基于稀疏故障演化判别分析的故障根源追溯
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摘要
火力发电过程规模庞大,过程变量众多。在故障发生时,部分变量将受故障扰动影响偏离正常运行状态,分析这些故障变量之间的故障传递关系并找到根源故障变量,这对于定位故障位置以及排除故障具有重大意义。因此采用稀疏演化判别分析方法(FDFDA)隔离火电过程中的故障变量,随后对隔离到的故障变量进行格兰杰因果分析,追溯故障根源。
The thermal power processes contain many variables, while only a part of variables will be influenced when the fault occurs. It is meaningful to analyze the fault causalities, which may help track root fault reasons and locate abnormal components. Therefore, for the fault processes, this paper isolates the faulty variables on basis of sparse fault degradation oriented fisher discriminant analysis(FDFDA) and then analyzes the causalities between different variables by Granger Causality analysis for identifying root faulty reasons.
The thermal power processes contain many variables, while only a part of variables will be influenced when the fault occurs. It is meaningful to analyze the fault causalities, which may help track root fault reasons and locate abnormal components. Therefore, for the fault processes, this paper isolates the faulty variables on basis of sparse fault degradation oriented fisher discriminant analysis(FDFDA) and then analyzes the causalities between different variables by Granger Causality analysis for identifying root faulty reasons.
引文
[1]杨勇平,杨志平,徐钢,等.中国火力发电能耗状况及展望[J].中国电机工程学报,2013,33(23):1-11.Yang Y P,Yang Z P,Xu G,et al.The Energy Consumption and Prospect for Thermal Power in China[J].Journal of Chinese Electrical Engineering Science,2013,33(23):1-11.
[2]刘强,柴天佑,秦泗钊,等.基于数据和知识的工业过程监视及故障诊断综述[J].控制与决策,2010,25(06):801-807,813.Liu Q,Chai T Y,Qin S Z,et al.The Review of Data and Knowledge Based Process Monitoring and Fault Diagnosis Methods in Industrial Processes[J].Journal of Control and Decision,2010,25(06):801-807,813.
[3]Li W Q.,Zhao C H.Linearity Evaluation and Variable Subset Partition Based Hierarchical Process Modeling and Monitoring[J].IEEE Transactions on Industrial Electronics,2018,65(3):2683-2692.
[4]Qin Y,Zhao C H.Subspace Decomposition and Critical Phase Selection Based Cumulative Quality Analysis for Multiphase Batch Processes[J].Chemical Engineering Science,2017,166:130-143.
[5]Wang Y,Zhao C H.Probabilistic Fault Diagnosis Method Based on the Combination of Nest-loop Fisher Discriminant Analysis and Analysis of Relative Changes[J].Control Engineering Practice,2017,68:32-45.
[6]Wold S,Esbensen K.Principal Component Analysis[J].Chemometrics and Intelligent Laboratory Systems,1987,2(1):37-52.
[7]Burnham A J,Viveros R.Frameworks for Latent Variable Multivariate Regression[J].Journal of chemometrics,1996,10(1):31-45.
[8]De Jong S.SIMPLS:an Alternative Approach to Partial Least Squares Regression[J].Chemometrics and Intelligent Laboratory Systems,1993,18(3):251-263.
[9]Chiang L H,Kotanchek M E.Fault Diagnosis Based on Fisher Discriminant Analysis and Support Vector Machines[J].Computers&chemical engineering,2004,28(8):1389-1401.
[10]Zhao C H,Gao F R.A Nested-loop Fisher Discriminant Analysis Algorithm[J].Chemometrics and Intelligent Laboratory Systems,2015,146:396-406.
[11]Zhao C H,Gao F R.Critical-to-Fault-Degradation Variable Analysis and Direction Extraction for Online Fault Prognostic[J].IEEETransactions on Control Systems Technology,2017,25(3):842-854.
[12]Choi S W,Lee I B.Multiblock PLS-based Localized Process Diagnosis[J].Journal of Process Control,2005,15(3):295-306.
[13]Alcala C F,Qin S J.Reconstruction-based Contribution for Process Monitoring[J].Automatica,2009,45(7):1593-1600.
[14]Wang Y,Zhao C H.Sparse Analysis Based Fault Deviations Modeling and Its Application to Fault Diagnosis[C].2017 29th Chinese Control And Decision Conference(CCDC),Chongqing,2016.
[15]Granger C W J.Investigating Causal Relations by Econometric Models and Cross-spectral Methods[J].Econometrica:Journal of the Econometric Society,1969,37(3):424-438.
[2]刘强,柴天佑,秦泗钊,等.基于数据和知识的工业过程监视及故障诊断综述[J].控制与决策,2010,25(06):801-807,813.Liu Q,Chai T Y,Qin S Z,et al.The Review of Data and Knowledge Based Process Monitoring and Fault Diagnosis Methods in Industrial Processes[J].Journal of Control and Decision,2010,25(06):801-807,813.
[3]Li W Q.,Zhao C H.Linearity Evaluation and Variable Subset Partition Based Hierarchical Process Modeling and Monitoring[J].IEEE Transactions on Industrial Electronics,2018,65(3):2683-2692.
[4]Qin Y,Zhao C H.Subspace Decomposition and Critical Phase Selection Based Cumulative Quality Analysis for Multiphase Batch Processes[J].Chemical Engineering Science,2017,166:130-143.
[5]Wang Y,Zhao C H.Probabilistic Fault Diagnosis Method Based on the Combination of Nest-loop Fisher Discriminant Analysis and Analysis of Relative Changes[J].Control Engineering Practice,2017,68:32-45.
[6]Wold S,Esbensen K.Principal Component Analysis[J].Chemometrics and Intelligent Laboratory Systems,1987,2(1):37-52.
[7]Burnham A J,Viveros R.Frameworks for Latent Variable Multivariate Regression[J].Journal of chemometrics,1996,10(1):31-45.
[8]De Jong S.SIMPLS:an Alternative Approach to Partial Least Squares Regression[J].Chemometrics and Intelligent Laboratory Systems,1993,18(3):251-263.
[9]Chiang L H,Kotanchek M E.Fault Diagnosis Based on Fisher Discriminant Analysis and Support Vector Machines[J].Computers&chemical engineering,2004,28(8):1389-1401.
[10]Zhao C H,Gao F R.A Nested-loop Fisher Discriminant Analysis Algorithm[J].Chemometrics and Intelligent Laboratory Systems,2015,146:396-406.
[11]Zhao C H,Gao F R.Critical-to-Fault-Degradation Variable Analysis and Direction Extraction for Online Fault Prognostic[J].IEEETransactions on Control Systems Technology,2017,25(3):842-854.
[12]Choi S W,Lee I B.Multiblock PLS-based Localized Process Diagnosis[J].Journal of Process Control,2005,15(3):295-306.
[13]Alcala C F,Qin S J.Reconstruction-based Contribution for Process Monitoring[J].Automatica,2009,45(7):1593-1600.
[14]Wang Y,Zhao C H.Sparse Analysis Based Fault Deviations Modeling and Its Application to Fault Diagnosis[C].2017 29th Chinese Control And Decision Conference(CCDC),Chongqing,2016.
[15]Granger C W J.Investigating Causal Relations by Econometric Models and Cross-spectral Methods[J].Econometrica:Journal of the Econometric Society,1969,37(3):424-438.