Process control system fault diagnosis: a Bayesian approach

360 Pages·2016·5.782 MB·English

by  Gonzalez, Ruben, Huang, Biao, Qi, Fei

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PROCESS CONTROL
SYSTEM FAULT
DIAGNOSIS
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PROCESS CONTROL
SYSTEM FAULT
DIAGNOSIS
A BAYESIAN APPROACH
Ruben Gonzalez
Fei Qi
Biao Huang
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Thiseditionfirstpublished2016
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LibraryofCongressCataloging-in-PublicationData
Names:Gonzalez,Ruben,1985-author.|Qi,Fei,1983-author|Huang,Biao,
1962-author.
Title:Processcontrolsystemfaultdiagnosis:aBayesianapproach/Ruben
Gonzalez,FeiQi,BiaoHuang.
Description:Firstedition.|Chichester,WestSussex,UnitedKingdom:John
Wiley&Sons,2016.|Includesbibliographicalreferencesandindex.
Identifiers:LCCN2016010340|ISBN9781118770610(cloth)|ISBN9781118770597
(epub)
Subjects:LCSH:Chemicalprocesscontrol–Statisticalmethods.|Bayesian
statisticaldecisiontheory.|Faultlocation(Engineering)
Classification:LCCTP155.75.G672016|DDC660/.2815–dc23LCrecordavailableat
https://lccn.loc.gov/2016010340
AcataloguerecordforthisbookisavailablefromtheBritishLibrary.
Setin10/12pt,TimesLTStdbySPiGlobal,Chennai,India.
1 2016
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Contents
Preface xiii
Acknowledgements xvii
ListofFigures xix
ListofTables xxiii
Nomenclature xxv
(cid:2) PartI FUNDAMENTALS (cid:2)
1 Introduction 3
1.1 MotivationalIllustrations 3
1.2 PreviousWork 4
1.2.1 DiagnosisTechniques 4
1.2.2 MonitoringTechniques 7
1.3 BookOutline 12
1.3.1 ProblemOverviewandIllustrativeExample 12
1.3.2 OverviewofProposedWork 12
References 16
2 PrerequisiteFundamentals 19
2.1 Introduction 19
2.2 BayesianInferenceandParameterEstimation 19
2.2.1 TutorialonBayesianInference 24
2.2.2 TutorialonBayesianInferencewithTimeDependency 27
2.2.3 BayesianInferencevs.DirectInference 32
2.2.4 TutorialonBayesianParameterEstimation 33
2.3 TheEMAlgorithm 38
2.4 TechniquesforAmbiguousModes 44
2.4.1 TutorialonΘParametersinthePresenceofAmbiguousModes 46
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vi Contents
2.4.2 TutorialonProbabilitiesUsingΘParameters 47
2.4.3 Dempster–ShaferTheory 48
2.5 KernelDensityEstimation 51
2.5.1 FromHistogramstoKernelDensityEstimates 52
2.5.2 BandwidthSelection 54
2.5.3 KernelDensityEstimationTutorial 55
2.6 Bootstrapping 56
2.6.1 BootstrappingTutorial 57
2.6.2 SmoothedBootstrappingTutorial 57
2.7 NotesandReferences 60
References 61
3 BayesianDiagnosis 62
3.1 Introduction 62
3.2 BayesianApproachforControlLoopDiagnosis 62
3.2.1 ModeM 62
3.2.2 EvidenceE 63
3.2.3 HistoricalDatasetD 64
3.3 LikelihoodEstimation 65
3.4 NotesandReferences 67
References 67
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4 AccountingforAutodependentModesandEvidence 68
4.1 Introduction 68
4.2 TemporallyDependentEvidence 68
4.2.1 EvidenceDependence 68
4.2.2 EstimationofEvidence-transitionProbability 70
4.2.3 IssuesinEstimatingDependenceinEvidence 74
4.3 TemporallyDependentModes 75
4.3.1 ModeDependence 75
4.3.2 EstimatingModeTransitionProbabilities 77
4.4 DependentModesandEvidence 81
4.5 NotesandReferences 82
References 82
5 AccountingforIncompleteDiscreteEvidence 83
5.1 Introduction 83
5.2 TheIncompleteEvidenceProblem 83
5.3 DiagnosiswithIncompleteEvidence 85
5.3.1 SingleMissingPatternProblem 86
5.3.2 MultipleMissingPatternProblem 92
