Impact localization on a composite stiffened panel using reference signals with efficient training process

Abstract

This paper suggests an efficient training process for estimating low-velocity impact locations on a composite stiffened panel using the reference signals. The reference signals were obtained from the fiber Bragg grating (FBG) sensor system suitable for on-board installation. Because such signals have low signal-to-noise ratio (SNR), they are not useful for most of previous studies with the time of arrival (TOA) or advanced signal processing. As the solutions to this weakness, the impact identification methods based on the reference database have been proposed. However, although some existing researches using the reference signals showed good localization performances, the training procedure to obtain the reference signals from much of training points is highly time-consuming. Aiming at this problem, an improved reference database impact localizing algorithm with reduced training points is presented in this article. To reduce the training points, the averaging signals with the adjacent reference signals are used as the imaginary reference signals of mid-points between each training points. As a result, the proposed algorithm could successfully estimate the impact locations within the allowable error bounds. (C) 2016 Elsevier Ltd. All rights reserved