• 한국구조물진단유지관리공학회지
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• 제16권2호
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• pp.22-31
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• 2012

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 봄 학술발표회 논문집
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• pp.451-460
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• 2003

In this paper, high speed fiber optic sensor weigh-in motion (WIM) system is proposed. Bragg gratings which have several advantages such as good reproducibility and good multiplicity compare to other optical fiber sensors are used for the system. Fabry-Perot filter for the signal process, which cannot be used in the high speed measurement because of the limitation in fast operation of PZT, is excluded. A new signal processing system which employs bandwidth filter is proposed and bridge type new sensor package design is also proposed. Design of the mold supporter is modified to round shape and then supporting points do not change. The data from the fiber sensors show identical and linear behavior to the axle weight. The proposed fiber optic WIM system is tested in the laboratory and experimented with actual trucks. The new concept of calibration is introduced and calculated by the experiments. The calibrated weight data show good approximations to real axial weights regardless the velocities of the truck.

• 한국구조물진단유지관리공학회 논문집
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• 제7권2호
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• pp.125-134
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• 2003

교량의 현 내하력을 평가하기 위해서 사용되는 방법으로 허용응력 평가법(ASR), 하중계수평가법 (LFR) 등의 방법 등이 사용되고 있다. 현재, 교랑 평가 값을 이용하여 이 값을 확률이론에 연결시키려는 시도들이 많이 연구되고 있다. 본 논문의 주목적은 교량의 내하력 평가값 (Rating Factor)과 확률이론을 이용하여, 과하중 확률을 구하는데 있습니다. 본 논문에서는 이러한 평가 방법들을 요약 설명하고, Weigh-in-Motion에 의해 얻은 활하중 모델을 도입하여, 교량 평가 값을 확률이론에 연결 시켰다. 활하중 모델과 교량 내하력 값을 토대로, 초과 하중 확률을 계산하고, 그 방법을 설명하였다.

• 한국강구조학회 논문집
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• 제11권2호통권39호
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• pp.223-232
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• 1999

도로상의 교량이나 기타구조물의 설계 및 유지관리를 위해서 도로상을 주행하는 중차량의 통행자료가 필요하다. 현재 국내에서 주로 이용되는 정적인 측정은 많은 시간과 인원이 필요하고 차종분포나 차간거리등은 수집할 수 없다. 특히 위치가 노출되어 신뢰성있는 자료을 얻지 못하는 단점이 있다. BWIM시스템은 교량을 이용하여 차량을 정지시키지않고 중량을 계측하는 시스템으로 정확하고 광범위한 자료를 얻을 수 있는 장치이다. 본 연구에서는 국내에서는 처음으로 BWIM시스템을 교량에 설치하여 그 적용성을 검증하고 시스템으로부터 얻어지는 여러 가지 자료를 분석하였다. 또한 과적검문소자료, Toll Gate자료 등 다른 방법에 의한 수집자료와 비교분석하여 일일교통량, 중량분포, 대표차량, 과적차량현황 등 여러가지 중차량의 통행특성들을 구하였다.

• Structural Monitoring and Maintenance
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• 제9권4호
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• pp.323-336
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• 2022

Steel truss bridge is one of the most widely used bridge types in Indonesia. Out of all Indonesia's national roads, the number of steel truss bridges reaches 12% of the total 17,160 bridges. The application of steel truss bridges is relatively high considering this type of bridge provides advantages in the standardization of design and fabrication of structural elements for typical bridge spans, as well as ease of mobilization. Directorate of Road and Bridge Engineering, Ministry of Works and Housing, has issued a standard design for steel truss bridges commonly used in Indonesia, which is designed against the design load in SNI 1725-2016 Bridge Loading Standards. Along with the development of actual traffic load measurement technology using Bridge Weigh-in-Motion (B-WIM), traffic loading data can be utilized to evaluate the reliability of standard bridges, such as standard steel truss bridges which are commonly used in Indonesia. The result of the B-WIM measurement on the Central Java Pantura National Road, Batang - Kendal undertaken in 2018, which supports the heaviest load and traffic conditions on the national road, is used in this study. In this study, simulation of a sequences of traffic was carried out based on B-WIM data as a moving load on the Australian type Steel Truss Bridge (i.e., Rangka Baja Australia -RBA) structure model with 60 m class A span. The reliability evaluation was then carried out by calculating the reliability index or the probability of structural failure. Based on the analysis conducted in this study, it was found that the reliability index of the 60 m class Aspan for RBA bridge is 3.04 or the probability of structural failure is 1.18 × 10^-3, which describes the level of reliability of the RBA bridge structure due to the loads from B-WIM measurement in Indonesia. For this RBA Bridge 60 m span class A, it was found that the calibrated nominal live load that met the target reliability is increased by 13% than stated in the code, so the uniform distributed load will be 7.60 kN/m² and the axle line equivalent load will be 55.15 kN/m.

