Optimization of Sensor Orientation in Railway Wheel Detector, Using Kriging Method

Ali Zamani; Ahmad Mirabadi

doi:10.4236/jemaa.2011.312080

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JEMAA> Vol.3 No.12, December 2011

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Optimization of Sensor Orientation in Railway Wheel Detector, Using Kriging Method

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DOI: 10.4236/jemaa.2011.312080 4,981 Downloads 8,353 Views Citations

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Ali Zamani, Ahmad Mirabadi

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ABSTRACT

Considering the importance of axle counter function in detecting the train wheels and determining the clearance or occupancy of a track section, it is important to ensure a safe and reliable performance of this system. In this paper, in order to improve the sensor performance, the authors have focused on the orientation of magnetic sensors’ coils. In order to improve the detection capability of the system, through measuring the induced voltage in the receiver coil, it is important to adjust the relative orientation of the transmitter and receiver coils. Due to the existence of infinite relative orientations, in order to determine the optimum orientation for the sensor coils, Kriging methods which is one of the Response Surface Methodologies (RSMs) is applied. Finite Element Method (FEM) is utilized to provide sample data, as inputs to the Kriging algorithm. The analysis not only provides the optimum relative orientation of the sensor coils, it also improves analysis time, comparing to field based measurements. The analysis results are validated by the laboratory based data implemented in the control and signaling laboratory of the school of railway engineering and also field based tests in Iranian railway.

KEYWORDS

Electromagnetic Sensor, Finite Element Method (FEM), Kriging, Optimization, Railway Axle Counter, Response Surface Methodology (RSM)

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

A. Zamani and A. Mirabadi, "Optimization of Sensor Orientation in Railway Wheel Detector, Using Kriging Method," Journal of Electromagnetic Analysis and Applications, Vol. 3 No. 12, 2011, pp. 529-536. doi: 10.4236/jemaa.2011.312080.

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