A Statistical Spatial Repeatability Algorithm for Multiple Sensor Weigh-in-Motion

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Title: A Statistical Spatial Repeatability Algorithm for Multiple Sensor Weigh-in-Motion
Authors: O'Brien, Eugene J.
González, Arturo
McInerney, F.
Permanent link: http://hdl.handle.net/10197/9242
Date: 22-May-2008
Online since: 2018-02-21T10:07:16Z
Abstract: The use of an array consisting of multiple WIM sensors is well established as a means of increasing the overall accuracy of in-motion axle weighing. This paper proposes a new algorithm for processing the outputs from such arrays and finding an improved estimate of the static axle weights. The mean pattern of forces from the axles of many vehicles are repeatable – this is the phenomenon of Statistical Spatial Repeatability (SSR). The recorded WIM force is therefore, on average, over- or under-estimating the static axle weight. Removing this bias and averaging the corrected measurements is the basis for the new algorithm. The newly developed SSR algorithm is assessed using experimental data from the WIM-Hand project test site near Arnheim in the Netherlands. The accuracy of the new algorithm was therefore assessed by applying the algorithm twice, once for each half of the multiple-sensor array, and comparing the calculated static weights. The difference was found to be small, which demonstrates that the calculation is accurate.
Funding Details: European Commission
Type of material: Conference Publication
Publisher: Wiley
Copyright (published version): 2013 Wiley
Keywords: Weigh-in-motionWIMMS-WIMMultiple sensorSpatial repeatabilitySSR
Other versions: https://www.wiley.com/en-us/ICWIM+5%2C+Proceedings+of+the+International+Conference+on+Heavy+Vehicles%3A+5th+International+Conference+on+Weigh+in+Motion+of+Heavy+Vehicles-p-9781118623275
Language: en
Status of Item: Peer reviewed
Is part of: Proceedings of the International Conference on Heavy Vehicles Paris 2008
Conference Details: International Conference on Heavy Vehicles, Paris, France, 19-22 May 2008
ISBN: 9781118623275
Appears in Collections:Civil Engineering Research Collection

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