A lightweight convolutional neural network model for quantitative analysis of phosphate ore slurry based on laser-induced breakdown spectroscopy-Reference-Cited by-同舟云学术

A lightweight convolutional neural network model for quantitative analysis of phosphate ore slurry based on laser-induced breakdown spectroscopy

Published:2021 Issue:11 Volume:36 Page:2528-2535
ISSN:0267-9477
Container-title:Journal of Analytical Atomic Spectrometry
language:en
Short-container-title:J. Anal. At. Spectrom.

Author:

Dong Haiyan¹²³⁴⁵,Sun Lanxiang¹²³⁵^ORCID,Qi LiFeng¹²³⁵,Yu HaiBin¹²³⁵,Zeng Peng¹²³⁵

Affiliation:

1. State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

2. Key Laboratory of Networked Control System, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China

3. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China

4. University of Chinese Academy of Sciences, Beijing 100049, China

5. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

Abstract

Taking the raw spectrum as input data, a lightweight convolutional network architecture estimates quantitatively chemical content due to removing pooling operation, activation function and incorporating inception module.

Funder

National Key Research and Development Program of China

Key Research Program of Frontier Science, Chinese Academy of Sciences

Science and Technology Service Network Plan

Youth Innovation Promotion Association of the Chinese Academy of Sciences

Liaoning Revitalization Talents Program

Publisher

Royal Society of Chemistry (RSC)

Subject

Spectroscopy,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/JA/D1JA00209K

Reference28 articles.

1. A review of zinc oxide mineral beneficiation using flotation method

2. An overview of the beneficiation of iron ores via reverse cationic flotation

3. CALCULATION OF MINERAL COMPOSITION FROM CHEMICAL ASSAYS

4. Practical way to quantify minerals from chemical assays at Malmberget iron ore operations – An important tool for the geometallurgical program

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