A review of electrical signal-based train transmission machinery diagnosis technology. Issue 3 (14th September 2021)

• Record Type: Journal Article
• Authors: Dai, Jisheng; Ding, Rongjun; Guan, Zhaoyi; Xu, Shaolong
• Is Part Of: Transportation safety and environment. Volume 3:Issue 3(2021)
• Publication Date: 2021-09-14
• Subjects: transmission machinery -- fault diagnosis -- bearing -- gear -- machine learning -- signal processing -- rail transportation; Transportation engineering -- Periodicals; Transportation -- Safety measures -- Periodicals; 629.04
• DOI: 10.1093/tse/tdab013
• Languages: English
• ISSNs: 2631-4428

Abstract

Abstract: Transmission machinery is widely used in railway vehicles and is an important component in driving the operation of trains. Such transmission components are prone to faults under long exposure to harsh environments and complex working conditions. This affects normal operation and order, and thus it is important to ensure their safe and reliable operation. Electrical signal-based diagnosis technology has advantages of easy signal acquisition, with no need to install additional sensors, nor embedded monitoring of the object components. It has gradually become a research hotspot in the field of rail transportation diagnosis. This paper describes the fault modes of transmission machinery, takes the electrical signal-based diagnosis method as the entry point, collates and compares the existing diagnosis methods and research results in this field. It analyses their advantages and disadvantages, and finally puts forward problems for current and future research and development.