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生丝黑板智能检测方法及应用研究

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本文采用深度学习技术,建立神经网络和数字图像处理方法相结合的生丝质量评分系统,统一完成生丝黑板法对匀度、清洁度、洁净度的测量和评分过程.作为一种新的生丝黑板AI辅助判定系统,做到了黑板原始图像可溯源、检验数据可复现,生丝疵点识别更准确,可以实现检验过程智能化、信息化和可视化等.解决了 目前生丝黑板完全靠人眼看、靠经验评等问题,最大限度减少生丝黑板检验中人为因素影响,提高检验效率,保证结果公正.
Research on intelligent detection method and application of raw silk blackboard
This article adopts deep learning technology to establish a raw silk quality evaluation system that combines neural net-works and digital image processing methods,and uniformly completes the measurement and evaluation process of evenness,clean-liness,and cleanliness using the blackboard raw silk method.As a new type of raw silk blackboard AI assisted judgment system,it achieves traceability of the original image of the blackboard,reproducibility of inspection data,more accurate identification of raw silk defects,and can achieve intelligent,information-based,and visual inspection processes.Solved the problem of relying solely on human observation and experience evaluation in the current raw silk blackboard inspection,minimizing the influence of human factors in raw silk blackboard inspection,improving inspection efficiency,and ensuring fair results.

raw silk blackboardintelligenceautomationimage recognitionAI assisted

徐贵勇、赵仲秋、王琛、李军、柴捷、吴霜

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中国纤维质量监测中心,北京 100010

合肥工业大学智能制造技术研究院,安徽合肥 230041

安徽省纤维检验局,安徽合肥 230041

生丝黑板 智能化 自动化 图像识别 AI辅助

2024

中国纤检
中国纤维检验局

中国纤检

影响因子:0.11
ISSN:1671-4466
年,卷(期):2024.(1)