16,7.DOI:10.11860/j.issn.1673-0291.2017.05.002
内燃机优化VMD-CWD时频表征与BSNMF编码识别诊断方法
Parameter optimized VMD-CWD time-frequency representation and BSNMF identification diagnosis method of internal combustion engine
摘要
Abstract
Aiming at the problem of vibration response signal of internal combustion engine featuring the strong coupling and weak fault,a fault diagnosis method based on vibaration time-frequency feature of parameter optimization VMD-CWD internal combustion engine and BSNMF block coding recognition is proposed.Variational Mode Decomposition (VMD) is used to decompose the vibration signal of internal combustion engine into a set of Intrinsic Modal Function (IMF),and the Choi-Williams Distribution (CWD) of the IMF component signal is superimposed in order to obtain the vibration spectrum image with better time-frequency concentration and without cross term interference.In allusion to the parameter selection in the process of VMD decomposition,power spectral entropy is introduced as the objective function and the successive grid optimization is achieved for decomposition parameter of VMD,which improves the adaptability of VMD decomposition.In order to realize the automatic recognition and diagnosis of the vibration spectrum image of the internal combustion engine,a more easily convergent Block Sparse Nonnegative Matrix Factorization(BSNMF) is proposed based on the Sparse Nonnegative Matrix Factorization(SNMF),which is used to extract features of vibration spectrum of internal combustion engine and the support vector machine is adopted to directly conduct the pattern identification of extracted feature parameters.The method is applied to the fault diagnosis of internal combustion engine.The results show that this method can effectively extract the weak fault characteristics of the vibration signal of internal combustion engine and realize the automatic diagnosis of the valve mechanism failure of internal combustion engine.关键词
故障诊断/内燃机/Choi-Williams分布/变分模态分解/分块稀疏非负矩阵分解Key words
fault diagnosis/IC engine/Choi-Williams distribution/variational mode decomposition/block sparse non-negative matrix Factorization分类
机械制造引用本文复制引用
岳应娟,王旭,蔡艳平,刘渊,郑勇..内燃机优化VMD-CWD时频表征与BSNMF编码识别诊断方法[J].北京交通大学学报,2017,41(5):10-16,7.基金项目
国家自然科学基金项目(51405498) （51405498）
中国博士后科学基金项目(2015M582642)National Natural Science Foundation of China(51405498) （2015M582642）
China Postdoctoral Science Foundation(2015M582642) （2015M582642）
