• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.25-31
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• 2013

The AVC System which has operated in Highways has two-piezo sensors. In this system the piezo sensors are installed on parally each other this configuration has a defect about diversion driving and sensor damage. In this reserch, 3-Sensor AVC algorithm has been proposed which is supported enhance accuracy of the vehicle classification rate compare with usual 2-Sensor systems. This algorithm is allowed to calculate wheel tread, wheel width. The third inclinded piezo sensor can detec twheel tread, wheel width using signal processing. 3-Sensor AVC has been installed in real highway and the outcome performance has been proof.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1940-1945
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• 2007

The wheelsets are one of most important component: damages in wheel tread and press fitted axle are a significant cost for railway industry. Since failure in railway wheelset can cause a disaster, regular inspection of defects in wheels and axles are mandatory. Ultrasonic testing, acoustic emission and eddy current testing method and so on regularly check railway wheelset in service. However, it is difficult to use this method because of its high viscosity and because its sensitivity is affected by temperature. Also, due to noise echoes it is difficult to detect defects initiation clearly with ultrasonic testing. It is necessary to develop a non-destructive technique that is superior to conventional NDT techniques in order to ensure the safety of railway wheelset. In the present paper, the new NDT technique is applied to the detection of surface defects for railway wheelset. To detect the defects for railway wheelset, the sensor for defect detection is optimized and the tests are carried out with respect to surface and internal defects each other. The results show that the surface crack depth of 1.5 mm in press fitted axle and internal crack in wheel could be detected by using the new method. The ICFPD method is useful to detect the defect that initiated in the tread of railway wheelset.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.12
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• pp.1237-1244
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• 2016

Vehicle classification system in domestic tollgates is usually to use treadle sensor for calculating wheel width and tread of the vehicle. Due to the impact that occurs when the wheels of the vehicle contact, treadle sensor requires high durability. Recently, KHC(Korea Highway Corporation) began operating high-speed lane for cargo truck. High-speed cargo truck generate more impact the design criteria of previous treadle. Therefore, an increase in the maintenance and management costs of the treadle damage is concerned. In this paper, we propose an algorithm to classify vehicles using non-contact treadle sensors for improving durability from physical impacts. This was based on the KHC's classification criteria and showed a classification accuracy of 99.5 % in one experiment with 1892 vehicles through Changwon tollgate in 1020 local road. Therefore, it shows that vehicle classification system using non-contact treadle sensor could be applied to domestic toll tollgates, effectively.