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Viser: Gas Turbine Diagnostics - Signal Processing and Fault Isolation

Gas Turbine Diagnostics - Signal Processing and Fault Isolation

Gas Turbine Diagnostics

Signal Processing and Fault Isolation
Ranjan Ganguli
(2017)
Sprog: Engelsk
CRC Press LLC
960,00 kr.
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Detaljer om varen

  • Paperback: 251 sider
  • Udgiver: CRC Press LLC (April 2017)
  • ISBN: 9781138074422

Widely used for power generation, gas turbine engines are susceptible to faults due to the harsh working environment. Most engine problems are preceded by a sharp change in measurement deviations compared to a baseline engine, but the trend data of these deviations over time are contaminated with noise and non-Gaussian outliers. Gas Turbine Diagnostics: Signal Processing and Fault Isolation presents signal processing algorithms to improve fault diagnosis in gas turbine engines, particularly jet engines. The algorithms focus on removing noise and outliers while keeping the key signal features that may indicate a fault.

The book brings together recent methods in data filtering, trend shift detection, and fault isolation, including several novel approaches proposed by the author. Each method is demonstrated through numerical simulations that can be easily performed by the reader. Coverage includes:

  • Filters for gas turbines with slow data availability
  • Hybrid filters for engines equipped with faster data monitoring systems
  • Nonlinear myriad filters for cases where monitoring of transient data can lead to better fault detection
  • Innovative nonlinear filters for data cleaning developed using optimization methods
  • An edge detector based on gradient and Laplacian calculations
  • A process of automating fault isolation using a bank of Kalman filters, fuzzy logic systems, neural networks, and genetic fuzzy systems when an engine model is available
  • An example of vibration-based diagnostics for turbine blades to complement the performance-based methods

Using simple examples, the book describes new research tools to more effectively isolate faults in gas turbine engines. These algorithms may also be useful for condition and health monitoring in other systems where sharp changes in measurement data indicate the onset of a fault.

Introduction Background Signal Processing Typical Gas Turbine Diagnostics Linear Filters Median Filters Least-Squares Approach Kalman Filter Influence Coefficients Vibration-Based Diagnostics Idempotent Median Filter Weighted Median Filter Center Weighted Median Filter Center Weighted Idempotent Median Filter Test Signal Error Measure Summary Median-Rational Hybrid Filters Test Signals Rational Filter Median-Rational Filter Numerical Simulations Summary FIR-Median Hybrid Filters FIR-Median Hybrid (FMH) Filters Weighted FMH Filter Test Signal Numerical Simulations Summary Transient Data and the Myriad Filter Steady-State and Transient Signals Myriad Filter Numerical Simulations Gas Turbine Transient Signal Weighted Myriad Algorithm Adaptive Weighted Myriad Filter Algorithm Summary Trend Shift Detection Problem Formulation Image Processing Concepts Median Filter Recursive Median Filter Cascaded Recursive Median Filter Edge Detection Numerical Simulations Trend Shift Detection Summary Optimally Weighted Recursive Median Filters Weighted Recursive Median Filters Test Signals Numerical Simulations Test Signal with Outliers Performance Comparison Three- and Seven-Point Optimally Weighted RM Filters Simulations Kalman Filter Kalman Filter Approach Single-Fault Isolation Numerical Simulations Sensor Error Compensation Summary Neural Network Architecture Artificial Neural Network Approach Kalman Filter and Neural Network Methods Autoassociative Neural Network Summary Fuzzy Logic System Module and System Faults Fuzzy Logic System Defuzzification Problem Formulation Fuzzification Rules and Fault Isolation Numerical Simulations Summary Soft Computing Approach Gas Turbine Fault Isolation Neural Signal Processing--Radial Basis Function Neural Networks Fuzzy Logic System Genetic Algorithm Genetic Fuzzy System Numerical Simulations Summary Vibration-Based Diagnostics Formulations Numerical Simulations Summary References Index
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