Raman spectrum data analysis method and device based on deep learning

Abstract

The invention relates to a Raman spectrum data analysis method and device based on deep learning. The method comprises the following steps: analyzing Raman spectrum data characteristics of a substance; manually labeling substance Raman spectrum data categories, and establishing a Raman spectrum training set, a verification set and a test set; in order to solve the problems that Raman spectrum data is preprocessed, spectrums are easily interfered by ambient light and Raman spectrum data of the same type of tissues are different, constructing a deep residual neural network model based on multi-scale feature fusion, employing ResNet50 as a model backbone network, fusing Raman spectrum feature information, and improving the spectrum space semantic information characterization capability; training the Raman spectrum analysis model by using the training set, and evaluating the performance of the model on the verification set and the test set; and finally, deploying the trained model to edge computing equipment, and constructing a Raman spectrum data analysis device. The Raman spectrum data can be efficiently and accurately analyzed and identified, and the method can be applied to different types of Raman spectrum equipment.

Description

technical field [0001] This patent relates to the field of Raman spectral data analysis, in particular to a method and device for analyzing Raman spectral data based on deep learning. Background technique [0002] Raman spectroscopy is a molecular structure characterization technology based on the Raman effect, and has been widely used in materials, biomedicine, petrochemicals, polymers and other fields. The Raman spectral signal contains a wealth of molecular fingerprint information, and it is necessary to combine data statistics methods to analyze the front, peak and band spectral features, and then identify the detected material properties. However, Raman spectral information is often accompanied by strong fluorescent background noise and external environmental interference information. At the same time, due to the performance problems of different Raman spectral detection equipment, the detected Raman spectral information of the same type of substance has certain differe...

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Problems solved by technology

[0004] The purpose of the present invention includes three: (1) solve the problem of loss of characteristic information of Raman spectrum original data caused by preprocessing; (2) solve the problem of low identification accuracy of Raman spectrum of substances caused by ambient light interference; (3) solve the problem of The problem of low accuracy of Raman spectrum identification due to the difference in Raman spectrum data of the same type of substance

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