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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Main Authors: Rui Sun, Gang Qin, Gaibian Li, Jinbao Hu, Jingqi Xiong, Huanwei Xu
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/12/7/3691
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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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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
work_keys_str_mv AT ruisun abnormalconductivestateidentificationofthecopperrodinanickelelectrolysisprocedurebasedoninfraredimagefeaturesandpositioncharacteristics
AT gangqin abnormalconductivestateidentificationofthecopperrodinanickelelectrolysisprocedurebasedoninfraredimagefeaturesandpositioncharacteristics
AT gaibianli abnormalconductivestateidentificationofthecopperrodinanickelelectrolysisprocedurebasedoninfraredimagefeaturesandpositioncharacteristics
AT jinbaohu abnormalconductivestateidentificationofthecopperrodinanickelelectrolysisprocedurebasedoninfraredimagefeaturesandpositioncharacteristics
AT jingqixiong abnormalconductivestateidentificationofthecopperrodinanickelelectrolysisprocedurebasedoninfraredimagefeaturesandpositioncharacteristics
AT huanweixu abnormalconductivestateidentificationofthecopperrodinanickelelectrolysisprocedurebasedoninfraredimagefeaturesandpositioncharacteristics