Scipediacontent: Scipediacontent moved page Draft Content 294578983 to Grignard et al 2018a

2021-01-28T18:54:40Z

Scipediacontent moved page Draft Content 294578983 to Grignard et al 2018a

Scipediacontent: Created page with " == Abstract == WIM (Weight in motion) technologies are already widely used to detect overloaded vehicles. However, these systems have not yet been approved by the Legal Metr..."

2021-01-28T18:54:36Z

Created page with " == Abstract == WIM (Weight in motion) technologies are already widely used to detect overloaded vehicles. However, these systems have not yet been approved by the Legal Metr..."

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== Abstract ==

WIM (Weight in motion) technologies are already widely used to detect overloaded vehicles. However, these systems have not yet been approved by the Legal Metrology for automated overload control and verbalization. The Automated Overload Control (AOC) project, supported by the French Ministry of Transport (DGITM), aims to demonstrate the feasibility of AOC with existing WIM technologies adapted to allow certification. The target accuracy is the 5% class from the OIML R1342006. To perform this, we need to know very precisely all the influence factors in order to correct and sort data to be sure to keep only the heavy weights overloaded. Repeatability, reproducibility tests were carried out on IFSTTAR full scale pavement fatigue facility in Nantes on piezo quartz sensors. Also real tests were performed on highway A4 near St Avold in France where Ten WIM sensors were installed. Road instrumentation also included like temperature, vertical displacement, geophones and accelerometers sensors. A large database of signals has been collected and Sorting algorithms were developed from to identify the various influencing factors such as pavement temperature, wheel position on the sensor, speed, dynamic overload, etc. Weighing within the required tolerances and road tests are intended to demonstrate the feasibility of the entire system. This paper focuses on the approach adopted to construct the criteria and sorting algorithms. It is based on 3 levels of sorting: Level 1 is the raw signals delivered by the sensors; Level 2 is dynamic force compared to static weight deviations; Level 3 is external factors affecting sensor response. In conclusion, experience shows that WIM sensors and additional data processing are able to accurately estimate truck loads in the OIML class 5. However, calibration of WIM sensors must be performed periodically with load position on the sensor and the road profile must be checked in order to evaluate the effects of dynamic loading. Finally, it is necessary to clearly define the ranges of validity of the pavement temperature and the speed of the vehicle

== Original document ==

The different versions of the original document can be found in:

* [https://zenodo.org/record/1491490 https://zenodo.org/record/1491490] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

* [https://zenodo.org/record/1491490 https://zenodo.org/record/1491490],
: [http://dx.doi.org/10.5281/zenodo.1491489 http://dx.doi.org/10.5281/zenodo.1491489] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

* [https://zenodo.org/record/1491490 https://zenodo.org/record/1491490],
: [http://dx.doi.org/10.5281/zenodo.1491490 http://dx.doi.org/10.5281/zenodo.1491490] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode

DOIS: 10.5281/zenodo.1491489 10.5281/zenodo.1491490

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Grignard et al 2018a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 294578983 to Grignard et al 2018a

Scipediacontent: Created page with " == Abstract == WIM (Weight in motion) technologies are already widely used to detect overloaded vehicles. However, these systems have not yet been approved by the Legal Metr..."