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Academic literature on the topic 'Wegh in Motion Systems'

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Published: 10 March 2023

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Journal articles on the topic "Wegh in Motion Systems"

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Sonmez, Umit, Nina Sverdlova, Robin Tallon, David Klinikowski, and Donald Streit. "Static calibration methodology for weigh-in-motion systems." International Journal of Heavy Vehicle Systems 7, no. 2/3 (2000): 191. http://dx.doi.org/10.1504/ijhvs.2000.004836.

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Cebon, D. "Design of Multiple-Sensor Weigh-in-Motion Systems." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 204, no. 2 (April 1990): 133–44. http://dx.doi.org/10.1243/pime_proc_1990_204_145_02.

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Stawska, Sylwia, Jacek Chmielewski, Magdalena Bacharz, Kamil Bacharz, and Andrzej Nowak. "Comparative Accuracy Analysis of Truck Weight Measurement Techniques." Applied Sciences 11, no. 2 (January 14, 2021): 745. http://dx.doi.org/10.3390/app11020745.

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Roads and bridges are designed to meet the transportation demands for traffic volume and loading. Knowledge of the actual traffic is needed for a rational management of highway infrastructure. There are various procedures and equipment for measuring truck weight, including static and in weigh-in-motion techniques. This paper aims to compare four systems: portable scale, stationary truck weigh station, pavement weigh-in-motion system (WIM), and bridge weigh-in-motion system (B-WIM). The first two are reliable, but they have limitations as they can measure only a small fraction of the highway traffic. Weigh-in-motion (WIM) measurements allow for a continuous recording of vehicles. The presented study database was obtained at a location that allowed for recording the same traffic using all four measurement systems. For individual vehicles captured on a portable scale, the results were directly compared with the three other systems’ measurements. The conclusion is that all four systems produce the results that are within the required and expected accuracy. The recommendation for an application depends on other constraints such as continuous measurement, installation and operation costs, and traffic obstruction.
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Burnos, Piotr, Janusz Gajda, Ryszard Sroka, Monika Wasilewska, and Cezary Dolega. "High Accuracy Weigh-In-Motion Systems for Direct Enforcement." Sensors 21, no. 23 (December 1, 2021): 8046. http://dx.doi.org/10.3390/s21238046.

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In many countries, work is being conducted to introduce Weigh-In-Motion (WIM) systems intended for continuous and automatic control of gross vehicle weight. Such systems are also called WIM systems for direct enforcement (e-WIM). The achievement of introducing e-WIM systems is conditional on ensuring constant, known, and high-accuracy dynamic weighing of vehicles. WIM systems weigh moving vehicles, and on this basis, they estimate static parameters, i.e., static axle load and gross vehicle weight. The design and principle of operation of WIM systems result in their high sensitivity to many disturbing factors, including climatic factors. As a result, weighing accuracy fluctuates during system operation, even in the short term. The article presents practical aspects related to the identification of factors disturbing measurement in WIM systems as well as methods of controlling, improving and stabilizing the accuracy of weighing results. Achieving constant high accuracy in weighing vehicles in WIM systems is a prerequisite for their use in the direct enforcement mode. The research results presented in this paper are a step towards this goal.
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Mykyjchuk, Mykola, Taras Hut, and Nadiya Lazarenko. "METROLOGICAL REQUIREMENTS OF WEIGH-IN-MOTION SYSTEMS FOR VEHICLES." Measuring Equipment and Metrology 82, no. 2 (2021): 10–15. http://dx.doi.org/10.23939/istcmtm2021.02.010.

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The article analyzes and proposes solutions for metrological support of weight information systems of road vehicles in motion, including the method of classification of WIM systems by purpose and accuracy classes, metrological requirements for them and control methods for testing and verification, as well as the main metrological risks for Weigh-in-motion systems for road vehicles and requirements for determining and calculating reliability.
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Dyshenko, V. S., A. E. Raskutin, and M. A. Zuev. "The road detector in systems of Weigh-In-Motion." Proceedings of VIAM, no. 5 (2016): 12. http://dx.doi.org/10.18577/2307-6046-2016-0-5-12-12.

