• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.1
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• pp.29-37
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• 2015

In this study, the estimation of axial load and total axial load was conducted using Bridge Weigh-in-Motion(BWIM) technique which generally consists of devices for measuring the strain induced in the bridge by the vehicles. axle detectors for collecting information on vehicle velocity and axle spacing. and data acquisition equipment. Vehicle driving test for the development of the BWIM system is necessary but it needs much cost and time. In addition, it demands various driving conditions for the test. Thus, we need a numerical-simulation method for resolving the cost and time problems of vehicle driving tests, and a way of measuring bridge response according to various driving conditions. Using a bridge model reflecting the dynamic characteristic contributes to increased accuracy in numerical simulation. In this paper, we conduct a numerical simulation which reflects the dynamic characteristic of a bridge using the Bridge Weigh-in-Motion technique, and suggest overload vehicle enforcement technology.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.111-123
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• 2006

In the design of bridges, exact evaluation of traffic loading is very important for the safety and maintenance of bridges. In general, traffic loading is represented by live load (including impact load) and fatigue load. For exact evaluation of traffic loading, it is important to get reliable and comprehensive truck data including the traffic and weight information. It requires the development of Bridge Weigh-In-Motion (BWIM), which measures the truck weights without stopping the traffic. Objectives of the study is (1) to develop the BWIM system, (2) to verified the system in bridges in Highways.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.6 s.52
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• pp.1-8
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• 2006

This paper describes the procedures developing the algorithm for analyzing signals acquired from the Bridge Weigh-in-Motion (BWIM) system installed in Seohae Bridge as a part of the bridge monitoring system. Through the analysis procedure, information about heavy traffics such as weight, speed, and number of axles are attempted to be extracted from time domain strain data of the BWIM system. One of numerous pattern recognition techniques, artificial neural network (ANN) is employed since it can effectively include dynamic effects, bridge-vehicle interaction, etc. A number of vehicle running experiments with sufficient load cases are executed to acquire training and/or test set of ANN. Extracted traffic information can be utilized for developing quantitative database of loading effect. Also, it can contribute to estimate fatigue lift or current health condition, and design truck can be revised based on the database reflecting recent trend of traffic.

• International Journal of Highway Engineering
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• v.13 no.4
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• pp.123-132
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• 2011

The purpose of this study is to calculate and propose rational multi-lane loading factors for bridge design considering the probability of simultaneous truck passing in adjacent lanes and real truck weights. The probability of simultaneous truck passing is calculated by analyzing video image taken at various locations in highways and national roads. Weigh-In-Motion system data at two locations are used, which is combined with the probability of multiple presence to calculate the multi-lane loading factors for typical 2 lane and 5 lane bridges. Statistical properties of multi-lane loading factors are also calculated assuming that locations for video images and WIM data represent the overall traffic condition in the country. Results are compared with various design codes in the world and they show that the values are between the current Korea Bridge Design Code and AASHTO LRFD specification or Eurocode and are similar to Canadian Code.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.3
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• pp.57-67
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• 2021

A thorough administration of the arterial road network requires a continuous supply of updated and accurate information about the traffic that travels on the roads. One of the ways to effectively obtain the traffic volume and weight distribution of heavy vehicles is the BWIM technique, which is actively being studied. Unlike previous studies, this study was performed to develop a simplified Bridge Weigh-In-Motion (BWIM) algorithm that can easily estimate the axle spacing and weight of a traveling vehicle by utilizing the structural characteristics of the bridge. A short span RC T-beam bridge with no crossbeam installed was selected for the study, and then the strain response characteristics of bridge deck and girder was checked through preliminary field test. Based on the preliminary field test results, a simplified BWIM algorithm suitable for the bridge to be studied was derived. The validity and accuracy of the BWIM algorithm derived in this study were verified through field test. As a result of the verification test, the proposed BWIM algorithm can estimate the axle spacing and gross weight of the travelling vehicles with the average percent error of less than 3%.

