Online Pantograph-Catenary Contact Point Detection in Complicated Background Based on Multiple Strategies

Yang, Xuan; Zhou, Ning; Liu, Yueping; Quan, Wei; Lu, Xuemin; Zhang, Weihua

doi:10.1109/access.2020.3042535

Cited by 7 publications

(3 citation statements)

References 25 publications

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“…The proposed system involved the computing of the height of the pantograph (to detect a bow drop) and a SIFT-based approach to geolocate the fault on the railway line. The authors of reference [122] proposed a detection method for systems with double contact lines. The authors also introduce a new dataset, called PAC-TPL2020, collected using a high-resolution system installed on the roof of the train.…”

Section: B Pantograph and Arcsmentioning

confidence: 99%

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A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance

et al. 2022

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Within Artificial Intelligence, Deep Learning (DL) represents a paradigm that has been showing unprecedented performance in image and audio processing by supporting or even replacing humans in defect and anomaly detection. The Railway sector is expected to benefit from DL applications, especially in predictive maintenance applications, where smart audio and video sensors can be leveraged yet kept distinct from safety-critical functions. Such separation is crucial, as it allows for improving system dependability with no impact on its safety certification. This is further supported by the development of DL in other transportation domains, such as automotive and avionics, opening for knowledge transfer opportunities and highlighting the potential of such a paradigm in railways. In order to summarize the recent state-of-the-art while inquiring about future opportunities, this paper reviews DL approaches for the analysis of data generated by acoustic and visual sensors in railway maintenance applications that have been published until August 31st, 2021. In this paper, the current state of the research is investigated and evaluated using a structured and systematic method, in order to highlight promising approaches and successful applications, as well as to identify available datasets, current limitations, open issues, challenges, and recommendations about future research directions.

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Section: B Pantograph and Arcsmentioning

confidence: 99%

“…EMU Train Key Components [149], [150] Others [151] model for the detection of brace sleeve screws, however, it is not clear whether the dataset is available. The same issue applies to the PAC-TPL2020 dataset used in [122].…”

Section: E Datasetsmentioning

confidence: 99%

A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance

et al. 2022

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“…The traditional method relies on manual judgement. [15][16][17][18] The laser-displacement-sensor based detection algorithms have strong anti-interference ability, high accuracy, but high cost. [19][20][21] Image processing used for contact strip monitoring has been a research hotspot in recent years.…”

Section: Introductionmentioning

confidence: 99%

Modeling and analysis of transition-point disappearance in high-speed railway pantograph-catenary system

Chen,

Liu,

Guan

et al. 2023

Advances in Mechanical Engineering

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During the operation of high-speed railway, the transition-point disappearance phenomenon, which is caused by the deformation of pantograph head, poses a safety threat to the pantograph-catenary system. In this study, the analytical model for transition-point disappearance analysis is presented. The instantaneous profile, as well as the deformation process of the pantograph head under different contact force values and positions or different pantograph-head parameters can be solved using the model. Curve equation, force analysis, coordinate axis rotation, and few other methods are adopted to achieve simplified modeling. The proposed modeling method and analysis conclusion provide theoretical support for the permissible contact force range calculation and pantograph-head parameters optimization to prevent transition-point disappearance. The effectiveness of the proposed model is verified using both finite element simulation and experimental measurements. Finally, a case analysis for the prevention of transition-point disappearance is conducted, using pantographs with the models CX-GI and DSA250 as examples.

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Edge intelligence-based proposal for onboard catenary stagger amplitude diagnosis

Errandonea

Ciáurriz

Alvarado

et al. 2023

Computers in Industry

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Online Pantograph-Catenary Contact Point Detection in Complicated Background Based on Multiple Strategies

Cited by 7 publications

References 25 publications

A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance

A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance

Modeling and analysis of transition-point disappearance in high-speed railway pantograph-catenary system

Edge intelligence-based proposal for onboard catenary stagger amplitude diagnosis

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