High-Speed Trains (HSTs) have emerged as a mainstream mode of transportation in China, owing to their exceptional safety and efficiency. Ensuring the reliable operation of HSTs is of paramount economic and societal importance. As critical rotating mechanical components of the transmission system, bearings make their fault diagnosis a topic of extensive attention. This paper provides a systematic review of image encoding-based bearing fault diagnosis methods tailored to the condition monitoring of HSTs. First, it categorizes the image encoding techniques applied in the field of bearing fault diagnosis. Then, a review of state-of-the-art studies has been presented, encompassing both monomodal image conversion and multimodal image fusion approaches. Finally, it highlights current challenges and proposes future research directions to advance intelligent fault diagnosis in HSTs, aiming to provide a valuable reference for researchers and engineers in the field of intelligent operation and maintenance.

Due to the advantages of comfort and safety, high-speed trains are gradually becoming the mainstream public transport in China. Since the operating speed and mileage of high-speed trains have achieved rapid growth, it is more and more urgent to ensure their reliability and safety. As an important component in the bogies of high-speed trains, the health state of the bearing directly affects the operational safety of the trains. It is therefore necessary to diagnoze the faults of bearings in the bogies of high-speed trains as early as possible. In this paper, the bearing fault diagnostic methods for high-speed trains have been systematically summarized with their challenges and perspectives. First, it briefly introduces the structure of bearings in the bogies as well as the fault characteristic frequencies. Then, a brief review of the research on vibration-based signal processing methods and machine learning methods has been provided. Finally, the challenges and future developments of vibration-based bearing fault diagnostic methods for high-speed trains have been analyzed.