APPLICATION OF MULTIVARIATE ACOUSTIC EMISSION PARAMETERS IN DAMAGE MONITORING AND ASSESSMENT OF A LOW-ALLOYED STEEL

Acoustic Emission (AE) as a nondestructive evaluation technique has been frequently utilized to monitor the damage progression of materials and structures. Analysis based on multivariate features is more viable in completely understanding the damage progression than using only one single or limited AE parameters. Program or software facilitates the processing of AE data by finishing the feature extraction and other analysis work. This article presents the application of multivariate AE parameters in damage analysis and evaluation of a low-alloyed steel. An AE software system to understand the AE events multi-dimensionally is developed. The software is capable of feature extraction, visualization, variational mode decomposition (VMD) and Hilbert-Huang transform (HHT) for the source mechanism analysis. The AE signals generated from three-point bending of Cr-Mo steel was processed and analyzed to verify the viability of the system. Nineteen different AE features are calculated from time and frequency domains. The variation of different features associated with AE events among different stages of the test are discussed. Moreover, AE signals are decomposed by VMD into several modes that indicate the dominant frequency of AE events. Hilbert spectrum obtained via HHT presents the amplitude of AE signal in both time and frequency domain. The results of the application may provide insights in multivariate feature extraction and methods of damage assessment in metallic materials and engineering structures.