化工学报 ›› 2023, Vol. 74 ›› Issue (6): 2522-2537.DOI: 10.11949/0438-1157.20230066
收稿日期:
2023-01-31
修回日期:
2023-05-01
出版日期:
2023-06-05
发布日期:
2023-07-27
通讯作者:
赵忠盖
作者简介:
邵远哲(1997—),男,硕士研究生,1983063392@qq.com
基金资助:
Yuanzhe SHAO(), Zhonggai ZHAO(), Fei LIU
Received:
2023-01-31
Revised:
2023-05-01
Online:
2023-06-05
Published:
2023-07-27
Contact:
Zhonggai ZHAO
摘要:
现有质量相关监控方法基于数据平稳的假设,而实际生产中存在大量的非平稳过程。针对上述问题,提出了一种基于共同趋势模型的非平稳过程质量相关故障检测方法。该方法首先识别出系统中的非平稳过程变量和质量变量,再利用Gonzalo-Granger分解求解共同趋势模型,从而分离非平稳数据中的平稳部分和非平稳部分,然后,整合平稳数据,以及非平稳数据的平稳子空间整合,应用慢特征分析(slow feature analysis, SFA)和典型相关分析(canonical correlation analysis, CCA)建立质量相关的监控模型,实现对非平稳质量变量的有效监控。最后通过对比实验,证明所提出方法可以有效发现非平稳过程质量相关故障。
中图分类号:
邵远哲, 赵忠盖, 刘飞. 基于共同趋势模型的非平稳过程质量相关故障检测方法[J]. 化工学报, 2023, 74(6): 2522-2537.
Yuanzhe SHAO, Zhonggai ZHAO, Fei LIU. Quality-related non-stationary process fault detection method by common trends model[J]. CIESC Journal, 2023, 74(6): 2522-2537.
阶段 | 性能 衡量指标 | CCA | 残差序列方法 | QRCTSFA | ||
---|---|---|---|---|---|---|
无故障阶段 | FAR/% | 49.25 | 28.40 | 1.15 | 0.65 | 1.30 |
故障一(质量相关) | MDR/% | 39.10 | 0 | 12.50 | 0.20 | 94.80 |
故障二(质量相关) | MDR/% | 71.00 | 51.00 | 58.30 | 65.40 | 55.60 |
故障三(质量无关) | FAR/% | 59.90 | 81.00 | 1.80 | 0 | 1.40 |
表1 数值仿真三种方法质量相关监控性能
Table 1 Quality-related monitoring performance of three methods in numerical simulation
阶段 | 性能 衡量指标 | CCA | 残差序列方法 | QRCTSFA | ||
---|---|---|---|---|---|---|
无故障阶段 | FAR/% | 49.25 | 28.40 | 1.15 | 0.65 | 1.30 |
故障一(质量相关) | MDR/% | 39.10 | 0 | 12.50 | 0.20 | 94.80 |
故障二(质量相关) | MDR/% | 71.00 | 51.00 | 58.30 | 65.40 | 55.60 |
故障三(质量无关) | FAR/% | 59.90 | 81.00 | 1.80 | 0 | 1.40 |
阶段 | 性能衡量指标 | CCA | QRCTSFA | |
---|---|---|---|---|
正常集T2 | FAR/% | 100.00 | 0.03 | 0.81 |
案例一(故障集2.1) | FAR/% | 100.00 | 0.21 | 1.20 |
表2 三相流实验CCA、QRCTSFA质量相关指标对T2和案例一误报率
Table 2 False alarm rates of CCA and QRCTSFA for T2 and Case 1 in three-phase flow process
阶段 | 性能衡量指标 | CCA | QRCTSFA | |
---|---|---|---|---|
正常集T2 | FAR/% | 100.00 | 0.03 | 0.81 |
案例一(故障集2.1) | FAR/% | 100.00 | 0.21 | 1.20 |
1 | 赵忠盖, 刘飞. 因子分析及其在过程监控中的应用[J]. 化工学报, 2007, 58(4): 970-974 |
Zhao Z G, Liu F. Factor analysis and its application to process monitoring[J]. Journal of Chemical Industry and Engineering(China), 2007, 58(4): 970-974. | |
2 | 李庆华, 潘丰, 赵忠盖. 一种基于残差再提取的概率PLS监控方法[J]. 控制工程, 2019, 26(4): 631-637. |
Li Q H, Pan F, Zhao Z G. Probabilistic PLS based on re-extraction of residuals and its application in[J]. Control Engineering of China, 2019, 26(4): 631-637. | |
3 | 沙万里, 陈军豪, 赵春晖. 基于负荷轴工况划分的发电厂关键设备非平稳状态监测[J]. 浙江电力, 2019, 38(12): 31-38. |
