LAUSR

Abstract A Data Consistency Assessment Function (DCAF) is developed to check the consistency of a measurement or set of measurements to all of the data in the entire data set. The inconsistent data can be precisely spotted and identified, which are recognized as the poorly measured data and can also be modified to be consistent with the rest of the data with an expansion process. The data can be either mode shapes, dynamic time response, frequency response functions or strain fields. Depending on the particular situation, three forms of the data expansion approach can be selected to implement the DCAF: System Equivalent Reduction Expansion Process (SEREP) with finite element model, SEREP with experimental mode shapes, and polynomial expansion. Some academic and industrial structures are used as examples to study the application of DCAF. Experimental data are used to validate the technique.