• Journal of the Korean Society of Safety
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• v.27 no.1
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• pp.86-95
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• 2012

The BWIM(Bridge Weigh-In-Motion) is a technology to identify vehicle properties, such as weight, speed, axle spacing and running lane, passing over a bridge by using dynamic response of bridge member. Such information will be used for assessing durability and establishing a maintenance strategy of roadway structures. In this paper, as a first step for developing BWIM system, analytical and experimental studies were conducted in order to verify whether the response of vertical stiffener in steel girder bridge can be used to identify vehicle properties running on the bridge. It was known from this study that such vehicle information could be estimated reasonably by using strain time history curve of a vertical stiffener due to running vehicles. It is because the effect of each axle-load of vehicle appears definitely in the curve. However, as the magnitude of strain of vertical stiffener is effected by running pattern of vehicles, further study is necessary to reduce error when estimating vehicle weight.

• Journal of the Korea institute for structural maintenance and inspection
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• v.15 no.2
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• pp.70-78
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• 2011

The paper aims at developing a more reliable and accurate BWIM(Bridge Weigh-In-Motion) algorithm using measured strain data and examining its efficiency with various tests on bridges. It proposes a BWIM algorithm using density estimation function and average modification factor for moment-strain relationship. Density estimation function has been proved to be reliably applied when multiple axle loads are estimated. An average modification factor is applied to minimize overall error that can be encountered between theoretically computed moments and measured strains at multiple locations in a bridge. The developed algorithm has been successfully examined through numerical simulations, laboratory tests, and also by field tests on a multi-girder composite bridge.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.187-196
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• 2010

The purpose of this study is to develop the calibration method for temperature effects to improve the accuracy of the Weigh-In-Motion(WIM) system for collecting long-term truck weight data. WIM system was installed at a location where the truck traffic volume is high and weight data has been collected from January 2010. In this study, as a calibration measure, the first axle weight of Truck Type 10, the semi tractor-trailer is used based on the fact that the first axle weight is relatively constant, independent of the cargo weight. From this fact, calibration equations are developed from the relationship between the axle weight and the temperature(daily mean, maximum and minimum). Analysis on calibrated weight data shows adequacy of the proposed calibration method. Results of this study can be used to improve the accuracy of the WIM system and to carry out more rational design of pavement and bridge structures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.143-153
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• 2006

In design of bridges, estimation of actions and loadings is very important for the safety and maintenance of bridges. In general, effect of traffic loading on the bridge can be modeled as live load (including impact load) and fatigue load. For estimation of traffic loading, it is important to get reliable and comprehensive truck statistical data such as the traffic and weight information. To get statistical data, Bridge Weigh-In-Motion (BWIM), which measures the truck weights without stopping the traffic, is need to be developed. In this study, BWIM system with various functions is developed first. Then this system is used to get comprehensive truck data. Traffic loadings including fatigue and live loading are formulated from the truck data acquired from the bridges. Objectives of this study are to develop the BWIM system, to apply the system in test bridge in Highway, and to formulate the live and fatigue loading for bridge design.

• Structural Engineering and Mechanics
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• v.20 no.1
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• pp.85-110
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• 2005

This paper aims at formulating various statistical models for the study of a ten year Weigh-in-Motion (WIM) data collected from various WIM stations in Hong Kong. In order to study the bridge live load model it is important to determine the mathematical distributions of different load affecting parameters such as gross vehicle weights, axle weights, axle spacings, average daily number of trucks etc. Each of the above parameters is analyzed by various stochastic processes in order to obtain the mathematical distributions and the Maximum Likelihood Estimation (MLE) method is adopted to calculate the statistical parameters, expected values and standard deviations from the given samples of data. The Kolmogorov-Smirnov (K-S) method of approach is used to check the suitability of the statistical model selected for the particular parameter and the Monte Carlo method is used to simulate the distributions of maximum value stochastic processes of a series of given stochastic processes. Using the statistical analysis approach the maximum value of gross vehicle weight and axle weight in bridge design life has been determined and the distribution functions of these parameters are obtained under both free-flowing traffic and dense traffic status. The maximum value of bending moments and shears for wide range of simple spans are obtained by extrapolation. It has been observed that the obtained maximum values of the gross vehicle weight and axle weight from this study are very close to their legal limitations of Hong Kong which are 42 tonnes for gross weight and 10 tonnes for axle weight.