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Sensors 2018, 18(9), 3044; https://doi.org/10.3390/s18093044

Effects of Sensor Location on Dynamic Load Estimation in Weigh-in-Motion System

State Key Laboratory of Software Development Environment, School of Mechanical Engineering & Automation, Beihang University, Beijing 100083, China
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Received: 15 July 2018 / Revised: 21 August 2018 / Accepted: 3 September 2018 / Published: 12 September 2018
(This article belongs to the Section Physical Sensors)
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Abstract

In recent years, weigh-in-motion systems based on embedded sensor networks have received a lot of attention. However, how to improve the accuracy of multi-sensor weigh-in-motion (WIM) systems while keeping costs low remains a challenge. In this paper, a numerical simulation method is presented to analyze the relationship between sensor location and the accuracy of static weight estimation. The finite element model of a WIM system is developed, which consists of three parts: a pavement model, a moving load model and two types of sensor models. Analysis of simulation results shows that the ability of sensing dynamic load is closely related to the installation depth of sensors and pavement material. Moreover, the distance between the moving wheel and sensors has a great impact on estimating performance. Gaussian curve fitting could be used to reduce weighing error within a limited range. Our work suggests that much more attention should be paid to the design of the sensor layout of a WIM system. View Full-Text
Keywords: weigh-in-motion; embedded sensor network; sensor layout weigh-in-motion; embedded sensor network; sensor layout
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Qin, T.; Lin, M.; Cao, M.; Fu, K.; Ding, R. Effects of Sensor Location on Dynamic Load Estimation in Weigh-in-Motion System. Sensors 2018, 18, 3044.

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