scholarly journals Investigation of Weigh-in-Motion Measurement Accuracy on the Basis of Steering Axle Load Spectra

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3272 ◽  
Author(s):  
Dawid Rys
Keyword(s):  
Data Quality ◽  
Vehicle Speed ◽  
Traffic Data ◽  
Obvious Effect ◽  
Road Infrastructure ◽  
Load Spectra ◽  
Weigh In Motion ◽  
Infrastructure Design ◽  
Load Sensor ◽  
Measurement Results

Weigh-in-motion systems are installed in pavements or on bridges to identify and reduce the number of overloaded vehicles and minimise their adverse effect on road infrastructure. Moreover, the collected traffic data are used to obtain axle load characteristics, which are very useful in road infrastructure design. Practical application of data from weigh-in-motion has become more common recently, which calls for adequate attention to data quality. This issue is addressed in the presented paper. The aim of the article is to investigate the accuracy of 77 operative weigh-in-motion stations by analysing steering axle load spectra. The proposed methodology and analysis enabled the identification of scale and source of errors that occur in measurements delivered from weigh-in-motion systems. For this purpose, selected factors were investigated, including the type of axle load sensor, air temperature and vehicle speed. The results of the analysis indicated the obvious effect of the axle load sensor type on the measurement results. It was noted that systematic error increases during winter, causing underestimation of axle loads by 5% to 10% for quartz piezoelectric and bending beam load sensors, respectively. A deterioration of system accuracy is also visible when vehicle speed decreases to 30 km/h. For 25% to 35% of cases, depending on the type of sensor, random error increases for lower speeds, while it remains at a constant level at higher speeds. The analysis also delivered a standard steering axle load distribution, which can have practical meaning in the improvement of weigh-in-motion accuracy and traffic data quality.

Use of Long-Term Pavement Performance Data to Develop Traffic Defaults in Support of Mechanistic-Empirical Pavement Design Procedures

2003 ◽  
Vol 1855 (1) ◽  
pp. 176-182 ◽  
Author(s):  
Weng On Tam ◽  
Harold Von Quintus
Keyword(s):  
Pavement Design ◽  
Vehicle Classification ◽  
Pavement Performance ◽  
Traffic Data ◽  
Design Procedures ◽  
Load Spectra ◽  
State Highway ◽  
Pavement Structures ◽  
Empirical Design

Traffic data are a key element for the design and analysis of pavement structures. Automatic vehicle-classification and weigh-in-motion (WIM) data are collected by most state highway agencies for various purposes that include pavement design. Equivalent single-axle loads have had widespread use for pavement design. However, procedures being developed under NCHRP require the use of axle-load spectra. The Long-Term Pavement Performance database contains a wealth of traffic data and was selected to develop traffic defaults in support of NCHRP 1-37A as well as other mechanistic-empirical design procedures. Automated vehicle-classification data were used to develop defaults that account for the distribution of truck volumes by class. Analyses also were conducted to determine direction and lane-distribution factors. WIM data were used to develop defaults to account for the axle-weight distributions and number of axles per vehicle for each truck type. The results of these analyses led to the establishment of traffic defaults for use in mechanistic-empirical design procedures.

Theoretical investigation into the measurability of rail unevenness and corrugation using the dynamic response of axle box and bogie

2020 ◽  
pp. 095440972092321
Author(s):  
Yurong Wang
Keyword(s):  
Dynamic Response ◽  
Standing Waves ◽  
Vehicle Speed ◽  
Long Distance ◽  
Rail Corrugation ◽  
Track Maintenance ◽  
Track System ◽  
Measurement Results ◽  
Ballasted Track ◽  
Rail Irregularity