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Gajda, Janusz, Ryszard Sroka, and Piotr Burnos. "Designing the Calibration Process of Weigh-In-Motion Systems." Electronics 10, no. 20 (October 18, 2021): 2537. http://dx.doi.org/10.3390/electronics10202537.

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Weigh-In-Motion (WIM) systems provide information on the state of road traffic and are used in activities undertaken as part of traffic supervision and management, enforcement of applicable regulations, and in the design of road infrastructure. The further development of such systems is aimed at increasing their measurement accuracy, operational reliability, and their resistance to disturbing environmental factors. Increasing the accuracy of measurement can be achieved both through actions taken in the hardware layer (technology of load sensors, the number of sensors and their arrangement, technology used in the construction of the pavement, selection of the system location), as well as by implementing better system calibration algorithms and algorithms for pre-processing measurement data. In this paper, we focus on the issue of WIM system calibration. We believe that through the correct selection of the calibration algorithm, it is possible to significantly increase the accuracy of vehicle weighing in WIM systems, from a practical point of view. The simulation and experimental studies we conducted confirmed this hypothesis.
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Ryguła, Artur, Krzysztof Brzozowski, and Andrzej Maczyński. "Limitations of the effectiveness of Weigh in Motion systems." Open Engineering 10, no. 1 (March 17, 2020): 183–96. http://dx.doi.org/10.1515/eng-2020-0020.

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AbstractOverloaded vehicles pose a real threat to road safety and significantly contribute to the degradation of the road surface. High-Speed Weigh in Motion (HS-WIM) stations are the commonly used method of eliminating them from traffic. In Poland, HS-WIM stations operate in pre-selection mode, sending information to services about the potential exceedance of acceptable standards by a specific vehicle. The article presents the results of the data analysis from selected HS-WIM stations operating on the national road network in Poland indicating significant limitations of the effectiveness of the whole system. The main reason for this may be that carriers use the knowledge about the HS-WIM stations location and working time to avoid inspections. The results presented in the paper indicate, among other things, that in some locations the share of vehicles overloaded with traffic increases significantly outside the working hours of the controlling services. For Light Commercial Vehicle, the share of overloaded vehicles in this group is also significant. Also, the paper indicates that the effectiveness of the procedure for determining vehicle overload has been limited due to errors in classification.
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Mosleh, Araliya, Pedro Alves Costa, and Rui Calçada. "A new strategy to estimate static loads for the dynamic weighing in motion of railway vehicles." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 234, no. 2 (March 29, 2019): 183–200. http://dx.doi.org/10.1177/0954409719838115.

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The present paper focuses on the numerical modeling of a weigh-in-motion system developed with the purpose of assessing the static loads imposed by the train onto the track infrastructure. Weigh-in-motion systems would be useful in overcoming the disadvantages typical of the conventional static weighing such as costs and traffic management. However, contrary to the conventional static weighing, weigh-in-motion systems do not allow a direct measurement of the static load since the train–track dynamic interaction gives rise to dynamic loads that are added to the static ones. This study investigates how train speed and track unevenness affect the loads assessed by the weigh-in-motion system. In order to achieve that goal, a comprehensive statistical study was performed based on an extensive amount of calculations. Finally, based on the conclusions and trend identified through the comprehensive parametric study, an approach is proposed to correct the direct result given by the weigh-in-motion system in order to obtain an estimation of the static load.
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Gajda, Janusz, Ryszard Sroka, and Piotr Burnos. "Sensor Data Fusion in Multi-Sensor Weigh-In-Motion Systems." Sensors 20, no. 12 (June 13, 2020): 3357. http://dx.doi.org/10.3390/s20123357.

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In this paper, we present the results of a comparison of two estimators of the gross vehicle weight (GVW) and the static load of individual axles of vehicles. The estimators were used to process measurement data derived from Multi-Sensor Weigh-In-Motion systems (MS-WIM). The term estimator is understood as an algorithm according to which the dynamic axle load measurement results are processed in order to determine the static load. The result obtained is called static load estimate. As a measure of measurement uncertainty, we adopted the standard deviation of the static load estimate. The mean value and the maximum likelihood estimators were compared. Studies were conducted using simulation methods based on synthetic data and experimental data obtained from a WIM system equipped with 16 lines of polymer axle load sensors. We have shown a substantially lower uncertainty of estimates determined using the maximum likelihood estimator. The results obtained have considerable practical significance, particularly during long-term usage of multi-sensor WIM systems.
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Dissertations / Theses on the topic "Wegh in Motion Systems"

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Dai, Chengxin. "Exploring Data Quality of Weigh-In-Motion Systems." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/1018.

