An intelligent analysis method for DLC coating sp² / sp³ carbon hybridization ratio based on raman spectroscopy and one-dimensional convolutional neural network

Abstract

The present invention discloses an intelligent analysis method for the sp ² / sp ³ carbon hybridization ratio of DLC coatings based on Raman spectroscopy and one- dimensional convolutional neural networks, which belongs to the interdisciplinary technical field of material characterization and artificial intelligence.The present invention addresses the problems of complex operation, low accuracy, and poor automation of existing DLC coating sp ² / sp ³ ratio detection methods. The Raman spectra of DLC coatings are obtained through a Raman spectroscopy acquisition device, preprocessed by a data processing unit, and input into a pre trained one-dimensional 10 convolutional neural network model to achievesp ² / sp ³ ratio prediction. The results are then output and presented in a visualization unit for analysis.The present invention adopts an end-to-end deep learning architecture, which does not require manual preprocessing.