Sha W L, Chen J H, Zhao C H. Nonstationary operation condition monitoring for key machines of power plant based on load axis operating condition division[J]. Zhejiang Electric Power, 2019, 38(12): 31-38. | |
4 | 潘昱昱, 陈前. 协整理论在系统状态监测与故障诊断的应用研究[J]. 计算机测量与控制, 2006, 14(3): 281-284. |
Pan Y Y, Chen Q. Monitoring and fault diagnosis of system using method of cointegration test[J]. Computer Measurement and Control, 2006, 14(3): 281-284. | |
5 | Li G, Qin S J, Yuan T. Nonstationarity and cointegration tests for fault detection of dynamic processes[J]. IFAC Proceedings Volumes, 2014, 47(3): 10616-10621. |
6 | Engle R F, Yoo B S. Forecasting and testing in cointegrated systems[J]. Journal of Econometrics, 1987, 35(1): 143-159. |
7 | Engle R F, Granger C W J. Co-integration and error correction: representation, estimation, and testing[J]. Econometrica, 1987, 55(2): 251. |
8 | Ali R, Bakhsh K, Yasin M A. Impact of urbanization on CO2 emissions in emerging economy: evidence from Pakistan[J]. Sustainable Cities and Society, 2019, 48: 101553. |
9 | Zhang S M, Zhao C H. Slow-feature-analysis-based batch process monitoring with comprehensive interpretation of operation condition deviation and dynamic anomaly[J]. IEEE Transactions on Industrial Electronics, 2019, 66(5): 3773-3783. |
10 | Chen Q, Kruger U, Leung A Y T. Cointegration testing method for monitoring nonstationary processes[J]. Industrial and Engineering Chemistry Research, 2009, 48(7): 3533-3543. |
11 | Zhao C H, Huang B. A full-condition monitoring method for nonstationary dynamic chemical processes with cointegration and slow feature analysis[J]. AIChE Journal, 2018, 64(5): 1662-1681. |
12 | 孔祥玉, 罗家宇, 张琪, 等. 基于正交信号修正与高效偏最小二乘的质量相关故障检测方法[J]. 控制与决策, 2020, 35(5): 1167-1174. |
Kong X Y, Luo J Y, Zhang Q, et al. Quality-related fault detection method based on orthogonal signal correction and high efficiency PLS[J]. Control and Decision, 2020, 35(5): 1167-1174. | |
13 | 金雨婷, 侍洪波, 吕晓龙, 等. 基于KVAE-OCCA的质量相关故障检测方法及应用[J]. 控制工程, 2022, 29(2): 348-355. |
Jin Y T, Shi H B, Lyu X L, et al. Quality-related fault detection method and application based on KVAE-OCCA[J]. Control Engineering of China, 2022, 29(2): 348-355. | |
14 | Li W Q, Zhao C H, Huang B. Distributed dynamic modeling and monitoring for large-scale industrial processes under closed-loop control[EB/OL]. 2018, . |
15 | Chen Z W, Zhang K, Ding S X, et al. Improved canonical correlation analysis-based fault detection methods for industrial processes[J]. Journal of Process Control, 2016, 41: 26-34. |
