Diagnosis of structural damage based on data fusion and wavelet analysis method

A new structural damage diagnosis method based on data fusion and wavelet analysis method is presented. The measuring data from multi-sensors are fused by improved consensus algorithm. It overcomes the shortcoming of the traditional consensus algorithm with two sensors, which has different confidence distance for different measuring precision. And the supporting matrix is fuzzified, which can avoid the subjective error in determining the threshold value. The data from multi-sensors are processed by wavelet analysis using its noise reduction ability and multi-scales resolving power, and then the damage of the structures can be diagnosed. The effectiveness of the method is confirmed through numerical examples. It can be concluded that the method could make full use of the data from multi-sensors and it could get correct diagnosing result even when part of sensors is affected or fully disabled.