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Smart machining: Monitoring of CFRP milling using AE and IR
In aerospace industry, polymers reinforced with carbon fibre offer several advantages, such as weight/strength ratio and corrosion resistance. However, the manufacturing process is complex, especially the machining of composite materials, due to their specific properties and characteristics. The det...
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Published in: | Composite structures 2020-10, Vol.249, p.112611, Article 112611 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | In aerospace industry, polymers reinforced with carbon fibre offer several advantages, such as weight/strength ratio and corrosion resistance. However, the manufacturing process is complex, especially the machining of composite materials, due to their specific properties and characteristics. The detection and prediction of surface finishing and occurrence of defects during manufacturing using non-destructive techniques is industrially useful, in terms of fomenting automated manufacturing systems to increase productivity and quality control. Acoustic emission signal processing is being successful in mechanical tests for determining material defects, more recently used as a method for manufacturing evaluation of machined parts. This paper focused in the machining process of CFRP plate, in terms of surface finishing evaluation with comprehension of process phenomenology using analyses of temperature and acoustic emission signal features. The aim of this paper is to show the possibility of online monitoring of the cutting process and to understand mechanism behind variables of control, with comparisons of different milling parameters and focusing in their impacts in acoustic emission signals and surface finishing, with suggestions of evaluation and prediction methods of machined surface quality using mainly acoustic emission signals. |
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ISSN: | 0263-8223 1879-1085 |
DOI: | 10.1016/j.compstruct.2020.112611 |