Acoustic emission signal analysis and event extraction through tuned wavelet packet transform and continuous wavelet transform while tensile testing the AA 2219 coupon

Abstract

Aluminium Alloy AA 2219 is the principal metal for the production of propellant reservoir used in launch vehicles. The propellant tanks are often proof tested with acoustic emission technique (AET) to ensure its health. Acoustic Emission Testing during the structural health monitoring and proof testing is complex and unrealistic occasionally as it is performed in the noisy environment. Identification of signature corresponds to crack and its extraction from noise signatures is a major challenge in AET. Wavelet Packet Transform is an efficient mathematical tool for the analysis of AE signals. This paper recommends a novel combination of normalized cross correlation, Wavelet Packet Transform and Continuous wavelet transform to detect and extract the event related to failure. Experiments were carried out on AA 2219 tensile coupons at different threshold conditions. The recorded AE hits contain signals related to different events such as atmospheric noise, rubbing noise and other noise signals along with the signals from cracks. By applying the fine tuned wavelet packet transform technique in combination with CWT, the extraction of denoised single event related to crack was executed. Based on the frequency and the wavelet coefficient the crack related hits and the noisy hits are categorized.