NDLI: Research on aviation synchronous generator dynamic performance based on empirical mode decomposition and support vector machine

Content Provider	IEEE Xplore Digital Library
Author	Wei Tang Dongchao Yan Chuang Guo
Copyright Year	2012
Description	Author affiliation: College of Engineering, Air Force Engineering University 12th team of Graduate Management Battalion of College of Engineering, Air Force Engineering University, China, Xi'an (Wei Tang; Dongchao Yan; Chuang Guo)
Abstract	Based on the in-depth study of empirical mode decomposition (EMD) and support vector machine (SVM) algorithm, a model for aviation synchronous generator dynamic performance was presented. The EMD method was firstly used to denoise the input signal of the model. The SVM method was used to establish the model of synchronous generator's dynamic performance under the condition of instant load and unload. The results showed that the dynamic transient process of aviation synchronous generator's voltage regulation was successfully described by the model, so this method was proven to be correct and reliable.
Starting Page	729
Ending Page	734
File Size	318260
Page Count	6
File Format	PDF
ISBN	9781467303125
e-ISBN	9781467303118
DOI	10.1109/INDIN.2012.6301161
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines empirical mode decomposition support vector machine Atmospheric modeling dynamic performance Noise Power system dynamics Generators Aircraft synchronous generator Load modeling
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

Power system excitation control based on support vector machine

Network traffic forecasting by support vector machines based on empirical mode decomposition denoising

The Forecasting of Electrical Consumption Proportion of Different Industries in Substation Based on SCADA and the Daily Load Curve of Load Control System

Minimum frequency prediction of power system after disturbance based on the v-support vector regression

Multi-generator system modelling based on dynamic phasor concept

Power Load Modeling Based on Wide-Area Measurements and Support Vector Machine

A study on dynamic behavior of load supply system including synchronous generators with and without load drop

Application of relevance vector regression model based on sparse bayesian learning to long-term electricity demand forecasting

Hybrid of EMD and SVMs for Short-Term Load Forecasting

Research on aviation synchronous generator dynamic performance based on empirical mode decomposition and support vector machine

Similar Documents

Power system excitation control based on support vector machine

Network traffic forecasting by support vector machines based on empirical mode decomposition denoising

The Forecasting of Electrical Consumption Proportion of Different Industries in Substation Based on SCADA and the Daily Load Curve of Load Control System

Minimum frequency prediction of power system after disturbance based on the v-support vector regression

Multi-generator system modelling based on dynamic phasor concept

Power Load Modeling Based on Wide-Area Measurements and Support Vector Machine

A study on dynamic behavior of load supply system including synchronous generators with and without load drop

Application of relevance vector regression model based on sparse bayesian learning to long-term electricity demand forecasting

Hybrid of EMD and SVMs for Short-Term Load Forecasting

Research on aviation synchronous generator dynamic performance based on empirical mode decomposition and support vector machine