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This research focuses on the data quality control methods for evaluating the performance of Weigh-In-Motion (WIM) systems on Oregon highways. This research identifies and develops a new methodology and algorithm to explore the accuracy of each station's weight and spacing data at a corridor level, and further implements the Statistical Process Control (SPC) method, finite mixture model, axle spacing error rating method, and data flag method in published research to examine the soundness of WIM systems. This research employs the historical WIM data to analyze sensor health and compares the evaluation results of the methods. The results suggest the new triangulation method identified most possible WIM malfunctions that other methods sensed, and this method unprecedentedly monitors the process behavior with controls of time and meteorological variables. The SPC method appeared superior in differentiating between sensor noises and sensor errors or drifts, but it drew wrong conclusions when accurate WIM data reference was absent. The axle spacing error rating method cannot check the essential weight data in special cases, but reliable loop sensor evaluation results were arrived at by employing this multiple linear regression model. The results of the data flag method and the finite mixed model results were not accurate, thus they could be used as additional tools to complement the data quality evaluation results. Overall, these data quality analysis results are the valuable sources for examining the early detection of system malfunctions, sensor drift, etc., and allow the WIM operators to correct the situation on time before large amounts of measurement are lost.
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Weng, Ying. "Operational effects of weigh-in-motion systems in weight enforcement." Thesis, This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-12302008-063629/.

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Bowie, Jeanne M. "Development of a weigh-in-motion system using acoustic emission sensors." Doctoral diss., University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4851.

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Statistical models for weight using the laboratory data and using the field data were developed. Dimensional analysis variables as well as other relevant measurable parameters were used in the development of the statistical models. The model created for the April 2009 dataset was validated, with only 27 lbs average error in the weight calculation as compared with the weight measurement made with the weigh station weigh-in-motion scale. The maximum percent error for the weight calculation was 204%, with about 65% of the data falling within 30% error. Additional research will be needed to develop an acoustic emission weigh-in-motion system with adequate accuracy for a commercial product. Nevertheless, this dissertation presents a valuable contribution to the effort of developing a low-cost acoustic emission weigh-in-motion scale. Future research needs that were identified as part of this dissertation include: bullet] Examination of the effects of pavement type (flexible or rigid), vehicle speeds greater than 50 mph, and temperature bullet] Determination of the best acoustic emission sensor for this system bullet] Exploration of the best method to separate the data from axles which pass over the equipment close together in time (such as tandem axles) bullet] Exploration of the effect of repeated measures on improving the accuracy of the system.; The acoustic emission response in the metal test strip to the motorcycle tire rolling over it was detected by the acoustic emission sensors and analyzed by the computer. Initial examinations of the data showed a correlation between the force of the tire against the cylinder and the energy and count of the acoustic emissions. Subsequent field experiments were performed at a weigh station on I-95 in Flagler County, Florida. The proposed weigh-in-motion system (the metal test bar with attached acoustic emission sensors) was installed just downstream of the existing weigh-in-motion scale at the weigh station. Commercial vehicles were weighed on the weigh station weigh-in-motion scale and acoustic emission data was collected by the experimental system. Test data was collected over several hours on two different days, one in July 2008 and the other in April 2009. Initial examination of the data did not show direct correlation between any acoustic emission parameter and vehicle weight. As a result, a more sophisticated model was developed. Dimensional analysis was used to examine possible relationships between the acoustic emission parameters and the vehicle weight. In dimensional analysis, a dimensionally correct equation is formed using measurable parameters of a system. The dimensionally correct equation can then be tested using experimental data. Dimensional analysis revealed the possible relationships between the acoustic emission parameters and the vehicle weight: w=f (gE/v??, YA, rE/Dsquare root of A], cE/square root of A], csubscript p]E/square root of A], E??/square root of A]multiplication dot]AbsE, aE/square root of A]) The defintions of these variables can be found in Appendix A.; This dissertation proposes a system for weighing commercial vehicles in motion using acoustic emission sensors attached to a metal bar placed across the roadway. The signal from the sensors is analyzed by a computer and the vehicle weight is determined by a statistical model which correlates the acoustic emission parameters to the vehicle weight. Such a system would be portable and low-cost, allowing for the measurement of vehicle weights in much the same way commercial tube and radar counters routinely collect vehicle speed and count. The system could be used to collect vehicle speed and count data as well as weight information. Acoustic emissions are naturally occurring elastic waves produced by the rapid release of energy within a material. They are caused by deformation or fracturing of a solid due to thermal or mechanical stress. Acoustic emission sensors have been developed to detect these waves and computer software and hardware have been developed to analyze and provide information about the waveforms. Acoustic emission testing is a common form of nondestructive testing and is used for pressure vessel testing, leak detection, machinery monitoring, structural integrity monitoring, and weld monitoring, among other things (Miller, 1987). For this dissertation, acoustic emission parameters were correlated to the load placed on the metal test bar to determine the feasibility of using a metal test bar to measure the weight of a vehicle in motion. Several experiments were done. First, the concept was tested in a laboratory setting using an experimental apparatus. A concrete cylinder was mounted on a frame and rotated using a motor. The metal test bar was applied directly to the surface of the cylinder and acoustic emission sensors were attached to each end of the bar. As the cylinder rotated, a motorcycle tire was pushed up against the cylinder using a scissor jack to simulate different loads.
ID: 029809680; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (Ph.D.)--University of Central Florida, 2011.; Includes bibliographical references (p. 130-133).
Ph.D.
Doctorate
Civil, Environmental and Construction Engineering
Engineering and Computer Science
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Seegmiller, Luke W. "Utah Commercial Motor Vehicle Weigh-in-Motion Data Analysis and Calibration Methodology." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1616.pdf.

