A novel dictionary learning approach based on blind source separation basis and its application. (June 2017)

• Record Type: Journal Article
• Authors: Zhang, Jie; Li, Shiyun
• Is Part Of: Advances in mechanical engineering. Volume 9:Number 6(2017:Jun.)
• Publication Date: 2017-06
• Subjects: Dictionary learning -- adaptive parameter blind source separation -- wheel condition monitoring; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/1687814017703008
• Languages: English
• ISSNs: 1687-8132

Abstract

The early recognition of wheel wear is an important task to the safe and efficient operation of a railway network. This article presents a new dictionary learning approach for wheel condition monitoring based on an adaptive parametric algorithm of blind source separation and extending K-means and singular value decomposition algorithm. Numerical simulations confirm the effectiveness of the proposed method. An experiment of wheel condition monitoring is conducted using a JD-1 wheel/rail simulation facility. Data calculation and theoretical analysis of wheel–rail contact dynamic show that the proposed method can adaptively learn and accurately identify wheel defects and verify the performance of the proposed method.