An Inversion Method Based on Inherent Similarity between Signals for Retrieving Source Mechanisms of Cracks

Abstract

The knowledge of cracking mechanisms is significant for evaluating the healthy condition of aircraft structures and can be retrieved by moment tensor inversion based on the acoustic emission (AE) phenomenon. For engineering applications, the inversion method cannot compute accurate results because the waveforms recorded by sensors are commonly contaminated by noise. Consequently, the correlation calculation of de-noising is introduced into the inversion and sufficient correlation functions are needed. In this paper, the correlation function of raw waveforms is proposed and based on the inherent similarity between the signals induced by one source and recorded by different sensors. According to the synthetic tests, the error of the inversion method based on the new correlation function is approximately 1/10 of that of the commonly used amplitude method. Although the inversion accuracy is influenced by the phase differences and the ratio of noise frequency to signal frequency, the influence is limited and the new correlation function is suitable for most practical cases. The inversion method based on the new correlation function does not require the knowledge of noise spectra or any complex calculation processes and provides a new way to improve the inversion accuracy of cracking mechanisms with little additional computation consumption.