Development of methodology for enhancing visual bridge condition assessment using image processing techniques

Wi, H; Lee, J; Blumenstein, M; Guan, H; Loo, YC

Development of methodology for enhancing visual bridge condition assessment using image processing techniques

Wi, H Lee, J Blumenstein, M

Guan, H Loo, YC

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Publication Type:: Journal Article
Citation:: Applied Mechanics and Materials, 2013, 256-259 (PART 1), pp. 1563 - 1570
Issue Date:: 2013-01-31

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Field	Value	Language
dc.contributor.author	Wi, H	en_US
dc.contributor.author	Lee, J	en_US
dc.contributor.author	Blumenstein, M https://orcid.org/0000-0002-9908-3744	en_US
dc.contributor.author	Guan, H	en_US
dc.contributor.author	Loo, YC	en_US
dc.date.issued	2013-01-31	en_US
dc.identifier.citation	Applied Mechanics and Materials, 2013, 256-259 (PART 1), pp. 1563 - 1570	en_US
dc.identifier.isbn	9783037855652	en_US
dc.identifier.issn	1660-9336	en_US
dc.identifier.uri	http://hdl.handle.net/10453/121445
dc.description.abstract	Many bridge authorities have implemented Bridge Information Systems (BISs) or Bridge Management Systems (BMSs) to effectively manage their routine inspection information. The success of a BMS is highly dependent on the quality of bridge inspection outcomes and accurate estimation of future bridge condition ratings. To ensure such successful outcomes, a BMS must (1) contain reliable, consistent and accurate condition data from routine bridge inspections; and (2) encompass reliable deterioration modelling that overcomes the shortcomings of a lack of historical bridge inspection records. However published literature demonstrates that several limitations exist particularly in terms of inconsistency of inspection outcomes due to subjective judgment. To minimise such limitations, this paper presents a feasibility study for the enhancement of the current visual bridge inspection method using optical image processing techniques. The development work consists of image processing and knowledge-based approaches. It is anticipated that the proposed method is capable of minimising the shortcomings of subjective judgment on condition rating assessment and providing cost effective solutions to bridge agencies. Ultimately, the proposed bridge inspection methodology can provide consistent and accurate evaluation on the condition states of bridge elements. This in turn will lead to more reliable predictions of long-term bridge performance. © (2013) Trans Tech Publications, Switzerland.	en_US
dc.relation.ispartof	Applied Mechanics and Materials	en_US
dc.relation.isbasedon	10.4028/www.scientific.net/AMM.256-259.1563	en_US
dc.title	Development of methodology for enhancing visual bridge condition assessment using image processing techniques	en_US
dc.type	Journal Article
utslib.citation.volume	PART 1	en_US
utslib.citation.volume	256-259	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	closed_access
pubs.issue	PART 1	en_US
pubs.publication-status	Published	en_US
pubs.volume	256-259	en_US

Abstract:

Many bridge authorities have implemented Bridge Information Systems (BISs) or Bridge Management Systems (BMSs) to effectively manage their routine inspection information. The success of a BMS is highly dependent on the quality of bridge inspection outcomes and accurate estimation of future bridge condition ratings. To ensure such successful outcomes, a BMS must (1) contain reliable, consistent and accurate condition data from routine bridge inspections; and (2) encompass reliable deterioration modelling that overcomes the shortcomings of a lack of historical bridge inspection records. However published literature demonstrates that several limitations exist particularly in terms of inconsistency of inspection outcomes due to subjective judgment. To minimise such limitations, this paper presents a feasibility study for the enhancement of the current visual bridge inspection method using optical image processing techniques. The development work consists of image processing and knowledge-based approaches. It is anticipated that the proposed method is capable of minimising the shortcomings of subjective judgment on condition rating assessment and providing cost effective solutions to bridge agencies. Ultimately, the proposed bridge inspection methodology can provide consistent and accurate evaluation on the condition states of bridge elements. This in turn will lead to more reliable predictions of long-term bridge performance. © (2013) Trans Tech Publications, Switzerland.

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http://hdl.handle.net/10453/121445