Acoustic Emission Analysis for Online Monitoring in Sheet Metal Forming

• Applicant: Professor Dr.-Ing. Bernd-Arno Behrens
• Subject Area: Primary Shaping and Reshaping Technology, Additive Manufacturing
• Term: from 2014 to 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 263066528

In the sheet metal forming industry, the need for 100% inspection has been increasing due to the continuous demand on quality requirements and particularly due to the intensive use of high and ultra-high strength steels, increasing tool complexity as well as the required part accuracy. These processes are commonly automated, so the monitoring and early detection of occurring defects of the tool and the product are becoming increasingly necessary. The acoustic emission technique (AET) is a non-destructive testing method, which records the released elastic ultrasonic waves by sensors generated during the structural change of the material. Within the acoustic emission analysis, the recorded signals get analyzed and evaluated in order to draw conclusions about the condition of the process and / or product.The applicability of AET for characterizing defects due to deformation, crack initiation and phase transformation could be already proofed in several research studies. There are no scientific investigations dealing with online monitoring of sheet metal forming processes or with the determination of sheet metal forming defects above 300 kHz.Recording and analyzing of acoustic emission signals allows the process monitoring with regard of cracks, lack of lubrication, doubling of blanks or incorrect insertion of the blanks. The diversity of the monitored effects, phenomena and sizes as well as the variety of analytical methods (including time analysis, frequency analysis, time-frequency analysis, pattern recognition) have several options for using the AE method for different monitoring tasks in the field of sheet metal forming and should be investigated more precisely within this research project.

• DFG Programme: Research Grants (Transfer Project)
• Participating Institution: Daimler AG; Mercedes-Benz Werk Sindelfingen