Gaussian mixture model–based path-synthesis accumulation imaging of guided wave for damage monitoring of aircraft composite structures under temperature variation

Abstract

With the capabilities of achieving large-scale monitoring, improving signal-to-noise ratio, and obtaining a high localization accuracy and strong fault tolerance, guided wave and piezoelectric sensor network–based damage imaging technique seems to be the key technique to realize damage localization of complex aircraft composite structures. However, aircraft structures usually work under random and complicated time-varying conditions, which may introduce nonnegligible uncertainties in the acquired guided wave signals and mask the subtle changes caused by damage. The current damage imaging methods barely consider this time-varying issue and are unable to reliably locate damage. To increase reliability, a Gaussian mixture model–based guided wave path-synthesis accumulation imaging method is proposed for damage imaging of complex aircraft composite structures under time-varying conditions. The Gaussian mixture model is used to suppress time-varying influence and achieve time-varying-independent damage characterization, based on which the guided wave path-synthesis imaging is conducted to perform the fusion of sensor network information and generate an image. During the monitoring process, a series of images will be generated with damage information accumulated, and the damage will gradually emerge in these images and can be located eventually. The typical time-varying condition, temperature variation, is chosen to verify the feasibility and effectiveness of the proposed method on a stiffened carbon fiber composite plate; the results show good performance of reliable damage imaging and localization within a temperature range from 0°C to 60°C.