16 | Wu D H, Zhou D H, Chen M Y, et al. Output-relevant common trend analysis for KPI-related nonstationary process monitoring with applications to thermal power plants[J]. IEEE Transactions on Industrial Informatics, 2021, 17(10): 6664-6675. |
17 | 王金萍, 赵忠盖, 刘飞. 一种融合无时滞测量值和含时滞测量值的状态估计方法[J]. 化工学报, 2016, 67(3): 940-946. |
Wang J P, Zhao Z G, Liu F. State estimation approach by incorporating measurements with delay-free and time delay[J]. CIESC Journal, 2016, 67(3): 940-946. | |
18 | Stock J H, Watson M W. Testing for common trends[J]. Journal of the American Statistical Association, 1988, 83(404): 1097-1107. |
19 | Wiskott L, Sejnowski T J. Slow feature analysis: unsupervised learning of invariances[J]. Neural Computation, 2002, 14(4): 715-770. |
20 | Wu C, Du B, Zhang L P. Slow feature analysis for change detection in multispectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(5): 2858-2874. |
21 | Zhang Z, Tao D C. Slow feature analysis for human action recognition[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(3): 436-450. |
22 | Blaschke T, Zito T, Wiskott L. Independent slow feature analysis and nonlinear blind source separation[J]. Neural Computation, 2007, 19(4): 994-1021. |
23 | Shang C, Yang F, Gao X Q, et al. Concurrent monitoring of operating condition deviations and process dynamics anomalies with slow feature analysis[J]. AIChE Journal, 2015, 61(11): 3666-3682. |
24 | Zheng J L, Zhao C H. Online monitoring of performance variations and process dynamic anomalies with performance-relevant full decomposition of slow feature analysis[J]. Journal of Process Control, 2019, 80: 89-102. |
25 | 王印松, 刘勇, 孙天舒. 基于协整系数矩阵的电动调节阀劣化分析[J]. 控制工程, 2021, 28(12): 2293-2298. |
Wang Y S, Liu Y, Sun T S. Degradation analysis of electric control valve based on cointegration coefficient matrix[J]. Control Engineering of China, 2021, 28(12): 2293-2298. | |
26 | Akaike H. A new look at the statistical model identification[J]. IEEE Transactions on Automatic Control, 1974, 19(6): 716-723. |
27 | Johansen S, Juselius K. Maximum likelihood estimation and inference on cointegration—with applications to the demand for money[J]. Oxford Bulletin of Economics and Statistics, 1990, 52(2): 169-210. |
28 | Gonzalo J. The making of “estimation of common long-memory components in cointegrated systems”[J]. Journal of Financial Econometrics, 2010, 8(2): 174-176. |
29 | Escribano A, Peña D. Cointegration and common factors[J]. Journal of Time Series Analysis, 1994, 15(6): 577-586. |
30 | Hotelling H. Relations between two sets of variates[J]. Biometrika, 1936, 28(3/4): 321-377. |