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Bock, André Luiz. "Pesagem em movimento de cargas atuantes em rodovias e seu impacto no desempenho de pavimentos da rede temática de asfalto." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/156809.

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Nas últimas décadas os pavimentos rodoviários brasileiros têm tido seu desempenho comprometido devido a uma série de fatores, entre eles incluem-se não somente o crescente aumento do volume de tráfego de veículos pesados e aumento de sua capacidade de transporte, mas principalmente a circulação com cargas acima dos limites legais estabelecidos, configurando uma situação crítica para a sua adequada durabilidade da estrutura projetada. Paralelamente aos investimentos necessários, é importante também o desenvolvimento de métodos mais racionais de dimensionamento de pavimentos contemplando as especificidades dos materiais empregados e levando em consideração as condições climáticas e, principalmente uma completa e detalhada caracterização do tráfego solicitante. Neste contexto apresentado, a pesquisa insere-se em dois importantes estudos. O acompanhamento construtivo e monitoramento sistemático de desempenho de dois trechos na rodovia BR-448/RS e a continuidade do monitoramento de outros dois na BR-290/RS, trecho em concessão entre Osório e Porto Alegre (Freeway). Estas atividades inserem-se no “Projeto Integrado da Rede Temática de Tecnologia em Asfalto Petrobras/ANP", de abrangência nacional, para desenvolvimento de um novo método brasileiro de dimensionamento de pavimentos O segundo estudo trata-se de um completo monitoramento de cargas na Freeway, através da instalação e operacionalização inédita de um equipamento de pesagem dinâmica de alta velocidade (Hight Speed Weigh-in-Motion – HS-WIM) para determinação do espectro de cargas e posterior análise de sua influência no desempenho de pavimentos. Com ambos os estudos foi possível, além de determinar o espectro de cargas, os carregamentos médios e os níveis de sobrecargas praticados naquela rodovia, verificar como estas cargas influenciam o desempenho do pavimento e confrontar estes dados com as tendências observadas através do monitoramento sistemático dos trechos analisados. Por meio do desenvolvimento do presente trabalho pretende-se contribuir para melhorias na engenharia rodoviária e de tráfego através da inserção de novas tecnologias de monitoramento e fiscalização das cargas transportadas e contribuir com o desenvolvimento de um novo método de dimensionamento de pavimentos flexíveis proposto pela Rede Temática de Asfalto, através do levantamento de dados nos trechos experimentais para desenvolvimento de modelos de desempenho e sua posterior inserção nos modelos de calibração.
In recent decades the Brazilian road pavements have had their performance reduced due to a number of factors, not only the increasing volume of heavy vehicles and increased transport capacity, but mainly the flow with loads above the established legal limits, setting a critical situation for the durability of the designed structure. Alongside the necessary investment, it is also important to the development of more rational methods of pavement design, considering the specificities of the materials used and taking into account the climatic conditions and a complete and detailed characterization of the traffic. In this context, the research was developed to attain two main objectives: the construction monitoring and systematic assessment of performance of two test sections built in BR-448/RS highway and the continuity of assesment of two others previously built in BR-290/RS, between Osório and Porto Alegre (known as Freeway). These activities are part of the "Integrated Project Theme Technology Network Petrobras Asphalt/ANP", a nationwide project aimed at developing a new Brazilian method for pavement design The second objective was to conduct a comprehensive monitoring loads study on the Freeway, by installing and carrying on an unprecedented operation of a dynamic weighting equipment of high speed (High speed weigh-in-Motion - HS-WIM) to determine the loads spectrum and subsequent analysis of the influence on pavement performance. Both studies made possible to determine the loads spectrum, average loads and levels of overloads practiced on that highway, to estimate how these loads affect the pavement performance and to compare these data with the trends observed through the systematic assessment of the analyzed sections. This work aims to contribute to improvements in road and traffic engineering, by introducing new monitoring technologies, monitoring the transported cargo and contributing to the development of a new design method of flexible pavements, a major goal of the Thematic Network of Asphalt, to be achieved through experimental data collection in test sections, the development of performance models and their subsequent insertion in the calibration models.
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Lydon, Myra. "Next generation bridge weigh-in-motion system using optical sensors." Thesis, Queen's University Belfast, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.707822.

