axle detection
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2020 ◽  
Vol 10 (21) ◽  
pp. 7485
Author(s):  
Hua Zhao ◽  
Chengjun Tan ◽  
Eugene J. OBrien ◽  
Nasim Uddin ◽  
Bin Zhang

Accurate vehicle configurations (vehicle speed, number of axles, and axle spacing) are commonly required in bridge health monitoring systems and are prerequisites in bridge weigh-in-motion (BWIM) systems. Using the ‘nothing on the road’ principle, this data is found using axle detecting sensors, usually strain gauges, placed at particular locations on the underside of the bridge. To improve axle detection in the measured signals, this paper proposes a wavelet transform and Shannon entropy with a correlation factor. The proposed approach is first verified by numerical simulation and is then tested in two field trials. The fidelity of the proposed approach is investigated including noise in the measurement, multiple presence, different vehicle velocities, different types of vehicle and in real traffic flow.



2018 ◽  
Vol 23 (8) ◽  
pp. 05018006 ◽  
Author(s):  
Hamed Kalhori ◽  
Mehrisadat Makki Alamdari ◽  
Xinqun Zhu ◽  
Bijan Samali


Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2376 ◽  
Author(s):  
Zbigniew Marszalek ◽  
Tadeusz Zeglen ◽  
Ryszard Sroka ◽  
Janusz Gajda

The article presents a measurement system that captures two components of a motor vehicle’s magnetic profile, which are associated with the real and imaginary part of the impedance of a narrow inductive loop sensor. The proposed algorithm utilizes both components of the impedance magnetic profile to detect vehicle axles, including lifted axles. Accuracies of no less than 71.8% were achieved for vehicles travelling with a lifted axle, and no less than 98.8% for other vehicles. The axle detection accuracy was determined during a series of experiments carried out under normal traffic conditions, using profile analysis, video footage and reference signals from an axle load detector on a total of 4000 vehicles.



2017 ◽  
Vol 7 (3) ◽  
pp. 325-332 ◽  
Author(s):  
Myra Lydon ◽  
D. Robinson ◽  
S. E. Taylor ◽  
G. Amato ◽  
E. J. O. Brien ◽  
...  




2012 ◽  
Vol 532-533 ◽  
pp. 908-913
Author(s):  
Yan Wang ◽  
Li Jun Zhang ◽  
Xiao Han ◽  
Zhao Yin

Axle detection is an important way to ensure the safety of rail transport. To meet the requirements of the Ministry of Railways, ZTY-1 type digital ultrasonic flaw detector is developed. It is designed based on VC++ 6.0 and runs on the PC system. The detector consists of five functional parts, which are flaw detecting, daily performance checking, quarterly performance checking, probe test and data management. In this paper, design of the detector’s software system is introduced, as well as solutions to some problems such as waveform flicker, double detection, waveform playback and document print.



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