Acoustic emission testing is a non-destructive inspection method in which ultrasonic waves emitted by defects in an object are detected and assessed based on their time of arrival and waveform, which strongly depends on the geometry of the object. Those waves appear in different modes with their own velocity and dispersion and different degrees of attenuation can occur for different wave modes. In previous work, a new method for (semi-)automatic recognition of the arrival time of wave modes was presented and validated on a dataset obtained in laboratory conditions on a flat plate. This paper builds upon the previous research and presents a modified method that can be applied to data obtained from an industrial gas storage sphere. The following two wave modes were commonly detected for this sphere: one similar to the zero-order anti-symmetrical mode (A0) and the other similar to the zero-order symmetrical Lamb mode (S0) in a plate. The method was adapted to solve the new challenges that were encountered for the sphere. The performance of the adapted automatic mode recognition method was assessed using a dataset with the following four different source types: Hsu–Nielsen sources, sensor pulses, impact by a metallic object and natural sources. The resulting wave mode recognition was compared to manual recognition to determine the rates of successful recognition. The resulting successful recognition rates range from 97% for A0 and S0 for Hsu–Nielsen sources down to 73% for A0 in signals due to natural sources and 74% for A0 in signals due to impact by a metallic object.
Büch et al. (Thu,) studied this question.