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摘要: 针对工业过程中故障发生源与故障信息在传播过程中的差异性问题, 提出了一种基于不同故障传播路径差异化(Fault propagation path-aware network, FPPAN)的故障诊断方法. 该方法分别从故障源邻域信息关系和故障信息传播两个角度出发, 设计了基于k近邻筛选(k-nearest-neighbor, k-NN) 和基于剪枝的k跳可达路径选择 (Pruning-based k-hop reachable path selection, k-PHop) 的两种故障源图的构建方式, 构建“故障源图”. 从故障在变量间的差异化表现着手, 将基于特征的分类问题转换为基于结构关系的图匹配问题, 利用该结构化信息优化过程特征, 提升模型故障诊断性能. 最后, 通过田纳西−伊斯曼 (Tennessee-Eastman, TE)过程和某海底盾构掘进施工过程进行仿真验证, 实验结果证明了所提方法的有效性.Abstract: In order to address the issue of variability of fault sources and fault information in the propagation process in industrial processes, this paper proposes a fault diagnosis method based on fault propagation path-aware network (FPPAN). The method is based on two perspectives of fault source neighbourhood information relationship and fault information propagation, and designs two ways of constructing fault source graphs based on k-nearest-neighbour (k-NN) filtering and pruning-based k-hop reachable path selection (k-PHop) to construct a “fault source graph”. Based on the differentiation of faults among variables, the feature-based classification problem is viewed as a graph matching problem based on structural relationships, and the structural information is used to optimise the process features and improve the fault diagnosis performance of the model. Finally, the simulation is verified by the Tennessee-Eastman (TE) process and a submarine shield boring construction process, and the experimental results prove the effectiveness of the proposed method.
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Key words:
- Fault diagnosis /
- graph neural network /
- fault source graph /
- fault root cause /
- fault propagation path
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图 9 不同k值和p值下的FPPAN-k-PHop的性能
Fig. 9 Performance of FPPAN-k-PHop with different k values and p values
图 11 盾构机内部结构示意图
Fig. 11 Schematic diagram of the internal structure of shield tunneling machine
表 1 TE过程故障信息
Table 1 Fault information for the TE process
序号 故障描述 类型 1 $A/C $ 进料流量比值变化, B含量不变 阶跃 2 B含量变化, $A/C $进料流量比值不变 阶跃 3 物料D温度发生变化 阶跃 4 反应器冷却水入口温度变化 阶跃 5 冷凝器冷却水入口温度变化 阶跃 6 物料A损失 阶跃 7 物料C压力损失 阶跃 8 物料A、B、C 的组成成分变化 随机 9 D进料温度变化 随机 10 C进料温度变化 随机 11 反应器冷却水入口温度变化 随机 12 冷凝器冷却水入口温度变化 随机 13 反应器动力学常数变化 缓慢漂移 14 反应器冷却水阀门 粘滞 15 冷凝器冷却水阀门 粘滞 
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表 2 不同方法在TE过程上的故障诊断表现
Table 2 Fault diagnosis performance of different methods on TE process
序号 PCA + LDA SVM DCNN GCN GAT PTCN IAGNN-CON IAGNN-AT FPPAN-k-NN FPPAN-k-PHop 1 1.000 1.000 0.997 0.973 0.983 1.000 0.960 0.880 1.000 1.000 2 1.000 1.000 1.000 0.864 1.000 1.000 0.987 0.997 1.000 1.000 3 0.103 0.541 0.439 0.355 0.362 0.329 0.280 0.319 0.331 0.561 4 0.747 1.000 0.997 0.997 0.963 1.000 0.917 0.953 1.000 1.000 5 0.547 0.938 0.970 0.613 0.240 0.963 0.346 0.452 0.975 0.961 6 1.000 1.000 1.000 0.973 1.000 1.000 1.000 1.000 1.000 1.000 7 1.000 1.000 1.000 0.678 0.924 1.000 0.960 0.983 1.000 1.000 8 0.464 0.613 0.674 0.243 0.452 0.681 0.465 0.475 0.731 0.728 9 0.139 0.159 0.073 0.206 0.021 0.050 0.342 0.213 0.199 0.262 10 0.084 0.047 0.792 0.352 0.472 0.498 0.508 0.375 0.827 0.694 11 0.046 0.284 0.967 0.967 0.781 0.977 0.960 0.970 1.000 1.000 12 0.269 0.853 0.714 0.595 0.664 0.867 0.631 0.671 0.883 0.869 13 0.450 0.362 0.621 0.173 0.011 0.794 0.090 0.123 0.711 0.739 14 0.058 0.997 1.000 1.000 1.000 0.967 1.000 1.000 1.000 1.000 15 0.151 0.177 0.212 0.276 0.193 0.301 0.282 0.279 0.312 0.196 平均值 0.471 0.665 0.764 0.618 0.604 0.762 0.649 0.646 0.798 0.801
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表 3 盾构施工故障信息
Table 3 Fault information for the shield tunneling construction
序号 故障描述 1 刀盘结泥饼 2 泥浆管路漏浆 3 刀盘驱动故障 4 推进系统故障
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表 4 不同方法在盾构施工上的故障诊断表现
Table 4 Fault diagnosis performance of different methods for the shield tunneling construction
序号 PCA + LDA SVM DCNN GCN GAT PTCN IAGNN-CON IAGNN-AT FPPAN-k-NN FPPAN-k-PHop 1 0.853 1.000 1.000 0.751 0.976 1.000 0.835 0.923 1.000 1.000 2 0.741 0.802 1.000 0.664 0.936 1.000 0.785 0.889 1.000 1.000 3 0.579 0.631 0.931 0.875 0.756 0.944 0.823 0.845 1.000 1.000 4 0.601 0.629 0.900 0.520 0.892 0.961 0.717 0.803 0.994 0.996 平均值 0.694 0.770 0.958 0.703 0.890 0.976 0.790 0.865 0.999 0.999
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