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Xue, Wenjing. "Integrated transportation monitoring system for both pavement and traffic." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/23217.

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In the passing decades, the monitoring of pavements and passing vehicles was developed vigorously with the growth of information and sensing technology. Pavement monitoring is an essential part of pavement research and plays an important role in transportation system. At the same time, the monitoring system about the traffic, such as Weigh-in-Motion (WIM) system and traffic classification system, also attracted lots of attention because of their importance in traffic statistics and management.
The monitoring system in this dissertation combines the monitoring for pavements and traffic together with the same sensing network. For pavement health monitoring purpose, the modulus of the asphalt layer can be back-calculated based on the collected mechanical responses under corresponding environmental conditions. At the same time, the actually strain and stress in pavements induced by each passing vehicle are also used for pavement distress prediction. For traffic monitoring purpose, the horizontal strain traces are analyzed with a Gaussian model to estimate the speed, wandering position, weight and classification of each passing vehicle. The whole system, including the sensing network and corresponding analysis method, can monitor the pavement and the traffic simultaneously, and is called transportation monitoring system. This system has a high efficiency because of its low cost and easy installation; multi-functionality to provide many important information of transportation system.

Many related studies were made to improve the prototyped transportation monitoring system. With the assistance of numerical simulation software ABAQUS and 3D-Move, the effect of many loading and environmental conditions, including temperature, vehicle speed, tire configuration and inflation pressure, are taken into consideration. A method was set up to integrate data points from many tests of similar environmental and loading conditions based on Gaussian model. Another method for consistent comparison of variable field sensor data was developed. It was demonstrated that variation in field measurement was due to uncontrollable environmental and loading factors, which may be accounted for by using laboratory test and numerical simulation based corrections.
Ph. D.
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Zhang, Zhiming. "An Integrated System for Road Condition and Weigh-in-Motion Measurements using In-Pavement Strain Sensors." Diss., North Dakota State University, 2016. http://hdl.handle.net/10365/25819.

