1. A feature extraction method based on ICD and MSE for gearbox
- Author
-
Yu Wei, Yongbo Li, Wenhu Huang, and Minqiang Xu
- Subjects
intrinsic characteristic-scale decomposition ,fault feature extraction ,0209 industrial biotechnology ,Computer science ,business.industry ,lcsh:Mechanical engineering and machinery ,Mechanical Engineering ,Feature vector ,Feature extraction ,multiscale entropy ,020206 networking & telecommunications ,Pattern recognition ,gearbox ,02 engineering and technology ,Support vector machine ,Multiscale entropy ,Vibration ,020901 industrial engineering & automation ,0202 electrical engineering, electronic engineering, information engineering ,Entropy (information theory) ,lcsh:TJ1-1570 ,General Materials Science ,Artificial intelligence ,business - Abstract
Since the vibration signals of gearbox are non-linear and non-stationary, it is difficult to accurately evaluate the working conditions. Therefore, a fault feature extraction technique based on intrinsic characteristic-scale decomposition (ICD) and multi-scale entropy (MSE) is presented in this paper. The measured signals are firstly decomposed into a series of product components (PCs) by ICD. Secondly, the main product component is selected, and then MSE is used to extract the feature vectors from the selected PCs. Finally, the obtained feature vectors of gearbox with different scale factors are adopted as inputs of support vector machine (SVM) to fulfill the fault patterns identification. The superiority of the proposed technique is verified through comparing with three other methods.
- Published
- 2016