31 | Dickey D A, Fuller W A. Likelihood ratio statistics for autoregressive time series with a unit root[J]. Econometrica, 1981, 49(4): 1057. |
32 | Li W Q, Zhao C H, Huang B. Distributed dynamic modeling and monitoring for large-scale industrial processes under closed-loop control[J]. Industrial and Engineering Chemistry Research, 2018, 57(46): 15759-15772. |
33 | 林原灵, 陈前. 基于共同趋势模型的非平稳过程在线监控[J]. 化工学报, 2017, 68(1): 178-187. |
Lin Y L, Chen Q. Online non-stationary process monitoring by common trends model[J]. CIESC Journal, 2017, 68(1): 178-187. | |
34 | Simoglou A, Martin E B, Morris A J. Statistical performance monitoring of dynamic multivariate processes using state space modelling[J]. Computers and Chemical Engineering, 2002, 26(6): 909-920. |
35 | Ruiz-Cárcel C, Cao Y, Mba D, et al. Statistical process monitoring of a multiphase flow facility[J]. Control Engineering Practice, 2015, 42: 74-88. |
36 | 孙鹤. 数据驱动的复杂非平稳工业过程建模与监测[D]. 杭州: 浙江大学, 2018. |
Sun H. Data-driven modeling and monitoring of complex non-stationary industrial processes[D]. Hangzhou: Zhejiang University, 2018. |
[1] | 陈哲文, 魏俊杰, 张玉明. 超临界水煤气化耦合SOFC发电系统集成及其能量转化机制[J]. 化工学报, 2023, 74(9): 3888-3902. |
[2] | 刘远超, 关斌, 钟建斌, 徐一帆, 蒋旭浩, 李耑. 单层XSe2(X=Zr/Hf)的热电输运特性研究[J]. 化工学报, 2023, 74(9): 3968-3978. |
[3] | 张逸豪, 王振雷. 基于最大信息系数的分组支持向量数据描述故障检测[J]. 化工学报, 2023, 74(9): 3865-3878. |
[4] | 郑玉圆, 葛志伟, 韩翔宇, 王亮, 陈海生. 中高温钙基材料热化学储热的研究进展与展望[J]. 化工学报, 2023, 74(8): 3171-3192. |
[5] | 李贵贤, 曹阿波, 孟文亮, 王东亮, 杨勇, 周怀荣. 耦合固体氧化物电解槽的CO2制甲醇过程设计与评价研究[J]. 化工学报, 2023, 74(7): 2999-3009. |
[6] | 文兆伦, 李沛睿, 张忠林, 杜晓, 侯起旺, 刘叶刚, 郝晓刚, 官国清. 基于自热再生的隔壁塔深冷空分工艺设计及优化[J]. 化工学报, 2023, 74(7): 2988-2998. |
[7] | 刘尚豪, 贾胜坤, 罗祎青, 袁希钢. 基于梯度提升决策树的三组元精馏流程结构最优化[J]. 化工学报, 2023, 74(5): 2075-2087. |
[8] | 李正涛, 袁志杰, 贺高红, 姜晓滨. 疏水界面上的NaCl液滴蒸发过程内环流调控机制研究[J]. 化工学报, 2023, 74(5): 1904-1913. |
[9] | 贠程, 王倩琳, 陈锋, 张鑫, 窦站, 颜廷俊. 基于社团结构的化工过程风险演化路径深度挖掘[J]. 化工学报, 2023, 74(4): 1639-1650. |
[10] | 宋冰, 郑城风, 侍洪波, 陶阳, 谭帅. 基于VAE-OCCA的质量相关故障检测方法研究[J]. 化工学报, 2023, 74(4): 1630-1638. |
[11] | 王子宗, 索寒生, 赵学良. 数字孪生智能乙烯工厂研究与构建[J]. 化工学报, 2023, 74(3): 1175-1186. |
[12] | 雍加望, 赵倩倩, 冯能莲. 基于非线性动态模型的质子交换膜燃料电池故障诊断[J]. 化工学报, 2022, 73(9): 3983-3993. |
[13] | 袁妮妮, 郭拓, 白红存, 何育荣, 袁永宁, 马晶晶, 郭庆杰. 化学链燃烧过程Fe2O3/Al2O3载氧体表面CH4反应:ReaxFF-MD模拟[J]. 化工学报, 2022, 73(9): 4054-4061. |
[14] | 杨明辉, 刘晓月, 邓晓刚, 廖明燕, 侯春望. 基于加权概率CVDA的动态化工系统微小故障检测[J]. 化工学报, 2022, 73(9): 3963-3972. |
[15] | 王雅琳, 潘雨晴, 刘晨亮. 基于GSA-LSTM动态结构特征提取的间歇过程监测方法[J]. 化工学报, 2022, 73(9): 3994-4002. |
阅读次数 | ||||||||||||||||||||||||||||||||||||||||||||||||||
全文 238
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||
摘要 189
|
|
|||||||||||||||||||||||||||||||||||||||||||||||||