Acoustic Emission Analysis for Online Monitoring in Sheet Metal Forming

在板材成形行业，由于对质量要求的不断要求，特别是高强度和超高强度钢的大量使用，对100%检测的需求一直在增加，这增加了工具的复杂性以及对零件精度的要求。这些过程通常是自动化的，因此对工具和产品发生的缺陷进行监控和早期检测变得越来越必要。声发射技术(AET)是一种利用传感器记录材料结构变化过程中释放的弹性超声波的无损检测方法。在声发射分析中，对记录的信号进行分析和评估，以得出关于工艺和/或产品条件的结论。AET在表征变形、裂纹萌生和相变引起的缺陷方面的适用性已经在几项研究中得到证明。目前还没有关于在线监测板材成形过程或确定300 kHz以上板材成形缺陷的科学研究。通过记录和分析声发射信号，可以对过程中的裂纹、缺乏润滑、毛坯重叠或毛坯错误插入进行监控。由于监测的效果、现象和规模的多样性以及分析方法的多样性(包括时间分析、频率分析、时频分析、模式识别)，在板材成形领域的不同监测任务中使用声发射方法有几种选择，应该在本研究项目中进行更精确的调查。

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.