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基于图像与电流特征的电熔镁炉欠烧工况半监督分类方法

卢绍文 温乙鑫

卢绍文, 温乙鑫. 基于图像与电流特征的电熔镁炉欠烧工况半监督分类方法. 自动化学报, 2021, 47(x): 1−12 doi: 10.16383/j.aas.c200754
引用本文: 卢绍文, 温乙鑫. 基于图像与电流特征的电熔镁炉欠烧工况半监督分类方法. 自动化学报, 2021, 47(x): 1−12 doi: 10.16383/j.aas.c200754
Lu Shao-Wen, Wen Yi-Xin. Semi-supervised classification of semi-molten working condition of fused magnesium furnace based on image and current features. Acta Automatica Sinica, 2021, 47(x): 1−12 doi: 10.16383/j.aas.c200754
Citation: Lu Shao-Wen, Wen Yi-Xin. Semi-supervised classification of semi-molten working condition of fused magnesium furnace based on image and current features. Acta Automatica Sinica, 2021, 47(x): 1−12 doi: 10.16383/j.aas.c200754

基于图像与电流特征的电熔镁炉欠烧工况半监督分类方法

doi: 10.16383/j.aas.c200754
基金项目: 国家自然科学基金资助(61991404, 61833004)
详细信息
    作者简介:

    卢绍文:东北大学流程工业综合自动化国家重点实验室教授. 于2006年获伦敦大学皇后玛丽学院电子工程学博士学位. 研究领域为工业过程建模与仿真. 目前主要研究多尺度随机建模方法, 模拟软件设计和数据可视化方法. 本文通信作者. E-mail: lusw@mail.neu.edu.cn

    温乙鑫:东北大学流程工业综合自动化国家重点实验室硕士研究生. 于2018年获东北大学自动化专业学士学位. 主要研究方向为半监督学习. E-mail: wenyixin0421@163.com

Semi-supervised Classification of Semi-molten Working Condition of Fused Magnesium Furnace Based on Image and Current Features

Funds: Supported by National Natural Science Foundation of China (61991404, 61833004)
  • 摘要: 本文针对电熔镁炉异常工况识别任务, 在半监督学习框架下提出了一种将电流与图像两类特征融合的解决方案. 本文的贡献主要为: 使用多元图像分析技术代替人眼, 更为准确客观地对镁炉火焰进行特征提取; 利用基于熵正则化的半监督学习框架, 同时使用具有强互补性的生产图像与电流数据进行工况分类, 从而弥补了基于单一特征分类的某些缺点; 采用交叉熵方法优化分类器目标函数, 较传统优化方法显著地提升了训练速度. 通过仿真数据与公开数据集测试并讨论了本文算法的优势; 并通过工业数据验证了本文所提出的方法有效性、应用价值与良好的鲁棒性.
  • 图  1  炉口火焰与感兴趣区域

    Fig.  1  Furnace mouth flame and ROI

    图  2  无标记熔炼电流样本分布

    Fig.  2  Unlabeled smelting current samples' distribution

    图  3  特征数据升维示意图

    Fig.  3  Schematic diagram of upgrading feature data’s dimension

    图  4  特征融合前后分类实验结果对比

    Fig.  4  Comparison of classification experiment results before and after feature fusion

    图  5  鲁棒性测试实验结果图

    Fig.  5  Robustness test results

    图  6  Friedman检验图

    Fig.  6  Friedman test pictures

    图  7  从不同角度拍摄的镁炉图像

    Fig.  7  Magnesium furnace images taken from different angles

    表  1  分类准确率结果比较(97%与95%无标记占比)

    Table  1  Comparison of classification accuracy (97% and 95% unlabeled)

