PVDF type AE sensor monitoring system for AL-7075 surface polishing using fiber laser
- Title
- PVDF type AE sensor monitoring system for AL-7075 surface polishing using fiber laser
- Author
- 이성환
- Keywords
- Laser post-processing; convolution neural network; surface defect; pvdf-type acoustic emission sensor
- Issue Date
- 2023-03-17
- Publisher
- SPIE
- Citation
- Proceedings of SPIE
- Abstract
- Selective laser melting (SLM) is a combined process of melting and stacking three-dimensional products by fusing
micro-metal powder using a laser. It has the advantage of manufacturing parts with complex structures with reduced
production time. However, in the case of aluminum, the disadvantages of poor laser formability due to its high thermal
conductivity, diffusivity, and reflectivity result in process defects such as bowling, pore, and poor surface quality. This study aims to develop a surface defect removal methodology during aluminum melting by laser processing and to enhance process automation capabilities by introducing a sensor monitoring scheme. In the laser experiments, aluminum specimens (AL-7075) with mechanical scratches were used and the level of surface defect removal during processing was classified depending on surface conditions. In addition, a PVDF-type acoustic emission (AE) sensor monitoring system was implemented to collect characteristic signals during the laser polishing of the machined surface(scratch). It was shown that the degree of surface defects removal and surface state could be effectively classified through a convolution neural network (CNN) utilizing the collected signals as input vectors
- URI
- https://information.hanyang.ac.kr/#/eds/detail?an=ejs62943922&dbId=edohttps://repository.hanyang.ac.kr/handle/20.500.11754/189544
- ISSN
- 0277-786X
- DOI
- 10.1117/12.2665278
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > MECHANICAL ENGINEERING(기계공학과) > Articles
- Files in This Item:
- 124091C.pdfDownload
- Export
- RIS (EndNote)
- XLS (Excel)
- XML