工艺与制造英文2021被引 16
基于人工智能的高性能热塑性复合材料连续超声焊缝质量预测
Quality Prediction of Continuous Ultrasonic Welded Seams of High-Performance Thermoplastic Composites by means of Artificial Intelligence
D. Görick, Lars Larsen, Manuel Engelschall, Alfons Schuster · Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
摘要整理
热塑性复合材料(TCs)因其优异的性能在工业应用中得到广泛应用。随着该材料需求的增加,评估合适的加工工艺变得尤为重要。连续超声焊接(CUSW)是一种重要的加工技术,可在两个或多个热塑性复合材料零件之间形成连续接头(焊缝)。在CUSW工艺中,机械振动被施加到材料上,导致焊接部分熔融并相互连接。本研究通过训练不同的神经网络模型来预测连续超声焊接热塑性复合材料的接头强度(质量等级)。采用全连接神经网络实现了约72%的质量等级预测准确率。研究表明,利用人工智能进行焊接热塑性复合材料的质量预测是一种可行的质量监测方法,但需要进一步研究以开发更可靠的神经网络模型,以满足工业应用需求。
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