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The United States has the world?s largest road network with over 4.1 million miles of roads supporting more than 260 million of registered automobiles including around 11 million of heavy trucks. Such a large road network challenges the road and traffic management systems such as condition assessment and traffic monitoring. To assess the road conditions and track the traffic, currently, multiple facilities are required simultaneously. For instance, vehicle-based image techniques are available for pavements? mechanical behavior detection such as cracks, high-speed vehicle-based profilers are used upon request for the road ride quality evaluation, and inductive loops or strain sensors are deployed inside pavements for traffic data collection. Having multiple facilities and systems for the road conditions and traffic information monitoring raises the cost for the assessment and complicates the process. In this study, an integrated system is developed to simultaneously monitor the road condition and traffic using in-pavement strain-based sensors, which will phenomenally simplify the road condition and traffic monitoring. To accomplish such a superior system, this dissertation designs an innovative integrated sensing system, installs the integrated system in Minnesota's Cold Weather Road Research Facility (MnROAD), monitors the early health conditions of the pavements and ride quality evaluation, investigates algorithms by using the developed system for traffic data collection especially weigh-in-motion measurements, and optimizes the system through optimal system design. The developed integrated system is promising to use one system for multiple purposes, which gains a considerable efficiency increase as well as a potential significant cost reduction for intelligent transportation system.
USDOT (U.S. Department of Transportation)
MPC (Mountain-Plains Consortium)
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Al-Tarawneh, Mu'ath. "Traffic Monitoring System Using In-Pavement Fiber Bragg Grating Sensors." Diss., North Dakota State University, 2019. https://hdl.handle.net/10365/31539.

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Recently, adding more lanes becomes less and less feasible, which is no longer an applicable solution for the traffic congestion problem due to the increment of vehicles. Using the existing infrastructure more efficiently with better traffic control and management is the realistic solution. An effective traffic management requires the use of monitoring technologies to extract traffic parameters that describe the characteristics of vehicles and their movement on the road. A three-dimension glass fiber-reinforced polymer packaged fiber Bragg grating sensor (3D GFRP-FBG) is introduced for the traffic monitoring system. The proposed sensor network was installed for validation at the Cold Weather Road Research Facility in Minnesota (MnROAD) facility of Minnesota Department of Transportation (MnDOT) in MN. A vehicle classification system based on the proposed sensor network has been validated. The vehicle classification system uses support vector machine (SVM), Neural Network (NN), and K-Nearest Neighbour (KNN) learning algorithms to classify vehicles into categories ranging from small vehicles to combination trucks. The field-testing results from real traffic show that the developed system can accurately estimate the vehicle classifications with 98.5 % of accuracy. Also, the proposed sensor network has been validated for low-speed and high-speed WIM measurements in flexible pavement. Field testing validated that the longitudinal component of the sensor has a measurement accuracy of 86.3% and 89.5% at 5 mph and 45 mph vehicle speed, respectively. A performed parametric study on the stability of the WIM system shows that the loading position is the most significant parameter affecting the WIM measurements accuracy compared to the vehicle speed and pavement temperature. Also the system shows the capability to estimate the location of the loading position to enhance the system accuracy.
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Binks, P. N. "Orbital motion in stellar systems." Thesis, University of Oxford, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233397.

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Books on the topic "Wegh in Motion Systems"

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Lee, Clyde E. Demonstration of weigh-in-motion systems for data collection and enforcement. Austin, Tex: The Center, 1985.

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Use of weigh-in-motion systems for data collection and enforcement. Washington, D.C: Transportation Research Board, National Research Council, 1986.

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Qu, Tongbin. Traffic-load forecasting using weigh-in-motion data. [Austin, TX]: Center for Transportation Research, Bureau of Engineering Research, University of Texas at Austin, 1997.

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Strathman, James G. The Oregon DOT Slow-Speed Weigh-in-Motion (SWIM) Project: Final report. Portland, OR: Center for Urban Studies, School of Urban and Public Affairs, Portland State University, 1998.

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Strathman, James G. The Oregon DOT Slow-Speed Weigh-in-Motion (SWIM) Project: Final report. Portland, OR: Center for Urban Studies, School of Urban and Public Affairs, Portland State University, 1998.

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Tex.) International Conference on Weigh-in-Motion (6th 2012 Dallas. International Conference on Weigh-in-Motion: ICWIM 6. London: ISTE, 2012.

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European Conference on Weigh-in-Motion of Road Vehicles (2nd 1998 Lisbon). Second European conference on weigh-in-motion of road vehicles, Lisbon 14th-16th September, 1998. Luxembourg: Office for Official Publications of the European Commission, 1998.

