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Fault Detection and Diagnosis for Gas Turbine Based on Information Entropy Models

Abstract第4页
摘要第5-6页
Table of contents第6-8页
Chapter 1 Introduction第8-22页
    1.1 Background and Significance第8-10页
    1.2 Literature review第10-19页
        1.2.1 Detectable scenarios of Gas turbine faults第10-13页
        1.2.2 Physical model-based method第13-15页
        1.2.3 Data-driven models for fault diagnosis第15-19页
    1.3 Structure of thesis第19-21页
    1.4 Brief Summary of the Chapter第21-22页
Chapter 2 MIC in gas turbines abnormality awareness第22-40页
    2.1 Introduction第22-23页
    2.2 Principles and formulation第23-30页
    2.3 Experimental results第30-39页
        2.3.1 Data description第30-31页
        2.3.2 Simulated graphic illustrations第31-37页
        2.3.3 Description of abnormality detection algorithm第37-39页
    2.4 Brief Summary of the Chapter第39-40页
Chapter 3 Abnormality detection based on Kernelized Entropy第40-54页
    3.1 Introduction第40页
    3.2 Kernelized entropy Model第40-48页
        3.2.1 Entropy and gas turbine exhaust temperature第40-45页
        3.2.2 Entropy extended to Kernelized version for feature quality evaluation第45-48页
    3.3 Results第48-53页
        3.3.1 Data presentation第48-49页
        3.3.2 Kernelized mutual information versus fuzzy rough set method第49-53页
    3.4 Brief Summary of the Chapter第53-54页
Chapter 4 Fault recognition with information entropy based decision tree第54-61页
    4.1 Introduction第54-55页
    4.2 Algorithm design第55-59页
        4.2.1 Feature selection and Rule extraction第56-58页
        4.2.2 Experimental Results第58-59页
    4.3 Brief Summary of the Chapter第59-61页
Chapter 5 M2M structural prototype for remote fault diagnosis第61-65页
    5.1 Introduction第61页
    5.2 Every component’s role in a collective M2M chain第61-64页
        5.2.1 Data acquisition and local monitoring subsystem (DALM)第62-63页
        5.2.2 Data communication subsystem (DAC)第63页
        5.2.3 Data management subsystem (DMS)第63页
        5.2.4 Intelligent diagnosis subsystem (IDS)第63-64页
    5.3 Brief summary of the chapter第64-65页
Chapter 6 Conclusion and recommendations第65-66页
Recommendations第66-67页
References第67-76页
Acknowledgement第76页

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