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Multisensor Data Fusion for Bridge Condition Assessment
Considerable work has been carried out using a number of sensing technologies for condition assessment of civil infrastructure. Fewer efforts, however, have been directed for integrating the use of these technologies. This paper presents a newly developed method for automated condition assessment and rating of concrete bridge decks. The method integrates the use of ground-penetrating radar (GPR) and infrared thermography (IR) technologies. It utilizes a data-fusion technique to improve the accuracy of detecting defects and, accordingly, that of condition assessment. In this research, pixel-level image fusion is applied to assess bridge condition using these two technologies. GPR data are displayed as three-dimensional (3D) from 24 scans equally spaced by 0.33 m to interpret a section of a bridge deck surface in Montréal, Canada. The analysis of reflected amplitude waves is used to detect subsurface changed conditions. The GPR data are fused with infrared thermography images using a wavelet transform technique. Four scenarios based on image processing are studied and their application before and after data fusion is assessed in relation to accuracy of the employed fusion process. The concrete deck’s condition is assessed based on deteriorated areas that are extracted from the new fused image. Analysis of the results showed that bridge condition assessment can be improved with image fusion and this can enhance the capabilities of inspectors in interpretation of the results obtained.
Multisensor Data Fusion for Bridge Condition Assessment
Considerable work has been carried out using a number of sensing technologies for condition assessment of civil infrastructure. Fewer efforts, however, have been directed for integrating the use of these technologies. This paper presents a newly developed method for automated condition assessment and rating of concrete bridge decks. The method integrates the use of ground-penetrating radar (GPR) and infrared thermography (IR) technologies. It utilizes a data-fusion technique to improve the accuracy of detecting defects and, accordingly, that of condition assessment. In this research, pixel-level image fusion is applied to assess bridge condition using these two technologies. GPR data are displayed as three-dimensional (3D) from 24 scans equally spaced by 0.33 m to interpret a section of a bridge deck surface in Montréal, Canada. The analysis of reflected amplitude waves is used to detect subsurface changed conditions. The GPR data are fused with infrared thermography images using a wavelet transform technique. Four scenarios based on image processing are studied and their application before and after data fusion is assessed in relation to accuracy of the employed fusion process. The concrete deck’s condition is assessed based on deteriorated areas that are extracted from the new fused image. Analysis of the results showed that bridge condition assessment can be improved with image fusion and this can enhance the capabilities of inspectors in interpretation of the results obtained.
Multisensor Data Fusion for Bridge Condition Assessment
Moselhi, Osama (Autor:in) / Ahmed, Marwa (Autor:in) / Bhowmick, Anjan (Autor:in)
07.02.2017
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Multisensor Data Fusion for Bridge Condition Assessment
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