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This paper aims to conduct a comprehensive and in-depth study of the “AI online sorting system for anode rods in the anodeAnode assembly workshop” for use in the aluminum electrolysisAluminum electrolysis industry. Integrating the latest research findings and industry practices in artificial intelligenceArtificial intelligence, machine vision, and automationAutomation, this paper systematically explains the project background, technical solutions, performance indicators, and industrial applicationsIndustrial applications of the system, and provides a detailed analysis of the AI algorithm architecture and software functions. By integrating high-precision industrial visionIndustrial vision, deep learningDeep learning algorithms, and automated control technologies, this system effectively replaces traditional manual inspection, achieving rapid, accurate, and automated identification and sorting of anodeAnode rods, significantly improving product qualityQuality and production efficiency while reducing safetySafety hazards. In addition, the creation of a comprehensive database encompassing the full lifecycle of anodeAnode rods.

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Deep Learning for Automated Defect Detection and Sorting of Anode Rods in Aluminum Smelters

  • 会议论文

  • 发表日期：

    2026年

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  • Wang Xudong,
  • Li Yingwu,
  • Jiang Cheng

摘要

This paper aims to conduct a comprehensive and in-depth study of the “AI online sorting system for anode rods in the anodeAnode assembly workshop” for use in the aluminum electrolysisAluminum electrolysis industry. Integrating the latest research findings and industry practices in artificial intelligenceArtificial intelligence, machine vision, and automationAutomation, this paper systematically explains the project background, technical solutions, performance indicators, and industrial applicationsIndustrial applications of the system, and provides a detailed analysis of the AI algorithm architecture and software functions. By integrating high-precision industrial visionIndustrial vision, deep learningDeep learning algorithms, and automated control technologies, this system effectively replaces traditional manual inspection, achieving rapid, accurate, and automated identification and sorting of anodeAnode rods, significantly improving product qualityQuality and production efficiency while reducing safetySafety hazards. In addition, the creation of a comprehensive database encompassing the full lifecycle of anodeAnode rods.