NDLI: Fuzzy neural network approach for fault diagnosis of power plant thermal system under different operating points

Content Provider	IEEE Xplore Digital Library
Author	Liangyu Ma Lee, K.Y.
Copyright Year	2008
Description	Author affiliation: Autom. Dept., North China Electr. Power Univ., Baoding (Liangyu Ma)
Abstract	Developing a practical fault diagnosis system for a power plant thermal system is important in ensuring safe and reliable operation of the whole power generation unit. It is a difficult task due to the complex structure of the thermal system and the variable operating points of the system. Although artificial neural networks are very efficient in thermal system fault diagnosis, their applications for fault diagnosis usually consider only a single operating point (usually at the full rated load). Thus a fuzzy neural network approach for thermal system fault diagnosis under different operating points is investigated in this paper. An extended fuzzy fault symptom calculation method suitable for different load is discussed. The feedwater heater system of a 300 MW coal-fired power generation unit is taken as a fault diagnosis example. Several diagnosis tests for different faults under different operating points are carried out on a full-scope simulator of the power unit. The results under different operating points demonstrate the fault diagnosis ability of the fuzzy neural network method.
Starting Page	1
Ending Page	7
File Size	607803
Page Count	7
File Format	PDF
ISBN	9781424419050
ISSN	19325517
DOI	10.1109/PES.2008.4596176
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis Water heating Artificial neural networks Optimization Load modeling Training Heat pumps symptom optimization Variable operating points fault diagnosis feedwater heaters neural networks power plants symptom fuzzy calculation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Feedwater heater system fault diagnosis during dynamic transient process based on two-stage neural networks

ANN-based diagnosis of boiler four-tube leakage faults under different loads and operating modes

Multidimensional minimization training algorithms for steam boiler high temperature superheater trip using artificial intelligence monitoring system

A fault diagnosis system for heat pumps

Fault intelligent diagnosis for high-pressure feedwater heater system of a 300 MW coal-fired power unit based on improved BP neural network

An Intelligent Power Plant Fault Diagnostics for Varying Degree of Severity and Loading Conditions

The application and research of the intelligent fault diagnosis for marine diesel engine

An Improved Fuzzy Neural Network and Its Application in Machine Fault Diagnosis

Design of distributed energy system based on artificial neural network approach

Fuzzy neural network approach for fault diagnosis of power plant thermal system under different operating points

Similar Documents

Feedwater heater system fault diagnosis during dynamic transient process based on two-stage neural networks

ANN-based diagnosis of boiler four-tube leakage faults under different loads and operating modes

Multidimensional minimization training algorithms for steam boiler high temperature superheater trip using artificial intelligence monitoring system

A fault diagnosis system for heat pumps

Fault intelligent diagnosis for high-pressure feedwater heater system of a 300 MW coal-fired power unit based on improved BP neural network

An Intelligent Power Plant Fault Diagnostics for Varying Degree of Severity and Loading Conditions

The application and research of the intelligent fault diagnosis for marine diesel engine

An Improved Fuzzy Neural Network and Its Application in Machine Fault Diagnosis

Design of distributed energy system based on artificial neural network approach

Fuzzy neural network approach for fault diagnosis of power plant thermal system under different operating points