    数据 无标记占比: 97% 无标记占比: 95%
    CEM-ER Sf-T S$^3$VM Co-T CPLE LaN CEM-ER Sf-T S$^3$VM Co-T CPLE LaN
    1 $56.8^{\pm4.2}$ $53.8^{\pm6.8}$ $52.2^{\pm5.7}$ $49.7^{\pm6.3}$ $56.0^{\pm3.0}$ $52.3^{\pm4.7}$ $59.9^{\pm5.7}$ $48.0^{\pm7.8}$ $50.5^{\pm5.8}$ $50.8^{\pm8.0}$ $53.7^{\pm3.6}$ $53.9^{\pm5.8}$
    2 $63.2^{\pm15}$ $65.5^{\pm20}$ $50.2^{\pm16}$ $64.8^{\pm21}$ $75.7^{\pm3.6}$ $57.5^{\pm16}$ $64.0^{\pm8.1}$ $50.6^{\pm22}$ $49.9^{\pm13}$ $60.9^{\pm13}$ $76.1^{\pm2.3}$ $60.5^{\pm11}$
    3 $51.9^{\pm9.0}$ $51.7^{\pm12}$ $52.7^{\pm13}$ $41.2^{\pm13}$ $28.5^{\pm3.3}$ $53.0^{\pm10.1}$ $62.3^{\pm7.7}$ $60.1^{\pm17}$ $53.6^{\pm11}$ $56.2^{\pm9.8}$ $30.9^{\pm3.5}$ $58.8^{\pm8.8}$
    4 $72.9^{\pm6.4}$ $61.3^{\pm16}$ $69.7^{\pm6.7}$ $59.1^{\pm12}$ $60.9^{\pm3.8}$ $45.0^{\pm7.5}$ $73.2^{\pm11}$ $57.6^{\pm13}$ $75.7^{\pm9.2}$ $65.7^{\pm11}$ $35.8^{\pm11}$ $47.5^{\pm10}$
    5 $57.9^{\pm5.9}$ $51.8^{\pm8.3}$ $56.7^{\pm8.3}$ $57.3^{\pm8.0}$ $45.7^{\pm8.8}$ $52.7^{\pm6.6}$ $58.9^{\pm4.8}$ $52.5^{\pm11}$ $57.8^{\pm}9.0$ $56.4^{\pm10}$ $47.6^{\pm4.2}$ $52.5^{\pm6.5}$
    6 $67.2^{\pm9.7}$ $67.8^{\pm12}$ $70.1^{\pm8.7}$ $69.8^{\pm16}$ $42.7^{\pm5.3}$ $54.7^{\pm9.8}$ $62.1^{\pm5.0}$ $60.9^{\pm8.9}$ $71.4^{\pm5.1}$ $75.7^{\pm6.3}$ $46.4^{\pm4.4}$ $57.7^{\pm7.5}$
    7 $53.5^{\pm5.8}$ $51.0^{\pm7.0}$ $56.9^{\pm3.0}$ $52.4^{\pm4.6}$ $61.1^{\pm1.3}$ $47.8^{\pm6.0}$ $50.0^{\pm4.2}$ $51.7^{\pm4.6}$ $57.6^{\pm6.0}$ $49.7^{\pm2.2}$ $62.2^{\pm1.2}$ $52.0^{\pm5.2}$
    8 $93.1^{\pm1.5}$ $96.2^{\pm1.6}$ $96.6^{\pm1.4}$ $94.1^{\pm1.7}$ $68.8^{\pm 5.3}$ $89.5^{\pm1.8}$ $94.0^{\pm1.0}$ $96.5^{\pm1.3}$ $96.3^{\pm1.2}$ $93.7^{\pm1.5}$ $70.7^{\pm4.8}$ $89.7^{\pm1.5}$
    平均 64.56 62.38 63.14 61.01 54.93 56.56 65.54 59.73 64.08 63.61 52.91 59.07
    下载: 导出CSV

    表  3  分类准确率结果比较(80%与60%无标记占比)

    Table  3  Comparison of classification accuracy (80% and 60% unlabeled)