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European Conference on Weigh-in-Motion of Road Vehicles (2nd 1998 Lisbon, Portugal). Post-proceedings of the second European Conference on Weigh-in-Motion of Road Vehicles: Lisbon, 14th-16th September, 1998. Edited by O'Brien Eugene J. 1958-, Jacob Bernard, European Cooperation in the Field of Scientific and Technical Research (Organization). Management Committee., and European Commission. Brussels, Luxembourg: Office for Official Publications of the European Commission, 1998.

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Whitford, Robert K. State of Alaska truck weight monitoring plan using weigh-in-motion devices, (including analysis and proposed site locations): Final report, project #76095. [Juneau]: The Division, 1999.

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Papagiannakis, A. T. High speed weigh-in-motion system calibration practices. Washington, D.C: Transportation Research Board, 2008.

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Book chapters on the topic "Wegh in Motion Systems"

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Ding, Huijuan, Quanhu Li, Ting Xu, and Nengshao Li. "Vehicle Weigh-in-motion Systems Based on Particle Swarm Optimization." In Proceedings of the Second International Conference on Mechatronics and Automatic Control, 587–95. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-13707-0_64.

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Grakovski, Alexander, and Alexey Pilipovecs. "Weigh-in-Motion by Fibre-Optic Sensors: Problem of Measurement Errors Compensation for Longitudinal Oscillations of a Truck." In Lecture Notes in Networks and Systems, 371–80. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74454-4_36.

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Gajda, Janusz, Ryszard Sroka, Marek Stencel, and Tadeusz Zeglen. "Multi-sensor weigh-in-motion system." In International Conference on Heavy Vehicles HVParis 2008, 199–208. Hoboken, NJ, USA: John Wiley & Sons, Inc, 2013. http://dx.doi.org/10.1002/9781118623305.ch15.

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Loga, Wiktoria, Krzysztof Brzozowski, and Artur Ryguła. "A Method for Estimating the Occupancy Rates of Public Transport Vehicles Using Data from Weigh-In-Motion Systems." In Communications in Computer and Information Science, 426–35. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49646-7_36.

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Hinch, E. J. "Brownian Motion." In Mobile Particulate Systems, 73–78. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-015-8518-7_6.

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Henn, Volker. "Motion Sense." In Sensory Systems: II, 43. Boston, MA: Birkhäuser Boston, 1988. http://dx.doi.org/10.1007/978-1-4684-6760-4_20.

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Graybiel, Ashton. "Motion Sickness." In Sensory Systems: II, 44–46. Boston, MA: Birkhäuser Boston, 1988. http://dx.doi.org/10.1007/978-1-4684-6760-4_21.

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Ştefănescu, Dan Mihai. "A New Weigh-in-Motion and Traffic Monitoring System." In Handbook of Force Transducers, 119–26. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35322-3_12.

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Loga, Wiktoria, and Jerzy Mikulski. "Traffic Analysis Based on Weigh-In-Motion System Data." In Communications in Computer and Information Science, 268–79. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49646-7_23.

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Belkind, Ori. "Primitive Motion Relationalism." In Physical Systems, 59–91. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2373-3_3.

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Conference papers on the topic "Wegh in Motion Systems"

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Sroka, Ryszard, Janusz Gajda, Piotr Burnos, and Piotr Piwowar. "Information fusion in weigh in motion systems." In 2015 IEEE Sensors Applications Symposium (SAS). IEEE, 2015. http://dx.doi.org/10.1109/sas.2015.7133637.

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Xiao, Juncheng, and Pengmin Lv. "Application of Wavelet Transform in Weigh-in-Motion." In 2009 International Workshop on Intelligent Systems and Applications. IEEE, 2009. http://dx.doi.org/10.1109/iwisa.2009.5072754.

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He, Hai-lang, and Yun Wang. "Simulation of piezoelectric sensor in weigh-in-motion systems." In 2015 Symposium on Piezoelectricity, Acoustic Waves, and Device Applications (SPAWDA). IEEE, 2015. http://dx.doi.org/10.1109/spawda.2015.7364457.

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Srikanth, K. B., and G. Poornima. "Weigh-In-Motion Sensor Based Electronic Toll Collection System." In 2020 Fourth World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4). IEEE, 2020. http://dx.doi.org/10.1109/worlds450073.2020.9210394.

