Journal ArticleDOI
Model-based robust fault detection and isolation of an industrial gas turbine prototype using soft computing techniques
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TLDR
This study proposes a model-based robust fault detection and isolation (RFDI) method with hybrid structure that was tested on a single-shaft industrial gas turbine prototype model and has been evaluated based on the gas turbine data.About:
This article is published in Neurocomputing.The article was published on 2012-08-01. It has received 56 citations till now. The article focuses on the topics: Fault detection and isolation & Multilayer perceptron.read more
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Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review
TL;DR: In this paper, a systematic review of recently developed engine performance monitoring, diagnostic and prognostic techniques is presented, which provides experts, students or novice researchers and decision-makers working in the area of gas turbine engines with the state of the art for performance-based condition monitoring.
Journal ArticleDOI
A Review on Gas Turbine Gas-Path Diagnostics: State-of-the-Art Methods, Challenges and Opportunities
Amare Desalegn Fentaye,Aklilu Tesfamichael Baheta,Syed Ihtsham-ul-Haq Gilani,Konstantinos Kyprianidis +3 more
TL;DR: A critical survey of the existing literature produced in the area over the past few decades is provided, aiming to identify the type of physical faults that degrade a gas turbine performance, which gas-path faults contribute more significantly to the overall performance loss, and which specific components often encounter these faults.
Journal ArticleDOI
Neural network applications in fault diagnosis and detection: an overview of implementations in engineering-related systems
Ahmad Azharuddin Azhari Mohd Amiruddin,Haslinda Zabiri,Syed Ali Ammar Taqvi,Syed Ali Ammar Taqvi,Lemma Dendena Tufa +4 more
TL;DR: Across various ANN applications in FID, it is observed that preprocessing of the inputs is extremely important in obtaining the proper features for use in training the network, particularly when signal analysis is involved.
Journal ArticleDOI
Prediction of Urmia Lake Water-Level Fluctuations by Using Analytical, Linear Statistic and Intelligent Methods
TL;DR: In this paper, two traditional simulator models based on water budget are developed which benefit from most effective components on the water budget namely precipitation, evaporation, inflow and the lake level antecedents, as model inputs.
Journal ArticleDOI
Fault detection in distillation column using NARX neural network
TL;DR: It is shown that the proposed algorithm can be used for the detection of both internal and external faults in the distillation column for dynamic system monitoring and to predict the probability of failure.
References
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Journal ArticleDOI
Detection of abrupt changes: theory and application
TL;DR: A unified framework for the design and the performance analysis of the algorithms for solving change detection problems and links with the analytical redundancy approach to fault detection in linear systems are established.
Book
Robust Model-Based Fault Diagnosis for Dynamic Systems
Jie Chen,Ron J. Patton +1 more
TL;DR: Robust Model-Based Fault Diagnosis for Dynamic Systems targets both newcomers who want to get into this subject, and experts who are concerned with fundamental issues and are also looking for inspiration for future research.
Book
Diagnosis and Fault-Tolerant Control
TL;DR: In this paper, model-based analysis and design methods for fault diagnosis and fault-tolerant control are presented, where the propagation of the fault through the process, test fault detectability and reveal redundancies that can be used to ensure fault tolerance.
Book
Fault detection and diagnosis in engineering systems
TL;DR: In this article, a fault detection and diagnosis framework for discrete linear systems with residual generators and residual generator parameters is presented for additive and multiplicative faults by parameter estimation using a parity equation.
Book
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).