Multi-Sensor Feature Extraction and Data Fusion Using ANFIS and 2D Wavelet Transform in Structural Health Monitoring

Abstract

In this chapter, a novel feature extraction and data fusion approach for structural damage detection and localisation is presented. This approach combines adaptive network-based fuzzy inference systems (ANFIS) and two-dimensional wavelet transform (2D-WT) technologies. Simultaneous multi-sensor feature extraction and data fusion based on 2D-WT is carried out by forming a 2D multivariate signal, which is used to analyse the structure vibration response by measuring all sensors jointly. Energy values obtained from two-level db3 wavelet decomposition are arranged in a so-called energy percentage matrix (EPM), which is taken as an input for the ANFIS. The system is further trained by defining its output as the structural condition represented by a condition index. A set of output index patterns are defined depending on the level of damage assessment performed. The proposed method was tested through experiments using a cantilever beam structure. The testing results showed that the method is successful in detecting and localising damage by vibration analysis in structural health monitoring.