System and method for Raman signal identification based on depth machine learning model

A machine learning model, Raman signal technology, applied in the optical detection and optical fields, can solve the problems of inaccuracy and instability of the analysis results, and achieve the effect of fast and effective method and fast denoising.

Pending Publication Date: 2019-01-11
THE THIRD RES INST OF MIN OF PUBLIC SECURITY
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These sources of interference will bring inaccuracy and instability to subsequent analysis results

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • System and method for Raman signal identification based on depth machine learning model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] In order to describe the technical content of the present invention more clearly, further description will be given below in conjunction with specific embodiments.

[0033] The system for realizing Raman signal data processing and identification functions based on the deep machine learning model of the present invention includes:

[0034] An optical probe, connected to the spectrometer, is used to receive the laser beam emitted by the spectrometer and make the laser beam contact the surface of the sample, and collect the Raman signal of the sample;

[0035] Described spectrometer comprises:

[0036] A laser, connected to the optical probe, is used to emit a laser beam;

[0037] A processor, connected to the laser, is used to control the processor to process data and control other modules of the processor;

[0038] A signal preprocessing module, connected to the processor, for preprocessing the Raman signal data of the sample;

[0039] The deep machine learning model ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a Raman signal data processing and identification system based on a depth machine learning model, the system comprising a spectrometer for receiving a Raman signal of a sample; an optical probe is connected with the spectrometer; the spectrometer includes a laser for emitting a laser beam; a processor is configured to control the processor to process data and to control the remaining modules of the processor. A signal pre-processing module is used to pre-process the Raman signal data of the sample. The depth machine learning model data processing module is used for automatically analyzing the Raman signal data of the sample and training the classifier according to the data analysis tool. The sample classification and labeling module is used for classifying and labeling the sample data by the classifier. The display is used to display signal data. The system and the method for processing and identifying the Raman signal data based on the depth machine learning model can realize the automatic and fast denoising of the original Raman data collected by the Raman spectrometer and the intelligent recognition and classification of the effective signals.

Description

technical field [0001] The present invention relates to the field of optics, in particular to the field of optical detection technology, and specifically refers to a system and method for realizing Raman signal data processing and identification functions based on a deep machine learning model. Background technique [0002] Raman spectroscopy is a technology proposed by Indian scientist Raman in the 1920s. The birth of lasers in the 1960s brought room for development in the application of Raman spectroscopy. Raman spectroscopy has been widely used as an effective detection and analysis method due to its rich material property information, non-destructive testing, and no need for sample preparation. It is an important part of modern material characteristic analysis technology. The early Raman spectrometers were large in size and inconvenient to install, and were mainly used in laboratories. With the continuous advancement of optoelectronics, embedded software and hardware, a...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06K9/00G06N3/02
CPCG06N3/02G06F2218/04G06F2218/12G06F18/24
Inventor 何蔚
Owner THE THIRD RES INST OF MIN OF PUBLIC SECURITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap