Unlock instant, AI-driven research and patent intelligence for your innovation.

Garnet Subclass Recognition Method Based on Thermal Infrared Spectral Features and BP Neural Network Model

A BP neural network, garnet technology, applied in the field of garnet subclass classification, to achieve the effect of good technical inspiration

Active Publication Date: 2022-02-15
INST OF MINERAL RESOURCES CHINESE ACAD OF GEOLOGICAL SCI
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Grossmantine and spessartine have obvious reflection peak wavelength characteristics, while the reflection peak wavelengths of almandine and pyrope, andandandite and pyrope have a large overlapping area, which cannot be directly distinguished. Therefore, it is necessary to find A method capable of determining the mapping relationship between reflection peak wavelength and subclass type of garnet thermal infrared spectrum

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
  • Garnet Subclass Recognition Method Based on Thermal Infrared Spectral Features and BP Neural Network Model
  • Garnet Subclass Recognition Method Based on Thermal Infrared Spectral Features and BP Neural Network Model
  • Garnet Subclass Recognition Method Based on Thermal Infrared Spectral Features and BP Neural Network Model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0043] Embodiment 1 BP Neural Network Model Construction Method for Identifying Garnet Subtypes Based on Thermal Infrared Spectrum Features

[0044] The method of constructing BP neural network model based on thermal infrared spectral features and garnet subtypes is as follows: figure 1 As shown, the specific steps are as follows:

[0045] 1. Acquisition of thermal infrared spectral characteristic data of garnet samples of known subtypes

[0046]The thermal infrared spectral characteristic data of 85 garnet samples were extracted from the thermal infrared spectral library (Table 1), including 18 almandine, 15 andandrite, 25 andandroid, 18 The wavelength data of the reflection peaks of pyrope, 6 spessartines, and 3 garnets in the 9-13μm spectrum, that is, the wavelength of reflection peak 1, the wavelength of reflection peak 2, and the wavelength of reflection peak 3, and reflection peak wavelength difference information, reflection peak 3 wavelength minus reflection peak 2 w...

Embodiment 2

[0070] Embodiment 2 Based on the thermal infrared spectrum characteristics and the BP neural network model constructed in Embodiment 1, the method for identifying the garnet subtype of the sample to be tested

[0071] Obtain the thermal infrared spectrum characteristic data of the garnet sample to be tested, that is, the first reflection peak wavelength, the second reflection peak wavelength, the third reflection peak wavelength, and the third reflection peak and The wavelength difference of the second reflection peak, wherein the third reflection peak wavelength is greater than the second reflection peak wavelength and greater than the first reflection peak wavelength;

[0072] By inputting the feature data into the BP neural network model constructed as described in Example 1, the subtype of the garnet sample to be tested can be identified.

[0073] It can be seen from the identification results obtained by verifying the sample in Example 1 that the present invention obtains...

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 discloses a garnet subclass identification method based on thermal infrared spectrum features and a BP neural network model. The garnet subclass identification method of the present invention comprises: obtaining thermal infrared spectral characteristic data of garnet samples of known subclass types; constructing a BP neural network model by using the subclass type and thermal infrared spectral characteristic data of the garnet samples; Obtain the thermal infrared spectrum characteristic data of the garnet sample to be tested, input the constructed BP neural network model, and identify the subtype of the garnet sample to be tested. Based on the rich information in the thermal infrared spectrum of garnet and the nonlinear automatic mapping capability of the BP neural network model, the present invention identifies garnet subtypes, provides fast and effective technical support for garnet subtype identification, and provides support for other minerals. Provide technical inspiration for the rapid identification of .

Description

technical field [0001] The present invention relates to the field of classification of garnet subgroups. More specifically, it relates to a method for identifying garnet subtypes based on thermal infrared spectroscopy and BP neural network models. Background technique [0002] Garnet is a general term for silicate minerals with an island structure, and the chemical formula is X 3 Y 2 [ZO 4 ] 3 , where X represents divalent cations of calcium, iron, magnesium, and manganese, Y represents trivalent cations of aluminum, iron, chromium, and manganese, and Z generally represents tetravalent cations of silicon. According to the characteristics of X-position and Y-position cations, the currently known garnet minerals can be divided into two categories: calcium series garnets and aluminum series garnets. Calcium-series garnets include wandralite, andandroid, and pyrope, and aluminum-series garnets include spessartine, almandine, pyrope, and other subcategories. The traditional...

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 Patents(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06N3/047G06N3/048G06N3/045G06F2218/10G06F2218/12G06F18/241G06F18/2415
Inventor 代晶晶刘婷玥林彬
Owner INST OF MINERAL RESOURCES CHINESE ACAD OF GEOLOGICAL SCI