Detection and Identification of Different Metal Materials with Same Damage of Stretching Based on Acoustic Emission in Audible Domain

Analysis of metallic materials damage signal is effective for studying strength failure.Domestic and foreignscholars do much workbased on acoustic emission due to its real-time detection. Most researches are in ultrasonic region, few in audible domain. In this paper, taking low-carbon steel and cast iron as an example, we collected acoustic emission signals during tensile tests. Thenestablishassociated diagrams of processed signals, with multivariable parameter analysis used for eigenvalue processing. After normalizing data,wefigured out ranges of synthetic parameters. The experiment and calculation results show that eigenvalue of every low-carbon steel in one certain event is greater than cast iron’s. As a result,synthetic parameters canmake significant effect in detecting and identifying different metal materials