Partial least square/projection to latent structures (PLS) regression to estimate impact localization in structures

This paper presents results from the application of partial least squares/projection to latent structures (PLS) as a regression tool in order to estimate the localization of impacts in an aircraft structure using the strain wave produced by the impact and recorded by sensors attached to the structure. PLS is a technique that maximizes the covariance between the predictor matrix X and the predicted matrix Y for each component of the space. The main objectives of PLS are: to model X and Y, and to predict Y from X. The structure used in this work can be considered as a small scale version of a part of an aircraft wing. A total of 574 experiments were performed impacting the wing over its surface and receiving vibration signals from nine sensors. The data set (time history signal) is organized in a matrix to be used as predictors, while the predicted matrix is given by the real localization of the impact (x, y coordinates). Experiments are divided into four groups depending on their localization and probability of occurrence. A PLS model is built using three of these groups (X and Y) and tested using the remaining group. Results are presented, discussed and compared with other methods. (paper)