• 한국소음진동공학회논문집
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• 제20권7호
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• pp.620-628
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• 2010

Using the responses of deck plate, a new bridge weigh-in-motion system has been introduced. The approach includes not only a systematic algorithm for the extraction of moment influence sequence but also a sensitivity-based system identification technique. The algorithm indentifies the influence sequence, the axle loads, and axle location of moving vehicles on a bridge, simultaneously. The accuracy and practicability of the algorithm have been examined experimentally for a folded deck plate on Yongjong Grand suspension bridge. It turns out that the two-dimensional effects of the behavior of deck plate should be considered for further accuracy improvement.

• Smart Structures and Systems
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• 제17권6호
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• Structural Engineering and Mechanics
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• 제76권1호
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• pp.1-15
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• 2020

The aim of this paper is to simply present live load factor calculation methodology formulation with the addition of a simple new future load projection procedure to previously proposed two methods. For this purpose, Oregon Weigh-in-Motion (WIM) data were used to calculate live load factors by using WIM data. These factors were calculated with two different approaches and by presenting new simple modifications in these methods. A very simple future load projection method is presented in this paper. Using four different WIM sites with different average daily truck traffic (ADTT) volume, and all year data, live load factors were obtained. The live load factors, were proposed as a function of ADTT. ADTT values of these sites correspond to three different levels which are approximately ADTT= 5,000, ADTT = 1,500 and ADTT ≤ 500 cases. WIM data for a full year were used from each site in the calibration procedure. Load effects were projected into the future for the different span lengths considering five-year evaluation period and seventy-five-years design life. The live load factor for ADTT=5,000, AASHTO HS20 loading case and five-year evaluation period was obtained as 1.8. In the second approach, the methodology established in the Manual for Bridge Evaluation (MBE) was used to calibrate the live load factors. It was obtained that the calculated live load factors were smaller than those in the MBE specifications, and smaller than those used in the initial calibration which did not convert to the gross vehicle weight (GVW) into truck type 3S2 defined by AASHTO equivalents.

• 한국안전학회지
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• 제24권4호
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• pp.53-58
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• 2009

The importance of process for repair and reinforcement of the bridge is increasing because of the lack of the fatigue load and stress, a lowering of the bridge load carrying capacity owing to impact and oscillation, deterioration on cultivation periods of the bridge, etc. Typically the experimenter values the bridge load carrying capacity by the real rating factor and response modification factor in bridge load rating through static load test and dynamic load test. But the error occurred in reliability of response modification factor in bridge load rating according to experience of experimenter. so tests of connecting probability theory and valuation of the bridge recently. The study is to compute the real load carrying capacity of the bridge and the rating factor and response modification factor on grade of the bridge, and calculate the probability of over-loaded truck load from Weigh In Motion(WIM) Data in FORTRAN programming applying to Monte-Carlo Simulation. At the result of this study, it is acquired that the new grade is computed for the probability of over-loaded truck load and surface inspection. The A grade is over 1.95, B grade is $1.55{\sim}1.94$, C grade is $1.26{\sim}1.54$, D grade is $1.14{\sim}1.25$, E grade is under 1.13 of rating factor, respectively.

• 대한토목학회논문집
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• 제28권5A호
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• pp.673-683
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• 2008

본 연구는 PSC I 거더교량을 대상으로 포장층에 축감지기가 없이 오로지 교량 상부구조 하면에서 측정한 변형률 신호만을 이용하는 차량하중분석시스템 개발에 관한 것이다. 중 차량이 교량을 주행할 때 교량 바닥판에서 측정한 변형률 신호로 차량주행정보를 추출하고, 교량 거더 및 가로보에서 측정한 변형률 신호로 차량하중정보를 추출하는 방법이다. 이러한 정보 분석을 위하여 영향선 분석방법과 인공신경망 분석방법을 사용하였다. 학습 데이터 확보 및 시스템 검증을 위하여 임의차량 및 시험차량 주행시험을 실시하였다. 대상 교량에서 하중분석결과, 가로보 변형률 신호를 이용한 경우가 거더 변형률 신호를 이용한 경우보다 더 정확한 결과를 나타내었고, 차선당 2열로 설치된 교량 바닥판 슬래브의 변형률 신호를 이용한 피크 검출 알고리즘도 차량의 속도와 축 수, 주행 차선, 축간 거리, 차간 거리 등의 주행정보를 추출하는데 매우 효과적임을 확인하였다. 또한, 가로보의 변형률 신호를 가지고 인공신경망 학습을 하여 시스템을 구성할 수 있는 경우가 기존의 거더 변형률 신호와 영향선만으로 시스템을 구성하는 경우보다 더 정확한 결과를 얻을 수 있음도 확인 하였다.