5.3.3 LimitationsoftheSingleandMultipleMissingPatternSolutions 93
5.4 NotesandReferences 94
References 94
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Contents vii
6 AccountingforAmbiguousModes:ABayesianApproach 96
6.1 Introduction 96
6.2 ParametrizationofLikelihoodGivenAmbiguousModes 96
6.2.1 InterpretationofProportionParameters 96
6.2.2 ParametrizingLikelihoods 97
6.2.3 InformedEstimatesofLikelihoods 98
6.3 Fagin–HalpernCombination 99
6.4 Second-orderApproximation 100
6.4.1 ConsistencyofΘParameters 101
6.4.2 ObtainingaSecond-orderApproximation 101
6.4.3 TheSecond-orderBayesianCombinationRule 103
6.5 BriefComparisonofCombinationMethods 104
6.6 ApplyingtheSecond-orderRuleDynamically 105
6.6.1 UnambiguousDynamicSolution 105
6.6.2 TheSecond-orderDynamicSolution 106
6.7 MakingaDiagnosis 107
6.7.1 SimpleDiagnosis 107
6.7.2 RangedDiagnosis 107
6.7.3 ExpectedValueDiagnosis 107
6.8 NotesandReferences 111
References 111
7 AccountingforAmbiguousModes:ADempster–ShaferApproach 112
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7.1 Introduction 112
7.2 Dempster–ShaferTheory 112
7.2.1 BasicBeliefAssignments 112
7.2.2 ProbabilityBoundaries 114
7.2.3 Dempster’sRuleofCombination 114
7.2.4 Short-cutCombinationforUnambiguousPriors 115
7.3 GeneralizingDempster–ShaferTheory 116
7.3.1 Motivation:DifficultieswithBBAs 117
7.3.2 GeneralizingtheBBA 119
7.3.3 GeneralizingDempster’sRule 122
7.3.4 Short-cutCombinationforUnambiguousPriors 123
7.4 NotesandReferences 124
References 125
8 MakingUseofContinuousEvidenceThroughKernelDensityEstimation 126
8.1 Introduction 126
8.2 Performance:Continuousvs.DiscreteMethods 127
8.2.1 AverageFalseNegativeDiagnosisCriterion 127
8.2.2 PerformanceofDiscreteandContinuousMethods 129
8.3 KernelDensityEstimation 132
8.3.1 FromHistogramstoKernelDensityEstimates 132
8.3.2 DefiningaKernelDensityEstimate 134
8.3.3 BandwidthSelectionCriterion 135
8.3.4 BandwidthSelectionTechniques 136
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viii Contents
8.4 DimensionReduction 137
8.4.1 IndependenceAssumptions 138
8.4.2 PrincipalandIndependentComponentAnalysis 139
8.5 MissingValues 139
8.5.1 KernelDensityRegression 140
8.5.2 ApplyingKernelDensityRegressionforaSolution 141
8.6 DynamicEvidence 142
8.7 NotesandReferences 143
References 143
9 AccountingforSparseDataWithinaMode 144
9.1 Introduction 144
9.2 AnalyticalEstimationoftheMonitorOutputDistributionFunction 145
9.2.1 ControlPerformanceMonitor 145
9.2.2 ProcessModelMonitor 146
9.2.3 SensorBiasMonitor 148
9.3 BootstrapApproachtoEstimatingMonitorOutputDistributionFunction 150
9.3.1 ValveStictionIdentification 150
9.3.2 TheBootstrapMethod 153
9.3.3 IllustrativeExample 156
9.3.4 Applications 160
9.4 ExperimentalExample 164
9.4.1 ProcessDescription 164
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9.4.2 DiagnosticSettingsandResults 167
9.5 NotesandReferences 170
References 170
10 AccountingforSparseModesWithintheData 172
10.1 Introduction 172
10.2 ApproachesandAlgorithms 172
10.2.1 ApproachforComponentDiagnosis 173
10.2.2 ApproachforBootstrappingNewModes 176
10.3 Illustration 181
10.3.1 Component-basedDiagnosis 184
10.3.2 BootstrappingforAdditionalModes 188
10.4 Application 194
10.4.1 MonitorSelection 195
10.4.2 ComponentDiagnosis 195
10.5 NotesandReferences 198
References 199
PartII APPLICATIONS
11 IntroductiontoTestbedSystems 203
11.1 SimulatedSystem 203
11.1.1 MonitorDesign 203
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