As structures are becoming more and more complicated

large amounts of measuring data have to be acquired for the effective evaluation of the large-scale civil engineering structures.So it is very necessary to adopt multi-sensors in health monitoring.The purpose of data fusion is to combine and process the data from multi-sensors

thus to obtain much more exact and reliable results than that of the single sensor’s.An improved data fusion method for commensurate sensors is presented in this paper.It overcomes the shortcoming of the traditional consensus algorithm with two sensors

which has different confidence distance while measuring in different precision.The relation matrix is fuzzified to avoid the subjective error in determining the threshold value and the effectiveness of this method is confirmed through a numerical example.It can be concluded that this method can get good data fusion result and efficiently reduce the change of the measuring result due to external disturbance.