Towards an Abnormal Bridge Location Identification Method Based on Novelty Detection Technique

Abstract

The bridge structure abnormality recognition is one of the key steps of its health assessment. Using novelty detection technique based on BP neural network, the method to identify and locate abnormal bridge status was presented. It uses non-training-data in the original sample data to generate novelty indicator and determines threshold. If the difference between detection status indicator and normal value is larger than the threshold, the structure status is determined changed. The method adapts stepwise partition identification method. The method firstly determines damage position within a small range and then analyzes sensor data in detail, so as to locate specific position. The measured data on T beam model verifies the method can accurately carry out status identification and locate cracking position under cracking load conditions.