A Novel Real-Time Fault Diagnostic System for Steam Turbine Generator Set by Using Strata Hierarchical Artificial Neural Network

Energy and Power Engineering

ISSN Print: 1949-243X
ISSN Online: 1947-3818
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"A Novel Real-Time Fault Diagnostic System for Steam Turbine Generator Set by Using Strata Hierarchical Artificial Neural Network"
written by Changfeng YAN, Hao ZHANG, Lixiao WU,
published by Energy and Power Engineering, Vol.1 No.1, 2009

has been cited by the following article(s):

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[1]	Extreme learning machine–radial basis function (ELM-RBF) networks for diagnosing faults in a steam turbine
	2021

[2]	Model-Based Diagnostic Frameworks for Fault Detection and System Monitoring in Nuclear Engineering Systems
	2020

[3]	Development Of Predictive Maintenance Methodology Utilizing Machine Learning Technology To Support Plant Health Management
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[4]	Tìm hiểu phương pháp hiện đại trong lỗi máy điện và các bộ biến đổi công suất
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[5]	Fault detection and diagnosis methods in power generation plants-the Indian power generation sector perspective: an introductory review
	2018

[6]	A Comparative study between Support Vector Machine (SVM) and Extreme Learning Machine (ELM) for Fault Detection in Pumps
	2017

[7]	Neural network based system for detecting and diagnosing faults in steam turbine of thermal power plant
	2017

[8]	An effective fault feature extraction method for gas turbine generator system diagnosis
	Shock and Vibration, 2016

[9]	A survey of fault diagnosis and fault-tolerant techniques—Part I: Fault diagnosis with model-based and signal-based approaches
	2015

[10]	A Survey of Fault Diagnosis and Fault-Tolerant Techniques Part II: Fault Diagnosis with Knowledge-Based and Hybrid/Active Approaches
	2015

[11]	A survey of fault diagnosis and fault-tolerant techniques-Part I: fault diagnosis With model-based and signal-based approaches
	IEEE Transactions on Industrial Electronics, 2015

[12]	A survey of fault diagnosis and fault
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[13]	Real-time fault diagnosis for gas turbine generator systems using extreme learning machine
	Neurocomputing, Elsevier, 2014

[14]	Implementation Of Vlsi Model As A Tool In Diagnostics Of Slowly Varying Process Parameters Which Affect The Performance Of Steam
	Applied Soft Computing, Elsevier, 2014

[15]	Simultaneous-fault diagnosis of gas turbine generator systems using a pairwise-coupled probabilistic classifier
	Mathematical problems in engineering, 2013

[16]	Diagnosis and Detection of IC Engine Fault at End of Line Engine Vibration Measurement System with Machine Learning Model.

[1]	Extreme learning machine – radial basis function (ELM-RBF) networks for diagnosing faults in a steam turbine Journal of Industrial and Production Engineering, 2022 DOI:10.1080/21681015.2021.1887948

[2]	Development Of Predictive Maintenance Methodology Utilizing Machine Learning Technology To Support Plant Health Management 2019 International Conference on Technologies and Policies in Electric Power & Energy, 2019 DOI:10.1109/IEEECONF48524.2019.9102605

[3]	Neural network based system for detecting and diagnosing faults in steam turbine of thermal power plant 2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST), 2017 DOI:10.1109/ICAwST.2017.8256435

[4]	An Effective Fault Feature Extraction Method for Gas Turbine Generator System Diagnosis Shock and Vibration, 2016 DOI:10.1155/2016/9359426

[5]	A Survey of Fault Diagnosis and Fault-Tolerant Techniques Part II: Fault Diagnosis with Knowledge-Based and Hybrid/Active Approaches IEEE Transactions on Industrial Electronics, 2015 DOI:10.1109/TIE.2015.2419013

[6]	Implementation of VLSI model as a tool in diagnostics of slowly varying process parameters which affect the performance of steam turbine Applied Soft Computing, 2014 DOI:10.1016/j.asoc.2014.08.015

[7]	Real-time fault diagnosis for gas turbine generator systems using extreme learning machine Neurocomputing, 2014 DOI:10.1016/j.neucom.2013.03.059

[8]	Simultaneous-Fault Diagnosis of Gas Turbine Generator Systems Using a Pairwise-Coupled Probabilistic Classifier Mathematical Problems in Engineering, 2013 DOI:10.1155/2013/827128

[9]	Effects of Bioethanol-Blended Diesel Fuel on Combustion and Emission Reduction Characteristics in a Direct-Injection Diesel Engine with Exhaust Gas Recirculation (EGR) Energy & Fuels, 2010 DOI:10.1021/ef100233b

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