Monitoring track unevenness is important for noise and vibration control and track maintenance. Rail corrugation and shorter wavelength track unevenness can be measured using the corrugation analysis trolley, but it is not suitable for measurement over long distance. It is of great significance to study the dynamic behavior of the response of the axle box and bogie to the unevenness excitation for a better understanding of the measurement results. In this paper, the dynamic response of the axle box and bogie to the unevenness excitation is analyzed in the frequency domain by taking account of multiple wheel–rail interactions, which is the case in practice. The response of the axle box and bogie is found to be affected by the so-called P2 resonances at low and medium frequencies and the standing waves of rail vibration at higher frequencies due to the multiple wheel–rail interactions. Based on the analysis of the response of the axle box and bogie, the measurability of track unevenness is discussed. Results show that the measurement of rail unevenness using the axle box response is mainly limited by the P2 resonance. The frequency range of measurement for the ballasted track studied is estimated to be 1–35 Hz, corresponding to the measurable unevenness wavelength of 0.6–20 m (or longer) at a vehicle speed of 20 m/s. Above 200 Hz, the standing waves of rail vibration will cause serious uncertainty in the measurement of short wavelength rail irregularity using the axle box response for the resilient track. Short pitch rail corrugation, however, can be evaluated using the axle box response due to its strong correlation with certain modes of the wheel–track system.

scholarly journals Implementation of a Mobile Platform Based on Fiber Bragg Grating Sensors for Automotive Traffic Monitoring

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1567 ◽  
Author(s):  
Kivilcim Yuksel ◽  
Damien Kinet ◽  
Karima Chah ◽  
Christophe Caucheteur
Keyword(s):  
Fiber Optic ◽  
Traffic Monitoring ◽  
Fiber Optic Sensors ◽  
Mobile Platform ◽  
Vehicle Speed ◽  
Distributed Monitoring ◽  
Fiber Bragg Grating Sensors ◽  
Weigh In Motion ◽  
Monitoring Applications ◽  
Fbg Sensors

Instrumentation techniques, implementation and installation methods are major concerns in today’s distributed and quasi-distributed monitoring applications using fiber optic sensors. Although many successful traffic monitoring experiments have been reported using Fiber Bragg Gratings (FBGs), there has been no standardized solution proposed so far to have FBG seamlessly implemented in roads. In this work, we investigate a mobile platform including FBG sensors that can be positioned on roads for the purpose of vehicle speed measurements. The experimental results prove the efficiency of the proposed platform, providing a perspective toward weigh-in-motion systems.

scholarly journals How to Inspect and Measure Data Quality about Scientific Publications: Use Case of Wikipedia and CRIS Databases

Algorithms ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 107 ◽  
Author(s):  
Otmane Azeroual ◽  
Włodzimierz Lewoniewski
Keyword(s):  
Data Quality ◽  
Spatial Information ◽  
Real Data ◽  
Knowledge Bases ◽  
Quality Analysis ◽  
Quality Data ◽  
Measure Data ◽  
Research Information ◽  
Scientific Publications ◽  
Measurement Results

The quality assurance of publication data in collaborative knowledge bases and in current research information systems (CRIS) becomes more and more relevant by the use of freely available spatial information in different application scenarios. When integrating this data into CRIS, it is necessary to be able to recognize and assess their quality. Only then is it possible to compile a result from the available data that fulfills its purpose for the user, namely to deliver reliable data and information. This paper discussed the quality problems of source metadata in Wikipedia and CRIS. Based on real data from over 40 million Wikipedia articles in various languages, we performed preliminary quality analysis of the metadata of scientific publications using a data quality tool. So far, no data quality measurements have been programmed with Python to assess the quality of metadata from scientific publications in Wikipedia and CRIS. With this in mind, we programmed the methods and algorithms as code, but presented it in the form of pseudocode in this paper to measure the quality related to objective data quality dimensions such as completeness, correctness, consistency, and timeliness. This was prepared as a macro service so that the users can use the measurement results with the program code to make a statement about their scientific publications metadata so that the management can rely on high-quality data when making decisions.

Research on Integrated and Portable Weigh-in-Motion Scale

2012 ◽  
Vol 192 ◽  
pp. 149-153
Author(s):  
Liang Hao
Keyword(s):  
Data Collection ◽  
Dynamic Characteristic ◽  
Strain Gauge ◽  
High Accuracy ◽  
Traffic Data ◽  
Ansys Software ◽  
Weigh In Motion ◽  
Traffic Data Collection ◽  
Dynamic Weighing

The integrated dynamic weighing scale with a high accuracy was developed based on analyzing the loads when vehicles passed on the weighing scale. The ANSYS software was applied to determine the sensor’s foil strain gauge position and the dynamic characteristic was verified through the experiment; meanwhile the hardware and measuring software in the system were simply introduced in this article. Finally through the experiments the Weigh-In-Motion (WIM) system can be used in traffic data collection and is assistant tool for overload check.

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