Evaluation of modal identification under base motion excitation using vision techniques

•Transmissibility functions under base excitation were obtained using DIC.•Transmissibility functions were adapted for FRF-based identification procedures.•The conversion of the data improved the modal identification and curve synthesis.•Dense maps of synthesis correlation and error highlight inaccuracies using the original data. In certain situations, employing a movable base acting as the excitation of a mechanical system is the best or even the only way to determine the response model for modal analysis. However, the obtained transmissibility functions must be modified prior to modal identification with a conventional procedure based on frequency response functions. Moreover, when employing vision techniques, the response curves are noisier and even poorly defined as the sensitivity is significantly lower than traditional sensors. Using the right model for curve-fitting is particularly relevant in this case. The current study performs an analysis of the adaptation of transmissibility functions, obtained by a vision technique, to improve the accuracy of the modal data estimation with conventional procedures. Two sets of transmissibility functions were evaluated: the originally obtained in the experiment, and the adapted one. After modal identification, significant differences were found concerning mode shapes and curve synthesis. The adaptation improved the accuracy of the identification in all the measurement points, proved by statistical indicators of the curve-fitting procedure like the correlation coefficient and the error between the synthesised and the experimental curves.