Design Optimization of Magnetic Sensor for Train Detection

Yasukawa, Shogo; Takagi, Naoko; Dong, Gege; Wakao, Shinji; Takahashi, Masahide; Yagi, Makoto; Okutani, Tamio

doi:10.1109/tmag.2014.2358379

Cited by 13 publications

(3 citation statements)

References 9 publications

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“…In one architecture the detector is used only for detecting the presence of a wheel of the rolling stock [9], while in the other architecture a wheel detector is responsible for detecting and counting the wheels passing the point where it is installed. Yasukawa et al [10] designed an optimization of the axle counter through large-scale magnetic field computations. They estimated the signaling level by applying infinite edge elements to an extensive air domain.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Filtering Methods for Enhanced Reliability of a Train Axle Counter System

Grzechca

Szczeponik

2020

Sensors

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This paper presents signal filtering methods that can be effectively applied to train detection systems based on the axle counter systems that are currently in operation for train detection and provide information on the unoccupied status of railway tracks and turnouts. Signals from the wheel detectors contain noise, may be impulsive and time-varying, which means that even for the same train, the signals from the following wheels may be different. A problem appears when already homologated hardware (axle counter system) is working in a harsh environment, exposed to disturbances whose parameters significantly exceed standard thresholds. Despite this, the system must continue to provide reliable information. The authors present research on the application of such filters as median, Savitzkey-Golay, and moving average which can be implemented in the equipment currently in use under specific constraints (e.g., limited computational resources). The research results show that appropriately adjusted filters, for example, in terms of type and window size, increase the signal quality and thereby provide reliable information about passing trains, as well as enhance the availability and safety of the axle counter system performance.

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Section: Introductionmentioning

confidence: 99%

Comparison of Filtering Methods for Enhanced Reliability of a Train Axle Counter System

Grzechca

Szczeponik

2020

Sensors

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“…Zamani and Mirabadi (2012, 2011a, 2011b determined the installation angle of excitation and induction coils by calculating the electromagnetic field distribution of bilateral sensor using the finite element method (FEM). Shogo et al (Yasukawa et al, 2015) analyzed electromagnetic field distribution when the train and the sensor were located at deferent positions. They determined the optimum spatial relationship between excitation coil, induction coils and the track by calculating the electromagnetic field distribution in different situations, and then chose the optimum installation angles for the coils.…”

Section: Introductionmentioning

confidence: 99%

Design optimization of key components’ spatial position of unilateral axle counting sensor

Tong

Liu

Jin

et al. 2018

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Purpose The unilateral axle counting sensor is an important railway signal device that detects a train. For efficient and stable detection, the amplitude of induced electromotive force and its changes must be big enough. Therefore, the purpose of this study is to find a way to design and optimize the sensor structure quickly and accurately. Design/methodology/approach With the help of extensive electromagnetic field calculations, the study puts forward a modified model based on the finite element method, establishes an independent air domain around the sensor, wheel and the railway and adopts a unique grid division method. It offers a design optimization method of the induction coil angles and its spatial location with respect to the excitation coil by using the combination weighting algorithm. Findings The modified modeling method can greatly reduce the number of finite element mesh and the operation time, and the method can also be applied to other areas. The combination weighting algorithm can optimize the structure of the sensor quickly and accurately. Originality/value This study provides a way to design and optimize the structure of the sensor and a theoretical basis for the development. The results can improve and expand the technology of the axle counting sensor.

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“…Other studies applied some novel components, such as giant magneto-resistive sensors and microwave balises, to train detection systems (8,9). Yasukawa et al (10) introduced a new idea that improves the train detection system by changing the positions of the sensors.…”

mentioning

confidence: 99%

Template-Based Voting Logic for Dual Train Detection Systems

Hsueh,

Chang,

Lai

2023

Transportation Research Record: Journal of the Transportation R

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A train detection system is crucial in railway signaling and control systems. To improve the reliability and safety of train detection systems, the conventional railway operator in Taiwan, Taiwan Railways Administration (TRA), adopted dual detection systems for each signal block. However, conventional design logics for dual detection systems cannot fully and simultaneously improve reliability and safety. Thus, in this research, an innovative logic is proposed, namely, template-based voting (TBV) logic, to automatically correct possible train detection errors on the basis of preprocessed simulation data. The TBV logic first applies a “template generation module” to generate and store all possible train movement data in a database. Then an “occupation status comparing module” executes the standard or special process to trace passing trains and correct possible detection errors on the basis of the templates. Results of case studies and a sensitivity analysis demonstrate that this logic outperforms other existing logics with respect to integrated performance in reliability and safety. Thus, the application of this logic can substantially improve the reliability and safety of a dual train detection system with fixed blocks.

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Design Optimization of Magnetic Sensor for Train Detection

Cited by 13 publications

References 9 publications

Comparison of Filtering Methods for Enhanced Reliability of a Train Axle Counter System

Comparison of Filtering Methods for Enhanced Reliability of a Train Axle Counter System

Design optimization of key components’ spatial position of unilateral axle counting sensor

Template-Based Voting Logic for Dual Train Detection Systems

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