    数据 无标记占比: 80% 无标记占比: 60%
    CEM-ER Sf-T S3VM Co-T CPLE LaN CEM-ER Sf-T S3VM Co-T CPLE LaN
    1 $65.1^{\pm5.5}$ $47.8^{\pm8.8}$ $50.9^{\pm5.5}$ $45.5^{\pm6.3}$ $59.0^{\pm2.8}$ $56.7^{\pm6.1}$ $63.7^{\pm3.6}$ $55.7^{\pm5.9}$ $49.8^{\pm6.6}$ $52.9^{\pm4.3}$ $56.6^{\pm3.3}$ $58.7^{\pm4.6}$
    2 $64.9^{\pm3.9}$ $50.2^{\pm13}$ $64.9^{\pm8.0}$ $71.7^{\pm6.8}$ $72.2^{\pm1.9}$ $68.0^{\pm7.0}$ $68.8^{\pm4.3}$ $53.2^{\pm5.4}$ $65.9^{\pm3.5}$ $72.1^{\pm5.4}$ $67.6^{\pm2.6}$ $71.6^{\pm4.8}$
    3 $66.4^{\pm8.0}$ $50.8^{\pm19}$ $59.8^{\pm9.7}$ $58.4^{\pm10}$ $34.7^{\pm2.7}$ $67.4^{\pm8.5}$ $64.4^{\pm7.2}$ $44.1^{\pm23}$ $62.6^{\pm11}$ $58.6^{\pm7.5}$ $39.2^{\pm19}$ $69.6^{\pm8.9}$
    4 $80.8^{\pm3.0}$ $68.5^{\pm3.9}$ $83.8^{\pm4.4}$ $74.9^{\pm8.1}$ $39.5^{\pm13}$ $67.9^{\pm4.7}$ $81.6^{\pm2.8}$ $73.7^{\pm3.0}$ $85.9^{\pm3.0}$ $83.9^{\pm4.9}$ $67.5^{\pm20}$ $77.4^{\pm3.1}$
    5 $60.0^{\pm7.4}$ $61.6^{\pm8.0}$ $70.5^{\pm7.2}$ $66.8^{\pm5.7}$ $54.6^{\pm6.8}$ $57.1^{\pm7.2}$ $66.5^{\pm5.8}$ $61.9^{\pm7.6}$ $73.0^{\pm6.7}$ $72.4^{\pm6.8}$ $58.1^{\pm7.7}$ $58.7^{\pm6.4}$
    6 $76.3^{\pm2.7}$ $71.0^{\pm3.6}$ $78.2^{\pm5.4}$ $80.0^{\pm2.9}$ $52.4^{\pm8.8}$ $71.6^{\pm6.1}$ $81.0^{\pm2.9}$ $76.1^{\pm4.2}$ $82.8^{\pm4.8}$ $83.0^{\pm3.9}$ $64.6^{\pm6.8}$ $80.3^{\pm4.8}$
    7 $59.7^{\pm2.2}$ $34.7^{\pm3.5}$ $60.4^{\pm3.1}$ $51.4^{\pm4.2}$ $65.3^{\pm2.7}$ $55.6^{\pm3.2}$ $61.1^{\pm2.1}$ $36.8^{\pm3.9}$ $61.5^{\pm2.8}$ $58.3^{\pm2.5}$ $64.2^{\pm3.0}$ $56.9^{\pm2.9}$
    8 $96.0^{\pm1.0}$ $96.7^{\pm1.2}$ $96.8^{\pm1.3}$ $96.2^{\pm1.4}$ $80.4^{\pm9.3}$ $96.2^{\pm1.9}$ $95.9^{\pm1.0}$ $96.7^{\pm1.0}$ $96.9^{\pm0.8}$ $96.8^{\pm1.0}$ $90.6^{\pm3.1}$ $97.1^{\pm1.0}$
    平均 71.15 60.15 70.64 68.11 57.26 67.57 72.86 62.28 72.29 72.24 63.56 71.27
    下载: 导出CSV

    表  2  分类准确率结果比较(92%与90%无标记占比)

    Table  2  Comparison of classification accuracy (92% and 90% unlabeled)

