Signal Recognition of Acoustic Emission from Microstrutures in Composite Laminates
Tliermo-plastic composite materials commonly have weak fiber/matrix bonded strength due to their poor resin penetration. Several micro-defects, including fiber-breakage, fiber/matrix debonding, transverse matrix cracking, are frequently observed in thermo-plastic composites. Most previous researches characterized acoustic emission (AE) in composites often by temporal parameters. The frequency characteristics were also ignored from AE signals captured by resonant transducers. The propagation of AE waves in composite laminates is complex because of the anisotropy and dispersion. In this study several micro-fractures were induced in large-sized laminates made of glass fiber-reinforced, thermo-plastic composite during well-designed tensile and bending tests. The fractures were monitored by two broadband piezoelectric AE sensors mounted on surfaces of the specimens at 0° and 90° orientations to the fibers. The time-frequency patterns of those AE signals were determined by the continuous wavelet transform. Pattern recognition was carried out by back-propagation neural network through the characteristic parameters in frequency domain. A very good results of the AE signal recognition have been achieved.
|Appears in Collections:||Thesis|