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Appl. Sci. 2018, 8(5), 753; https://doi.org/10.3390/app8050753

Application of the Random Decrement Technique in Damage Detection under Moving Load

College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
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Received: 11 April 2018 / Revised: 4 May 2018 / Accepted: 6 May 2018 / Published: 9 May 2018
(This article belongs to the Special Issue Structural Damage Detection and Health Monitoring)

Abstract

This paper employs the random decrement technique as an output-only method to detect damage from the acceleration signals under a moving load. The random decrement technique is an especial averaging method that produces Random Decrement Signatures (RDS). For this purpose, Arias Intensity (AI) was employed to calculate the energy content of each RDS and substitute each acceleration signal by a scalar invariant value. Normalizing AIs, all RDSs were then updated so as to show a unique energy along the undamaged structure. Once the normalizing factor was computed for the intact structure, the damage was determined by the absolute difference of normalized AIs obtained from each individual RDS along the structure simultaneously. To verify the proposed method, two experimental models of a simply supported beam and a scaled arch bridge were developed under a moving load (vehicle simulation), and acceleration data were recorded. The results of laboratory models proved that the RDSs can accurately detect the damage location using the normalized AI without applying any further frequency filtering. This method needs neither the damage location nor modal parameters in advance, and could properly work in a noisy environment as well. View Full-Text
Keywords: random decrement technique; acceleration data; moving load; damage detection; Arias intensity random decrement technique; acceleration data; moving load; damage detection; Arias intensity
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Kordestani, H.; Xiang, Y.-Q.; Ye, X.-W.; Jia, Y.-K. Application of the Random Decrement Technique in Damage Detection under Moving Load. Appl. Sci. 2018, 8, 753.

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