    数据 无标记占比: 92% 无标记占比: 90%
    CEM-ER Sf-T S3VM Co-T CPLE LaN CEM-ER Sf-T S3VM Co-T CPLE LaN
    1 $59.1^{\pm5.5}$ $51.3^{\pm8.9}$ $48.2^{\pm7.1}$ $49.0^{\pm6.5}$ $56.7^{\pm2.8}$ $53.4^{\pm6.6}$ $61.1^{\pm5.6}$ $48.4^{\pm9.0}$ $47.4^{\pm7.1}$ $47.3^{\pm5.7}$ $58.4^{\pm4.6}$ $53.8^{\pm5.8}$
    2 $65.6^{\pm7.7}$ $50.1^{\pm21}$ $58.1^{\pm15}$ $72.6^{\pm11}$ $73.7^{\pm1.6}$ $63.1^{\pm9.5}$ $64.7^{\pm5.5}$ $49.4^{\pm15}$ $58.2^{\pm11}$ $72.2^{\pm4.2}$ $77.9^{\pm2.3}$ $65.8^{\pm6.5}$
    3 $60.3^{\pm8.4}$ $53.8^{\pm23}$ $61.7^{\pm11}$ $51.7^{\pm11}$ $28.2^{\pm3.0}$ $52.4^{\pm8.8}$ $62.0^{\pm10}$ $44.4^{\pm13}$ $56.3^{\pm6.7}$ $56.9^{\pm10.4}$ $27.5^{\pm3.5}$ $57.6^{\pm7.8}$
    4 $73.3^{\pm11}$ $61.8^{\pm13}$ $82.7^{\pm9.5}$ $68.4^{\pm10}$ $38.5^{\pm11}$ $57.8^{\pm11}$ $78.4^{\pm10}$ $57.5^{\pm19}$ $80.7^{\pm6.9}$ $72.2^{\pm4.4}$ $37.6^{\pm6.6}$ $64.2^{\pm9.5}$
    5 $57.1^{\pm6.5}$ $56.7^{\pm8.6}$ $65.7^{\pm8.0}$ $56.7^{\pm8.4}$ $47.3^{\pm9.7}$ $51.1^{\pm8.5}$ $59.5^{\pm6.8}$ $54.3^{\pm7.0}$ $66.7^{\pm9.9}$ $58.7^{\pm9.2}$ $48.4^{\pm4.8}$ $55.6^{\pm8.7}$
    6 $70.4^{\pm5.0}$ $66.9^{\pm8.5}$ $77.4^{\pm3.5}$ $79.8^{\pm5.2}$ $44.7^{\pm7.8}$ $58.5^{\pm6.5}$ $71.0^{\pm4.2}$ $71.1^{\pm4.7}$ $78.6^{\pm4.6}$ $80.5^{\pm6.2}$ $50.2^{\pm8.5}$ $65.4^{\pm5.5}$
    7 $54.2^{\pm4.3}$ $49.3^{\pm4.5}$ $51.7^{\pm6.0}$ $51.4^{\pm2.5}$ $65.6^{\pm2.1}$ $54.2^{\pm5.8}$ $58.2^{\pm3.3}$ $49.9^{\pm4.5}$ $59.0^{\pm3.5}$ $57.6^{\pm4.7}$ $61.4^{\pm3.3}$ $54.9^{\pm4.7}$
    8 $94.1^{\pm1.3}$ $96.4^{\pm1.5}$ $96.2^{\pm2.0}$ $94.9^{\pm1.9}$ $70.2^{\pm4.6}$ $91.9^{\pm1.9}$ $95.7^{\pm1.3}$ $97.2^{\pm1.4}$ $96.8^{\pm1.1}$ $96.0^{\pm1.5}$ $69.1^{\pm3.0}$ $95.7^{\pm2.2}$
    平均 66.76 60.77 67.74 65.56 53.11 60.30 68.82 59.00 67.96 67.68 53.79 64.12
    下载: 导出CSV

    表  4  分类器训练速度比较(UCI数据集)

    Table  4  Comparison of classifiers’ training speed (UCI dataset)

