Review on the Traction System Sensor Technology of a Rail Transit Train

Abstract

The development of high-speed intelligent rail transit has increased the number of sensors applied on trains. These play an important role in train state control and monitoring. These sensors generally work in a severe environment, so the key problem for sensor data acquisition is to ensure data accuracy and reliability. In this paper, we follow the sequence of sensor signal flow, present sensor signal sensing technology, sensor data acquisition, and processing technology, as well as sensor fault diagnosis technology based on the voltage, current, speed, and temperature sensors which are commonly used in train traction systems. Finally, intelligent sensors and future research directions of rail transit train sensors are discussed.

A Review in Fault Diagnosis and Health Assessment for Railway Traction Drives

“…Several sensors are located in a Railway traction drive. A review is presented in [21]. Current and voltage sensors, such as catenary current, motor phase current and DC-link voltage, are based on Hall-Effect.…”

“…The main faults in traction drives occur in sensors, power electronics devices and electric motors. In [21] the sensor technology in railway traction drives is presented. In case of faults, incipient or abrupt, the system performance is degraded and early fault diagnosis should be implemented in order to prevent a failure and improve the availability.…”

“…Furthermore, although during the last decade several publications related to fault diagnosis and health assessment in Railway traction drives have been published [25,[31][32][33], there is not a review, which summarizes all the research work done in Railway traction drives. Previous review works are focused on sensors more than in fault diagnosis [21] or on fault diagnosis in railway traction power supply [18].…”

Intelligent Diagnosis of Bogie Traction Seat Based on PCA-OVO and SVM Optimized by Modified Arithmetic Optimization Algorithm

“…Darong et al proposed an improved hidden Markov model (HMM) algorithm, which was applied to fault diagnosis of rail vehicle motor drive system to avoid disaster events to the maximum extent [4]. Feng et al discussed intelligent sensors and proposed sensor signal sensing technology, mainly from sensor data acquisition, processing technology, and voltage-based sensor fault diagnosis technology, which put forward ideas for the future research of rail transit train sensors [6]. For the bogie fault diagnosis of rail transit vehicles, the adaptive synthetic sampling approach, gradient boosting decision tree, is proposed [7], and it is helpful to detect bogie faults.…”