• Proceedings of the KIEE Conference
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• 2000.11b
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• pp.405-407
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• 2000

The most generally implemented method to detect the ground speed of the railway vehicles is to use the rotary type speed sensor attached to wheel axle. The Slip or sliding phenomenon on the railway vehicles occurs frequently caused by the weak viscosity of the wheel. Thus, precisely to control the car, the slip/sliding detection system is required. In this paper we proposed for the speed data management system, which uses rotary type speed sensor. Proposed speed management system can detect the slip/sliding with wheel axle as well as correct the generated speed error during in error time, to provide accurate speed and precise location data. The effectiveness for adapting to the railway system is clarified by the computer simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1303-1310
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• 2016

The track circuit carries out a train detection using a electrical closed loop, and incidentally it detects the rail rupture using the track circuit current flowing rail. However, in the case of the axle counter or the Radio based train control system, it requires a new way for detecting the rail rupture because of not using the track circuit. To solve this problem, it periodically checks non-steady state of rail by the track inspection car. but real-time detection of the rail rupture is impossible. Therefore, this paper analyzed feasibility to realize a real-time detection of rail rupture by using the return current.

• Smart Structures and Systems
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• v.19 no.2
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• pp.151-161
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• 2017

A new method is developed to estimate road profile in order to estimate IRI based on the ASTM standard. This method utilizes an accelerometer and a Dynamic Tire Pressure Sensor (DTPS) to estimate road roughness. The accelerometer measures the vertical axle acceleration. The DTPS, which is mounted on the tire's valve stem, measures dynamic pressure inside the tire while driving. Calibrated transfer functions are used to estimate road profile using the signals from the two sensors. A field test was conducted on roads with different quality conditions in the city of Brockton, MA. The IRI values estimated with this new method match the actual road conditions measured with Pavement Condition Index (PCI) based on the ASTM standard, images taken from an onboard camera and passengers' perceptions. IRI has negative correlation with PCI in general since they have overlapping features. Compared to the current method of IRI measurement, the advantage of this method is that a) the cost is reduced; b) more space is saved; c) more time is saved; and d) mounting the two sensors are universally compatible to most cars and vans. Therefore, this method has the potential to provide continuous and global monitoring the health of roadways.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.1059-1068
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• 2016

The current operation method for the AVC (Automatic Vehicle Classification) equipment does not generate vehicle speed, traffic volume and vehicle type information when part of the sensors has failed. Inefficiency of current methods would not use the collected data from the normal sensor. In this study was conducted research on the calculating method at the traffic volume and vehicle speed in the sensor failure AVC equipment. The failure situation of the sensor was classified into 4 types. Calculating the traffic volume and vehicle speed information for each type, and accuracy of these informations were analyzed. Analysis results, traffic volume was possible to calculate a highly accurate value (accuracy: 100%, 98%, 97%). In the case of speed, the accuracy of the calculated speed value reaches a level that can be accepted sufficiently (RMSE value is less than 16.8). So, using the methodology proposed in this study are expected to be able to increase the operational efficiency of the AVC equipment.