Diagnosis of Process Nonlinearities and Valve Stiction

I.Introduction
1. Introduction
Part I.Higher-Order Statistics
2. Higher-Order Statistics: Preliminaries
3. Bispectrum and Bicoherence
Part II.Data Quality – Compression and Quantization
4. Impact of Data Compression and Quantization on Data-Driven Process Analyses
Part III.Nonlinearity and Control Performance
5. Measures of Nonlinearity – A Review
6. Linear or Nonlinear? A Bicoherence-Based Measure of Nonlinearity
7. A Nonlinearity Measure Based on Surrogate Data Analysis
8. Nonlinearities in Control Loops
9. Diagnosis of Poor Control Performance
Part IV.Control Valve Stiction~– Definition, Modelling, Detection and Quantification
10. Different Types of Faults in Control Valves
11. Stiction: Definition and Discussions
12. Physics-Based Model of Control Valve Stiction
13. Data-Driven Model of Valve Stiction
14. Describing Function Analysis
15. Automatic Detection and Quantification of Valve Stiction
16. Industrial Applications of the Stiction Quantification Algorithm
17. Confirming Valve Stiction
Part V.Plant-wide Oscillations – Detection and Diagnosis
18. Detection of Plantwide Oscillations
19. Diagnosis of Plant-wide Oscillations

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