Failure Characterization of Al-Zn-Mg Alloy and Its Weld Using Integrated Acoustic Emission and Digital Image Techniques

• Published in: Metals (Basel ) Vol. 14; no. 2; p. 190
• Main Authors: Zhu, Ronghua, Chi, Dazhao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2024
• Subjects: Acoustic emission; Acoustic emission testing; AE source mechanisms; Alloys; Aluminum; aluminum alloy; Aluminum alloys; Aluminum base alloys; Analysis; Behavior; Centroids; Corrosion; Crack initiation; Crack propagation; Damage; damage evolution; Digital imaging; Electric railroads; Energy; Evolution; Magnesium; Metal fatigue; Methods; Microstructure; Peak frequency; Propagation; Railcars; Seam welds; Sensors; Specialty metals industry; Static loads; Stress concentration; Time-frequency analysis; Waveform analysis; Wavelet transforms; Welded structures; Zinc compounds
• ISSN: 2075-4701; 2075-4701
• DOI: 10.3390/met14020190

The three-point bending damage process of an A7N01 aluminum alloy body material and weld seam in an electric multiple unit train was monitored using acoustic emission (AE) and digital image technology. The AE signal characteristics of static load damage to the aluminum alloy and weld seam were studied using the AE signal parameter and time–frequency analysis. Based on the observation of the microstructure and fracture morphology, the source mechanism of AE signals was analyzed. The experimental results indicate that AE energy, centroid frequency, and peak frequency are effective indices for predicting the initiation of cracks in A7N01 aluminum alloy and weld seams. The digital image monitoring results of the notch tip damage evolution of aluminum alloy samples confirmed the predictions based on AE energy, centroid frequency, and peak frequency for crack initiation. The AE signal source mechanism revealed that the differences in AE characteristics between the base material and weld seam can be attributed to microstructure variations and fracture modes. In summary, the AE technique is more sensitive to changes in the fracture mode and can be utilized to monitor the damage evolution of welded structures.