Abstract

Current steel tubes inspection techniques are invasive, and the interpretation and evaluation of inspection results are manually done by skilled personnel. Part A of this work details the methodology involved in the newly developed non-invasive, non-destructive tube inspection technique based on the integration of vibration impact (VI) and acoustic emission (AE) systems known as the vibration impact acoustic emission (VIAE) technique. AE signals have been introduced into a series of ASTM A179 seamless steel tubes using the impact hammer. Specifically, a good steel tube as the reference tube and four steel tubes with through-hole artificial defect at different locations were used in this study. The AEs propagation was captured using a high frequency sensor of AE systems. The present study explores the cluster analysis approach based on autoregressive (AR) coefficients to automatically interpret the AE signals. The results from the cluster analysis were graphically illustrated using a dendrogram that demonstrated the arrangement of the natural clusters of AE signals. The AR algorithm appears to be the more effective method in classifying the AE signals into natural groups. This approach has successfully classified AE signals for quick and confident interpretation of defects in carbon steel tubes.

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