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Zhang, Dong-sheng, Dan Guo, Wei Li, Yong-guo Li, An Wu, Kai-fang Yao, and De-sheng Jiang. "Study on weigh-in-motion system based on chirped fiber gratings." In Advanced Sensor Systems and Applications III. SPIE, 2007. http://dx.doi.org/10.1117/12.753503.

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Tobin, Jr., Kenneth W., and Jeffrey D. Muhs. "Algorithm for a novel fiber optic weigh-in-motion sensor system." In Specialty Fiber Optic Systems for Mobile Platforms, edited by Norris E. Lewis and Emery L. Moore. SPIE, 1991. http://dx.doi.org/10.1117/12.50978.

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Allotta, B., P. D'Adamio, G. Gaburri, A. Innocenti, L. Marini, E. Meli, and L. Pugi. "Weigh in Motion systems for railway vehicles: Performance and robustness analysis." In 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2015. http://dx.doi.org/10.1109/i2mtc.2015.7151562.

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Chen, Nan, Quanhu Li, Fei Li, and Zhiliang Jia. "A data processing algorithm based on vehicle weigh-in-motion systems." In 2013 9th International Conference on Natural Computation (ICNC). IEEE, 2013. http://dx.doi.org/10.1109/icnc.2013.6817975.

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Lander, Peter, Nadine Fahed, and Yang Wang. "Martlet wireless sensing system for full scale bridge weigh-in-motion." In Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, edited by Daniele Zonta, Zhongqing Su, and Branko Glisic. SPIE, 2022. http://dx.doi.org/10.1117/12.2612610.

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Agorastou, Zoi, Vasiliki Gogolou, Konstantinos Kozalakis, and Stylianos Siskos. "Area estimation circuit for Weigh-In-Motion applications using piezoelectric transducers." In 2021 28th IEEE International Conference on Electronics, Circuits, and Systems (ICECS). IEEE, 2021. http://dx.doi.org/10.1109/icecs53924.2021.9665543.

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Reports on the topic "Wegh in Motion Systems"

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Dai, Chengxin. Exploring Data Quality of Weigh-In-Motion Systems. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.1018.

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Beshears, D. L. Static Scale Conversion Weigh-In-Motion System. Office of Scientific and Technical Information (OSTI), May 2001. http://dx.doi.org/10.2172/814441.

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Beshears, D. L., J. D. Muhs, and M. B. Scudiere. Advanced weigh-in-motion system for weighing vehicles at high speed. Office of Scientific and Technical Information (OSTI), February 1998. http://dx.doi.org/10.2172/588574.

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Cicci, David A., John E. Cochran, and Jr. Identification and Motion Prediction of Tethered Satellite Systems. Fort Belvoir, VA: Defense Technical Information Center, May 2001. http://dx.doi.org/10.21236/ada387974.

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Chan, C. W. Edge Detection to Isolate Motion in Adaptive Optics Systems. Office of Scientific and Technical Information (OSTI), July 2003. http://dx.doi.org/10.2172/15004551.

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Jennings, Brian A. Developing a simulation tool for evaluating in-motion detector systems. Office of Scientific and Technical Information (OSTI), December 2018. http://dx.doi.org/10.2172/1484611.

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William C. Johnson. Microstructural Evolution and Interfacial Motion in Systems with Diffusion Barriers. Office of Scientific and Technical Information (OSTI), June 2007. http://dx.doi.org/10.2172/1007959.

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Perry H. Leo. Microstructural Evolution and interfacial motion in systems with diffusion barriers. Office of Scientific and Technical Information (OSTI), March 2009. http://dx.doi.org/10.2172/948729.

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Zywiol, Harry, David Gorsich, Kaleb McDowell, and Susan Hill. Using Motion-Base Simulation to Guide Future Force Systems Design. Fort Belvoir, VA: Defense Technical Information Center, February 2006. http://dx.doi.org/10.21236/ada459735.

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Leonard, Naomi E., and P. S. Krishnaprasad. Motion Control of Drift-Free, Left-Invariant Systems on Lie Groups. Fort Belvoir, VA: Defense Technical Information Center, September 1995. http://dx.doi.org/10.21236/ada453131.

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