Inhaltsangabe1 Introduction.- 1.1 The Intention.- 1.2 The Concept.- 1.3 Modelling.- 1.3.1 Modelling of Systems.- 1.3.2 Modelling of Uncertainties.- 1.3.3 Holistic Modelling.- 1.4 Summary.- 2 Review of Tools and Concepts of Diagnosis.- 2.1 Damage, Faults and their Descriptions.- 2.1.1 General Discussion.- 2.1.2 Parameter Modifications: Preliminary Examples.- 2.1.3 Parameter Modifications: General Analysis.- 2.1.4 Model Structure Modifications.- 2.2 Symptoms.- 2.2.1 Introductory Remarks: Symptoms, Discriminants, Features.- 2.2.2 Symptoms of Linear Systems.- 2.2.3 Symptoms of Non-linear Systems.- 2.2.4 Features and Patterns, Classification.- 2.2.5 Remarks on the Decision Problem.- 2.2.6 Remarks on the Localization Problem.- 2.3 Damage Initiation and Evolution in Operating Systems.- 2.3.1 The Physics of Structural Wear and Damage.- 2.3.2 The Energy Model of System Damage and its Measure.- 2.3.3 Damage and Symptom Evolution.- 2.3.4 Mechanical Properties of Operating Systems in the Holistic Approach.- 2.3.5 Damage Capacity and Symptom Reliability of Operating Systems and their Diagnostic Use.- 2.3.6 Application of the Damage Evolution Theory.- 2.4 Summary.- 3 Fault-Related Processes: Monitoring, Measurements, Processing of Signals.- 3.1 Monitoring.- 3.1.1 The Goal of Condition Monitoring.- 3.1.2 Symptoms, Processes and their Characteristics.- 3.2 Measurements.- 3.2.1 The Goal of Measurements.- 3.2.2 Environmental and Boundary Conditions.- 3.2.3 Sensors: Properties, Calibration, Measuring Errors, Locations.- 3.2.4 Test/Measurement Set-up.- 3.3 Signal Pre-processing.- 3.3.1 Conditioning, Sampling, Pre-analysis.- 3.3.2 Filtering and Segmentation.- 3.4 Signal Processing.- 3.4.1 Increase of the Signal-to-noise Ratio.- 3.4.2 Information Condensation.- 3.4.3 Inverse Filtering.- 3.5 Summary.- 4 Model-Supported Diagnostics Via Parameter Estimation.- 4.1 The General Procedure.- 4.2 Model Adjustment - Preparations.- 4.2.1 Models.- 4.2.2 Tests.- 4.2.3 Residuals.- 4.2.4 Estimators.- 4.3 Model Adjustment - Methods.- 4.3.1 Subsystem Modelling.- 4.3.2 Adjustment Based on Eigenvalues.- 4.3.3 Adjustment with Identified Eigenvalues and Eigenvectors.- 4.3.4 Adjustment Based on Input/Output Measurements.- 4.3.5 State Observers.- 4.3.6 ARMA Models.- 4.3.7 Additional Methods.- 4.4 Algorithms.- 4.4.1 Linear Equation Solvers.- 4.4.2 Nonlinear Equation Solvers.- 4.4.3 Role of Regularization.- 4.5 Practical Hints.- 4.5.1 General.- 4.5.2 Incomplete Measurements.- 4.5.3 The Use of Order-Reduced Models.- 4.6 Use of the Knowledge Base for Diagnosis.- 4.6.1 Parameter Errors: Covariance Matrix and Confidence Regions.- 4.6.2 Dynamic Models.- 4.6.3 Static Models.- 4.6.4 Trend.- 4.7 Summary.- 5 Decision, Assessment, and System Modification Procedures.- 5.1 Fundamentals of Decision.- 5.1.1 Pseudo-deterministic Decision.- 5.1.2 Bayesian Decision Theory.- 5.1.3 Neyman-Pearson Rule.- 5.1.4 Fuzzy Logic and Decision.- 5.2 Symptom-based Decision.- 5.2.1 Deterministic Decision.- 5.2.2 Statistical Decision Based on Histograms.- 5.2.3 Statistical Decision Using Significance Tests.- 5.3 Model-based Decision.- 5.4 Assessment.- 5.4.1 Assessment of State Condition by Simulation.- 5.4.2 Cause Finding.- 5.4.3 Trend Prediction.- 5.4.4 Actions.- 5.5 System Modification Procedures.- 5.5.1 Sensitivity Analysis.- 5.5.2 Spectral Decomposition.- 5.5.3 Minimum Modification by the Application of Optimization.- 5.6 Summary.- 6 Examples and Remarks on Applications.- 6.1 An Academic Example: The FE-Model of a Satellite.- 6.1.1 The System and its Model.- 6.1.2 The Damaged System and the Simulation of the Dynamic Response.- 6.1.3 The Localization of Faults.- 6.1.4 The Adjusted Mathematical Model.- 6.2 Application in Mechanical Engineering.- 6.2.1 The Choice of Symptom Operator Shape.- 6.2.2 Model-Based Diagnostics for Rotor Machinery Including Turbosets.- 6.3 Application in Civil Engineering: Norderelb Bridge.- 6.3.1 The System and its Model.- 6.3.2 Identification of Eigenquantities.- 6.3.3 Comparison of Calcu