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采用感应焊接修复热塑性复合材料受冲击层压板

Repair of Impacted Thermoplastic Composite Laminates Using Induction Welding.

作者信息

Modi Vedant, Bandaru Aswani Kumar, Ramaswamy Karthik, Kelly Conor, McCarthy Conor, Flanagan Tomas, O'Higgins Ronan

机构信息

Bernal Institute, School of Engineering, University of Limerick, V94 T9PX Limerick, Ireland.

ÉireComposites, H91 Y923 Galway, Ireland.

出版信息

Polymers (Basel). 2023 Jul 29;15(15):3238. doi: 10.3390/polym15153238.

DOI:10.3390/polym15153238
PMID:37571135
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10421161/
Abstract

The lack of well-developed repair techniques limits the use of thermoplastic composites in commercial aircraft, although trends show increased adoption of composite materials. In this study, high-performance thermoplastic composites, viz., carbon fibre (CF) reinforced Polyetherketoneketone (PEKK) and Polyether ether ketone (PEEK), were subjected to low-velocity impact tests at 20 J. Post-impact, the damaged panels were repaired using an induction welder by applying two different methods: induction welding of a circular patch to the impacted area of the laminate (RT-1); and induction welding of the impacted laminates under the application of heat and pressure (RT-2). The panels were subjected to compression-after-impact and repair (CAI-R), and the results are compared with those from the compression-after-impact (CAI) tests. For CF/PEKK, the RT-1 and RT-2 resulted in a 13% and 7% higher strength, respectively, than the value for CAI. For CF/PEEK, the corresponding values for RT-1 and RT-2 were higher by 13% and 17%, respectively. Further analysis of the damage and repair techniques using ultrasonic C-scans and CAI-R tests indicated that induction welding can be used as a repair technique for industrial applications. The findings of this study are promising for use in aerospace and automotive applications.

摘要

尽管趋势显示复合材料的应用有所增加,但缺乏成熟的修复技术限制了热塑性复合材料在商用飞机中的使用。在本研究中,对高性能热塑性复合材料,即碳纤维(CF)增强聚醚酮酮(PEKK)和聚醚醚酮(PEEK),进行了20 J的低速冲击试验。冲击后,使用感应焊机通过两种不同方法对受损面板进行修复:将圆形补片感应焊接到层压板的冲击区域(RT-1);以及在加热和加压的情况下对冲击后的层压板进行感应焊接(RT-2)。对面板进行冲击后压缩及修复(CAI-R)试验,并将结果与冲击后压缩(CAI)试验的结果进行比较。对于CF/PEKK,RT-1和RT-2的强度分别比CAI的值高13%和7%。对于CF/PEEK,RT-1和RT-2的相应值分别高13%和17%。使用超声C扫描和CAI-R试验对损伤和修复技术进行的进一步分析表明,感应焊接可作为一种工业应用的修复技术。本研究的结果在航空航天和汽车应用方面很有前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/fb6dbb5c46d1/polymers-15-03238-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/2232084d3acb/polymers-15-03238-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/80ca827f26c9/polymers-15-03238-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/ef111bb8e010/polymers-15-03238-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/9da73027bdad/polymers-15-03238-g004a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/9ca7d3b4b4d9/polymers-15-03238-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/d5a135693a54/polymers-15-03238-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/6c83fbcf09d9/polymers-15-03238-g007a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/de19174e9a96/polymers-15-03238-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/fb6dbb5c46d1/polymers-15-03238-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/2232084d3acb/polymers-15-03238-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/80ca827f26c9/polymers-15-03238-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/ef111bb8e010/polymers-15-03238-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/9da73027bdad/polymers-15-03238-g004a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/9ca7d3b4b4d9/polymers-15-03238-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/d5a135693a54/polymers-15-03238-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/6c83fbcf09d9/polymers-15-03238-g007a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/de19174e9a96/polymers-15-03238-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/113f/10421161/fb6dbb5c46d1/polymers-15-03238-g009.jpg

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本文引用的文献

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Multi-objective optimisation of ultrasonically welded dissimilar joints through machine learning.通过机器学习对超声焊接异种接头进行多目标优化。
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