NDLI: Neural network based fault diagnosis and reconfiguration method for multilevel inverter

Content Provider	IEEE Xplore Digital Library
Author	Bin Xu Dan Yang Xu Wang
Copyright Year	2008
Description	Author affiliation: Comput. Center, Northeastern Univ., Shenyang (Bin Xu)
Abstract	Multilevel inverter drivers have become widely applied in high-voltage and high-power applications. Therefore fault diagnosis of voltage source inverters is becoming more and more important. One possible fault within the inverter is IGBT open circuit fault. An overview of the different strategies to detect this fault is given, including the algorithms to localize the fault switch device. This paper presents a technique to improve the fault detection by using an algorithm of neural network with orthogonal basis functions based on recursion least square (RLS) technique. The method is used to identify the type and location of occurring faults from inverter output voltage measurement. Simulation examples of fault diagnosis by the use of the presented method were given. Simulation results have shown that the method performs satisfactorily to detect the fault type fault location and reconfiguration, so it will be very valuable in power system.
Starting Page	564
Ending Page	568
File Size	358164
Page Count	5
File Format	PDF
ISBN	9781424417339
DOI	10.1109/CCDC.2008.4597375
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-02
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fault diagnosis fault diagnosis multilevel inverter Conferences Artificial neural networks neural networks Inverters least square algorithm
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 Libarray 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

Fault Diagnosis and Reconfiguration for Multilevel Inverter Drive Using AI-Based Techniques

Cascaded H-bridge Multilevel Inverter Drives Operating under Faulty Condition with AI-Based Fault Diagnosis and Reconfiguration

Fault Detection and Reconfiguration Technique for Cascaded H-bridge 11-level Inverter Drives Operating under Faulty Condition

A method of inverter circuit fault diagnosis based on BP neural network and D-S evidence theory

Intelligent Fault Diagnosis of Inverter Based on Improved PSO Algorithm

Open-circuit fault diagnosis of transistor in inverter based on wavelet neural network

Fault diagnosis for power units of cascaded inverters based on combined neural network

A Diagnostic Technique for Multilevel Inverters Based on a Genetic-Algorithm to Select a Principal Component Neural Network

Fault detection of a seven level modular multilevel inverter via voltage histogram and Neural Network

Neural network based fault diagnosis and reconfiguration method for multilevel inverter

Similar Documents

Fault Diagnosis and Reconfiguration for Multilevel Inverter Drive Using AI-Based Techniques

Cascaded H-bridge Multilevel Inverter Drives Operating under Faulty Condition with AI-Based Fault Diagnosis and Reconfiguration

Fault Detection and Reconfiguration Technique for Cascaded H-bridge 11-level Inverter Drives Operating under Faulty Condition

A method of inverter circuit fault diagnosis based on BP neural network and D-S evidence theory

Intelligent Fault Diagnosis of Inverter Based on Improved PSO Algorithm

Open-circuit fault diagnosis of transistor in inverter based on wavelet neural network

Fault diagnosis for power units of cascaded inverters based on combined neural network

A Diagnostic Technique for Multilevel Inverters Based on a Genetic-Algorithm to Select a Principal Component Neural Network

Fault detection of a seven level modular multilevel inverter via voltage histogram and Neural Network

Neural network based fault diagnosis and reconfiguration method for multilevel inverter