Proceedings ArticleDOI
V94.2 industrial gas turbine compressor fouling detection based on system identification methods, neural networks and experimental data
Sahar Rahimi Malekshan,Mahdi Aliyari Shoorehdeli,Mostafa Yari +2 more
- pp 709-714
TLDR
In this paper, a model based fault detection of gas turbine using linear and non-linear methods (multilayer perceptron and radial basis function neural network models) is studied.Abstract:
In this paper, model based fault detection of gas turbine using linear and non-linear methods (multilayer perceptron and radial basis function neural network models) is studied. We contemplate IGV positions and gas flow as input and sensors related to compressor as outputs. Then residual signals will be obtained based on system model. In addition, by these signals and exert the fixed and adaptive thresholds, the fault occurred in the V94.2 gas turbine which is pollution of vane compressor (Fouling detection) has identified and diagnosed. Consequently, by comparing the obtained results from different fault detection methods, we determine the most appropriate signal output that led to better and reliable result. All simulations have been carried out by using real data taken from an V94.2 industrial gas turbine 927 power plant in Fars.read more
Citations
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Proceedings ArticleDOI
Ensemble-Based Fault Detection and Isolation of an Industrial Gas Turbine
TL;DR: In this study, an efficient strategy for fault detection and isolation of an Industrial Gas Turbine is introduced based on ensemble learning methods, which is capable of isolating faults in a steady-state runtime.
Journal ArticleDOI
A Robust fault diagnosis and forecasting approach based on Kalman filter and Interval Type-2 Fuzzy Logic for efficiency improvement of centrifugal gas compressor system
TL;DR: The obtained results prove the performance of the proposed faults diagnosis and detection approach which can be used in several heavy industrial systems.
References
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Neural Networks: A Comprehensive Foundation
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TL;DR: This book is to introduce basic model-based FDI schemes, advanced analysis and design algorithms and the needed mathematical and control theory tools at a level for graduate students and researchers as well as for engineers.
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Fault-Diagnosis Systems
TL;DR: In this paper, the authors present a comparison and combination of fault-detection methods for different types of fault detection methods: Fault detection with classification methods, fault detection with inference methods, and fault detection using Principal Component Analysis (PCA).
Journal ArticleDOI
Fault Detection and Diagnosis in Industrial Systems
TL;DR: The appearance of this book is quite timely as it provides a much needed state-of-the-art exposition on fault detection and diagnosis, a topic of much interest to industrialists.
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Model-based fault diagnosis in dynamic systems using identification techniques
TL;DR: The model-based Fault Diagnosis techniques used in this study focused on system identification, while the application studies focused on residual generation and identification.
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