A fuzzy logic based approach for deterioration diagnosis in timber bridges

Current estimates show that there are about 40,000 bridges in Australia, of which 27,000 are aging timber bridges. Maintaining existing timber bridges is important to eliminate possibilities of structural collapse which can have catastrophic outcomes to the community. Aging timber bridges have a high maintenance cost. Relating different types of defects to possible underlying causes make deterioration diagnosis a complex task. Defects observed by bridge inspectors are usually reported in the form of natural language that contains intrinsic imprecision and uncertainty. In order to utilise the information to optimise the performance of the bridges, a knowledge base capturing the symptoms to causes is needed. This paper examines the feasibility of a diagnostic model based on the fuzzy logic approach in managing timber bridges. The inputs to the system are linguistic variables such as the type of element, the visual symptoms, the environmental conditions, method of construction and the location of the bridge. The expert system executes fuzzy inference to evaluate the cause of the distress using these input data and built in rules.