A Feasibility Study on Damage Detection of three Cable-Supported Bridges in Hong Kong using Vibration Measurement

Abstract

A feasibility study on vibration-based damage detection methods for the three cable supported bridges in Hong Kong is carried out. Emphasis is placed on how to deal with the noise corrupted/uncertain measurement data and how to use the series data from the on-line monitoring system for damage detection. Numerical simulation studies of using the noisy series measurement modal data for damage occurrence detection in terms of the auto-associative neural network arc presented. Neural network based novelty detectors using only natural frequencies of the intact and damaged structure are developed for the detection of damage occurrence in the three bridges. The noisy/uncertain measurement data are produced by polluting the analytical natural frequencies with random noise. Numerical simulations of a series of damage scenarios show that when the maximum frequency change caused by damage exceeds a cel1ain threshold, the occurrence of damage can be unambiguously flagged with the novelty detectors.