Data-Driven Fault Diagnosis for Traction Systems in High-Speed Trains: A Survey, Challenges, and Perspectives

Chen, Hongtian; Jiang, Bin; Ding, Steven X.; Huang, Biao

doi:10.1109/tits.2020.3029946

Cited by 293 publications

(122 citation statements)

References 151 publications

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“…In recent years, the neural network-based methods have been widely applied in intelligent transportation systems [13][14][15], intelligent video surveillance [16,17], automatic monitoring [18,19], and industrial inspection [20,21] fields. By improving the Faster R-CNN network model, Sun et al realized the detection of scratch, oil pollution, block, and grinning four kinds of wheel hub defects quickly and accurately [22].…”

Section: Application Of the Industrial Inspection Based On Dcnnsmentioning

confidence: 99%

Offset Detection of Grate Trolley’s Side Plate Based on YOLOv4

Wang

Fang

et al. 2021

Journal of Sensors

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Side plate offset is one of the grate system faults. If it is not dealt with in time, some accidents will occur and economic losses will be made. Aiming at the problems like time-consuming, labour-wasting, and low intelligent by the side plate offset detection method manually, an autoside plate offset detection method is proposed, based on You Only Look Once version 4 (YOLOv4). Two cameras were fixed to collect the image information of the grate trolley’s side plate. With reference to the grate trolley’s operation, the offset judgment rules were set. YOLOv4 object detection algorithm was used to detect the side plate and trolley’s chassis frame in video frame images. A baseline was set according to the position information of the trolley’s chassis frame output by detection, and then, the position intervals between side plates and the baseline could be determined by calculation. According to the judgment rules, the scheme in this paper could detect the offset fault of the trolley’s side plate timely, and an alarm would be made automatically when faults are detected. Our video images of the trolley’s side plate were collected and sorted in Baogang Group sintering plant for testing. In this experiment, no error judgment was made, and the average detection and judgment time was 0.024 s. In this paper, rather than manually, the real-time automatic detection was realized to detect the offset fault of the trolley’s side plate so as to provide a new solution for offset detection of the grate trolley’s side plate.

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Section: Application Of the Industrial Inspection Based On Dcnnsmentioning

confidence: 99%

Offset Detection of Grate Trolley’s Side Plate Based on YOLOv4

Wang

Fang

et al. 2021

Journal of Sensors

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“…Obviously, when a fault appears in high-speed trains, there may be multiple variables affected. In most cases, other state variables are also implicated [ 108 ]. Therefore, it is necessary to make a comprehensive analysis of these state variables.…”

Section: Applications Of Qualitative Ifd Approach In High-speed Trmentioning

confidence: 99%

A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches

Cheng

Wang

Chen

et al. 2020

Entropy

Self Cite

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For ensuring the safety and reliability of high-speed trains, fault diagnosis (FD) technique plays an important role. Benefiting from the rapid developments of artificial intelligence, intelligent FD (IFD) strategies have obtained much attention in the field of academics and applications, where the qualitative approach is an important branch. Therefore, this survey will present a comprehensive review of these qualitative approaches from both theoretical and practical aspects. The primary task of this paper is to review the current development of these qualitative IFD techniques and then to present some of the latest results. Another major focus of our research is to introduce the background of high-speed trains, like the composition of the core subsystems, system structure, etc., based on which it becomes convenient for researchers to extract the diagnostic knowledge of high-speed trains, where the purpose is to understand how to use these types of knowledge. By reasonable utilization of the knowledge, it is hopeful to address various challenges caused by the coupling among subsystems of high-speed trains. Furthermore, future research trends for qualitative IFD approaches are also presented.

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“…Inspired by fault estimation techniques, the alarm system failures and the suitable acts are decided as soon as possible to avoid heavy damages and dangerous situations. The idea of fault detection and identification (FDI) method becomes a powerful tool to reach the information of a sensor fault as well as an actuator fault [22]- [25]. In order to deploy the mentioned aim, several observer strategies have been investigated to estimate sensor faults such as adaptive observer [26]- [28], extended Kalman filter [29], [30], and Takagi-Sugeno fuzzy observer [17], [31].…”

Section: Introductionmentioning

confidence: 99%

Robust Fault-Tolerant Control of an Electro-Hydraulic Actuator With a Novel Nonlinear Unknown Input Observer

Phan

Dao

et al. 2021

IEEE Access

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In this paper, a novel adaptive fault-tolerant controller is proposed for a typical electrohydraulic rotary actuator in the presence of disturbances, internal leakage fault, and sensor fault simultaneously. To construct the suggested controller, a nonlinear unknown input observer is developed to effectively identify the sensor fault, which is unaffected by not only internal leakage fault but also mismatched disturbances/uncertainties. Furthermore, a radial basis function neural network is designed to compensate for the mismatched disturbances/uncertainties caused by payload variation and unknown friction nonlinearities. Besides, an adaptive law based on the projection mapping function is applied to tackle the effect of the internal leakage fault. The integration of the above-mentioned techniques into the adaptive backstepping terminal sliding mode is investigated to obtain high tracking performance, robustness as well as fast convergence. The stability of the closed-loop system is proven by the Lyapunov theory. Finally, the capability and effectiveness of the proposed approach are validated via simulation results under various faulty scenarios.

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Data-Driven Fault Diagnosis for Traction Systems in High-Speed Trains: A Survey, Challenges, and Perspectives

Cited by 293 publications

References 151 publications

Offset Detection of Grate Trolley’s Side Plate Based on YOLOv4

Offset Detection of Grate Trolley’s Side Plate Based on YOLOv4

A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches

Robust Fault-Tolerant Control of an Electro-Hydraulic Actuator With a Novel Nonlinear Unknown Input Observer

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