20.500.12556/DiRROS-16940 Using statistical analysis of an acceleration-based bridge weigh-in-motion system for damage detection This paper develops a novel method of bridge damage detection using statistical analysis of data from an acceleration-based bridge weigh-in-motion (BWIM) system. Bridge dynamic analysis using a vehicle-bridge interaction model is carried out to obtain bridge accelerations, and the BWIM concept is applied to infer the vehicle axle weights. A large volume of traffic data tends to remain consistent (e.g., most frequent gross vehicle weight (GVW) of 3-axle trucks); therefore, the statistical properties of inferred vehicle weights are used to develop a bridge damage detection technique. Global change of bridge stiffness due to a change in the elastic modulus of concrete is used as a proxy of bridge damage. This approach has the advantage of overcoming the variability in acceleration signals due to the wide variety of source excitations/vehicles–data from a large number of different vehicles can be easily combined in the form of inferred vehicle weight. One year of experimental data from a short-span reinforced concrete bridge in Slovenia is used to assess the effectiveness of the new approach. Although the acceleration-based BWIM system is inaccurate for finding vehicle axle-weights, it is found to be effective in detecting damage using statistical analysis. It is shown through simulation as well as by experimental analysis that a significant change in the statistical properties of the inferred BWIM data results from changes in the bridge condition. bridge health monitoring bridge WIM structural dynamics damage detection vehicle-bridge interaction spremljanje stanja mostov mostni sistem WIM dinamika konstrukcij odkrivanje poškodb interakcija vozilo-konstrukcija true false true MDPI Angleški jezik Slovenski jezik first_page settings Order Article Reprints Open AccessArticle Using Statistical Analysis of an Acceleration-Based Bridge Weigh-In-Motion System for Damage Detection by Eugene OBrien 1 [ORCID] , Muhammad Arslan Khan 1,* [ORCID] , Daniel Patrick McCrum 1 [ORCID] and Aleš Žnidarič 2 1 School of Civil Engineering, University College Dublin, D04 V1W8 Belfield, Ireland 2 Slovenian National Building and Civil Engineering Institute (ZAG), 1000 Ljubljana, Slovenia * Author to whom correspondence should be addressed. Appl. Sci. 2020, 10(2), 663; https://doi.org/10.3390/app10020663 Received: 9 December 2019 / Revised: 13 January 2020 / Accepted: 14 January 2020 / Published: 17 January 2020 (This article belongs to the Section Civil Engineering) Download Browse Figures Versions Notes Abstract This paper develops a novel method of bridge damage detection using statistical analysis of data from an acceleration-based bridge weigh-in-motion (BWIM) system. Bridge dynamic analy Neznano 2023-09-12 08:31:42 2023-09-12 08:39:33 2023-09-13 03:35:19 0000-00-00 00:00:00 2020 0 0 Nasl. z nasl. zaslona; Opis vira z dne 21. 1. 2020; Art. 663; str. 1-20 iss. 2 Vol. 10 Jan. 2020 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 2020-01-17 624 2076-3417 10.3390/app10020663 2515047 https://www.mdpi.com/2076-3417/10/2/663 Open Access 1 359d6b3d-5125-11ee-8cc8-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=23025 RAZ_O_Brien_Eugene_J._2020.pdf RAZ_O_Brien_Eugene_J._2020.pdf 1 9BB19601ABEA1618EE745D7B3A377734 36401f883292fe6016d3d7c44e80e0219fe5145aa44eba36e90762e9e8164c69 263418f9-5126-11ee-8cc8-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=23026 Zavod za gradbeništvo Slovenije 0 0 0