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Gas Turbine Diagnostics - Signal Processing and Fault Isolation - Ranjan Ganguli (CRC, 2013) pdf

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Description

 							
  
  ISBN 9781466502819
  
  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 						

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