Research on Monitoring Method of Micro-damage in Composite Assembly Drilling Holes based on Machine Learning
Aimed to develop a composite material assembly hole micro-damage monitoring method based on machine learning.In view of the problems of delamination damages which were easily caused during the process of drilling holes in carbon fiber reinforced composite materials(CFRP),it was collected that mechanical signals,acoustic emission signals,and temperature signals,and machine learning models were used to achieve real-time monitoring of micro-damage in the drilling process of carbon fiber reinforced composite materials(CFRP).The research contents included theoretical research,experi-mental research,signal processing,model construction,monitoring system design and so on,so as to form a set of compos-ite material micro-damage control methods based on process parameters and tool angle coupling constraints.It achieved cer-tain technical indicators,and pointed out the direction for future research.
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