&lt;b&gt;Methods for Detecting Pantograph Defects Using Sensors Installed on Contact Lines&lt;/b&gt;

Koyama, Tatsuya; Usuda, Takayuki; Kawasaki, K.; Nakamura, Kazuki; Kawamura, Takahiro

doi:10.2219/rtriqr.57.3_207

Cited by 9 publications

(6 citation statements)

References 1 publication

(1 reference statement)

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“…Although various conditions such as train velocity can be changed in the simulation of the current collection system, the simulation results are affected by pantograph and overhead contact line (OCL) modelling errors. A test facility has already been developed at the Railway Technical Research Institute (RTRI) to measure this dynamic interaction [1], consisting of a tracked running device (representing the vehicle) that supports a pantograph and a linear catenary of length 400 m. This equipment can evaluate current collection performance, but the maximum velocity of the running device is limited to 200 km/h, which is not always sufficient for high-speed railway investigations. Moreover, the 'coasting section' of the track is approximately 70 m long, which is not always of sufficient length for higher speed investigations.…”

Section: Hybrid Simulation Testing Of a Pantograph-catenary System Using A Dynamically Substructured System Framework And A Mdof Catenarymentioning

confidence: 99%

<b>Hybrid Simulation Testing of a Pantograph-Catenary System Using a Dynamically Substructured System Framework and a MDOF Catenary Model</b>

et al. 2020

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This study proposes a hybrid simulation (HS) method for pantograph/catenary systems based on a dynamically substructured system (DSS) framework. In this method, the contact force between an actual pantograph and a hydraulic actuator is utilized to calculate the motion of the catenary in real-time, whilst the actuator is driven according to the calculated motion of the catenary. The advantage of the proposed method, when compared with commonlyused methods such as the inverse transfer function approach, is that DSS is better able to avoid instability that can be caused, for example, by pure delay characteristics in the actuator dynamics. The proposed method is also able to accurately represent dynamic interaction between the pantograph and the catenary. In this paper, the DSS methodology is introduced and then the proposed method is validated via simulation and experiment.

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Section: Hybrid Simulation Testing Of a Pantograph-catenary System Using A Dynamically Substructured System Framework And A Mdof Catenarymentioning

confidence: 99%

<b>Hybrid Simulation Testing of a Pantograph-Catenary System Using a Dynamically Substructured System Framework and a MDOF Catenary Model</b>

et al. 2020

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“…7 However, since the excitation signal is necessarily generated by engineers prior to the commencement of a test, this approach cannot easily accommodate the evolving dynamic interaction between the pantograph and the OCS. This critical dynamic interaction can be examined using large-scale test equipment already developed at the Railway Technical Research Institute (RTRI), 8 consisting of a tracked running device (representing the vehicle) that supports a pantograph and a linear catenary of length 400 m. However, the maximum velocity of the running device is limited to 200 km/h, which is not always sufficient for high-speed railway investigations.…”

Section: Introductionmentioning

confidence: 99%

New methods for dynamically substructured system testing of a railway car pantograph

Kobayashi

Koyama

Harada

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part F:

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This study proposes new pantograph testing methods for railway pantograph/overhead catenary systems (OCS), based upon substructured testing consisting of a physical pantograph and a numerical OCS model. Hence, this work builds upon a previously presented work, (using the dynamically substructured system approach developed by Stoten and Hyde), which was conducted on a relatively simple mechanical structure in the Automatic Control and Test Laboratory (ACTLab), University of Bristol, UK. In this current paper, the dynamically substructured system (DSS) testing method is applied to a real shinkansen pantograph, using various actuator/DSS configurations that have been implemented at the Railway Technical Research Institute, Tokyo, Japan. In the first of these tests, a conventional servohydraulic actuated rig is used to represent phenomena due to the dropper-passing frequency. Resulting DSS test data are compared with those generated by a numerical simulation of the emulated system, i.e. the system to be represented by the DSS experimentation. Then, in the second set of investigations, the DSS method is used in conjunction with a new ‘rotational disc’ test rig that is arranged to be in dynamic interaction with the shinkansen pantograph contact head. This novel experimental system enables the investigation of dynamic interactions between the overhead catenary system contact wire and the pantograph head, due to span-passing. Again, results from this experimental investigation are compared with those generated by a purely numerical simulation of the emulated system.

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“…Song et al [25] carried out a study that took into account the contact surface and the dynamic performance of pantograph catenary systems. Koyama et al [26] proposed a method in which they placed sensors on the contact line to detect wear in the pantograph and developed a sensor system with this method. In their work, they obtained data by placing a sensor system on the pantograph head.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Based Method for Detecting of Wear on the Current Collector Strips’ Surfaces of the Pantograph in Railways

Karaduman

Akın

2020

IEEE Access

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In pantographs, current collector strips transmit the electrical energy they receive from the catenary to the locomotive and provide the necessary power for the locomotive's movement. In order for the current collector strips to transmit electricity to the locomotive in a healthy way, their surface must be smooth. Wear on the surface of the current collector strips reduces conductivity and can create arcs, endangering the health and safety of the pantograph and catenary system. In this paper, a Convolutional Neural Network (CNN) architecture is developed to detect wear on the current collector strips. Images obtained from pantographs used on railways were created with a clean and improved data set using Hough Transform and Power Law Transform. The created dataset contains 909 pantograph images. This dataset was trained and tested with both the developed CNN architecture and classic deep learning architectures (ResNet50, VGG16). The experimental results show that the developed CNN architecture's training results and test results are more successful than classical architectures.

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<b>Methods for Detecting Pantograph Defects Using Sensors Installed on Contact Lines</b>

Cited by 9 publications

References 1 publication

<b>Hybrid Simulation Testing of a Pantograph-Catenary System Using a Dynamically Substructured System Framework and a MDOF Catenary Model</b>

<b>Hybrid Simulation Testing of a Pantograph-Catenary System Using a Dynamically Substructured System Framework and a MDOF Catenary Model</b>

New methods for dynamically substructured system testing of a railway car pantograph

A Deep Learning Based Method for Detecting of Wear on the Current Collector Strips’ Surfaces of the Pantograph in Railways

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