    数据集 无标记97% 无标记95% 无标记92% 无标记90% 无标记80% 无标记60%
    ER CEM-ER ER CEM-ER ER CEM-ER ER CEM-ER ER CEM-ER ER CEM-ER
    Bupa 6.94 1.77 6.95 1.77 6.73 1.71 6.94 1.73 7.17 1.75 7.12 1.79
    Blood 20.06 2.34 20.31 2.36 20.22 2.41 20.16 2.45 20.14 2.36 19.44 2.47
    Haberman 8.31 2.55 7.58 2.25 7.28 1.92 7.66 2.27 6.31 2.27 6.97 1.91
    Ionosphere 9.16 1.92 8.98 1.8 7.59 2.22 8.98 2.55 8.63 1.8 7.95 1.8
    Sonar 6.19 2.25 5.05 1.83 5.16 1.8 5.67 1.92 5.23 1.86 5.55 1.7
    Statlog(Heart) 6.19 2.16 6.05 1.89 5.81 2.05 5.97 1.86 6.31 1.77 5.64 1.81
    Tic-tac-toe 31 2.97 28.75 2.88 20.03 2.89 30.14 3.11 32.36 3.08 32.58 3.2
    WBC 28.66 5.16 21.76 3.02 21.58 2.78 19.69 2.56 20.91 2.56 16.45 2.64
    平均值 14.56 2.64 13.18 2.22 11.8 2.22 13.15 2.31 13.38 2.18 12.71 2.17
    下载: 导出CSV

    表  5  电熔镁炉生产数据实验结果

    Table  5  Experimental results of fused magnesium furnace production data

    无标记占比 $\phi_v^{SSL}$准确率 $\phi_{vc}^{SSL}$准确率 准确率提升
    97% 66.72% 86.77% 30.05%
    95% 67.79% 91.84% 35.49%
    92% 70.72% 93.01% 31.51%
    90% 71.67% 93.98% 31.14%
    80% 72.86% 94.30% 29.43%
    60% 74.00% 94.68% 27.93%
    下载: 导出CSV

    表  6  过渡态样本准确率测试

    Table  6  Accuracy of the test on transition state samples

    无标记占比 CEM-ER Sf-T ${\rm{S}}^3$VM Co-T CPLE LaN
    97% 52.22% 48.89% 48.89% 46.67% 50.00% 49.53%
    95% 50.00% 49.17% 47.78% 48.61% 50.00% 49.07%
    92% 48.33% 47.50% 47.78% 46.94% 50.00% 50.00%
    90% 49.72% 48.61% 50.83% 49.17% 50.00% 54.17%
    80% 50.83% 45.00% 48.33% 47.50% 50.00% 50.27%
    60% 52.22% 50.56% 50.83% 46.39% 50.00% 50.92%
    下载: 导出CSV

    表  7  分类器鲁棒性测试结果

    Table  7  Classifier robustness test results

    无标记占比 原准确率 新测试集准确率
    97% 86.77% 84.06%
    95% 91.84% 86.63%
    92% 93.01% 88.32%
    90% 93.98% 89.75%
    80% 94.30% 91.02%
    60% 94.68% 91.14%
    下载: 导出CSV

    表  8  分类器训练速度测试(生产数据)

    Table  8  Comparison of classifiers’ training speed (production data)

    无标记占比 ER CEM-ER 速度提升
    97% 94.57 4.12 95.64%
    95% 86.63 4.06 95.31%
    92% 83.92 4.15 95.05%
    90% 73.48 4.18 94.31%
    80% 59.47 4.24 92.87%
    60% 15.21 4.39 71.14%
    下载: 导出CSV

    表  9  优化算法准确率对比测试结果

    Table  9  Comparison of accuracy in different optimization algorithms

    无标记占比 ER CEM-ER
    97% 88.33% 92.04%
    95% 89.62% 90.80%
    92% 91.00% 93.11%
    90% 92.16% 93.16%
    80% 93.76% 93.58%
    60% 94.50% 94.15%
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-09-14
  • 录用日期:  2020-12-23
  • 网络出版日期:  2021-01-13

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