Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position Characteristics
In the nickel electrolysis industry, detection of the conductive state of copper rods is an important part of production procedure management, as abnormal conductive states of the copper rod result in a decline in the quality of the electrodeposited nickel plate. Conventional treatment consists of m...
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MDPI AG
2022-04-01
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author | Rui Sun Gang Qin Gaibian Li Jinbao Hu Jingqi Xiong Huanwei Xu |
author_facet | Rui Sun Gang Qin Gaibian Li Jinbao Hu Jingqi Xiong Huanwei Xu |
author_sort | Rui Sun |
collection | DOAJ |
description | In the nickel electrolysis industry, detection of the conductive state of copper rods is an important part of production procedure management, as abnormal conductive states of the copper rod result in a decline in the quality of the electrodeposited nickel plate. Conventional treatment consists of manual detection and handing, which is inefficient and induces more problems, such as the safety of the insulation. Because abnormal conductive states are only located between the copper rod and busbar, it has obvious position characteristics, and abnormal conductive states also induce a calorific difference in a particular area, which can be detected in an infrared image. We can use the infrared feature and position characteristics to identify the abnormal conductive faults. This paper introduces a method and practice for the identification of abnormal conductive faults in a conductive copper rod in the nickel electrolysis procedure using computer vision theory, including infrared image segmentation with position characteristics, infrared feature extraction, and conductive fault identification with SVM (support vector machine). The result shows that the method can divide the conductive states of the copper rod into abnormal heating conditions, normal operating conditions, and open circuit conditions, with a 90% accuracy rate on the obtained samples. |
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language | English |
last_indexed | 2024-03-09T12:04:35Z |
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spelling | doaj.art-44049ea610d74cc39bc63f92d3d6e1912023-11-30T22:59:12ZengMDPI AGApplied Sciences2076-34172022-04-01127369110.3390/app12073691Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position CharacteristicsRui Sun0Gang Qin1Gaibian Li2Jinbao Hu3Jingqi Xiong4Huanwei Xu5School of Mechanical and Electrical Engineering, University of Electronical Science and Technology of China, Chengdu 611731, ChinaSchool of Mechanical and Electrical Engineering, University of Electronical Science and Technology of China, Chengdu 611731, ChinaJinChuan Group Co., Ltd., Jinchang 737100, ChinaJinChuan Group Co., Ltd., Jinchang 737100, ChinaSchool of Mechanical and Electrical Engineering, University of Electronical Science and Technology of China, Chengdu 611731, ChinaSchool of Mechanical and Electrical Engineering, University of Electronical Science and Technology of China, Chengdu 611731, ChinaIn the nickel electrolysis industry, detection of the conductive state of copper rods is an important part of production procedure management, as abnormal conductive states of the copper rod result in a decline in the quality of the electrodeposited nickel plate. Conventional treatment consists of manual detection and handing, which is inefficient and induces more problems, such as the safety of the insulation. Because abnormal conductive states are only located between the copper rod and busbar, it has obvious position characteristics, and abnormal conductive states also induce a calorific difference in a particular area, which can be detected in an infrared image. We can use the infrared feature and position characteristics to identify the abnormal conductive faults. This paper introduces a method and practice for the identification of abnormal conductive faults in a conductive copper rod in the nickel electrolysis procedure using computer vision theory, including infrared image segmentation with position characteristics, infrared feature extraction, and conductive fault identification with SVM (support vector machine). The result shows that the method can divide the conductive states of the copper rod into abnormal heating conditions, normal operating conditions, and open circuit conditions, with a 90% accuracy rate on the obtained samples.https://www.mdpi.com/2076-3417/12/7/3691abnormal conductivestate identificationinfrared imageposition characteristics |
spellingShingle | Rui Sun Gang Qin Gaibian Li Jinbao Hu Jingqi Xiong Huanwei Xu Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position Characteristics Applied Sciences abnormal conductive state identification infrared image position characteristics |
title | Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position Characteristics |
title_full | Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position Characteristics |
title_fullStr | Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position Characteristics |
title_full_unstemmed | Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position Characteristics |
title_short | Abnormal Conductive State Identification of the Copper Rod in a Nickel Electrolysis Procedure Based on Infrared Image Features and Position Characteristics |
title_sort | abnormal conductive state identification of the copper rod in a nickel electrolysis procedure based on infrared image features and position characteristics |
topic | abnormal conductive state identification infrared image position characteristics |
url | https://www.mdpi.com/2076-3417/12/7/3691 |
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