Development of Methodology for Enhancing Visual Bridge Condition Assessment Using Image Processing Techniques

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.