A review of electrical signal-based train transmission machinery diagnosis technology

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.

Optical Hybrid Network Structure Based on Cloud Computing and Big Data Technology

“…The advantages of photoelectric hybrid network lie in the high efficiency and accuracy of signal transmission. The Internet of Things networking technology of photoelectric hybrid communication uses both optical signals and electrical signals to transmit information, which is naturally more efficient than the single application of a certain signal [2]. In addition, due to mixed communication, when a certain signal transmission medium fails, another signal transmission mode can replace it well, thus having the opportunity to troubleshoot the other medium without affecting the normal use of the Internet of Things.…”