Procedure of fault detection for driving systems using self-organizing neural networks

Gheorghe Puscasu; Vasile Palade; Alexandru Stancu

doi:10.1109/MELCON.2000.879966

Procedure of fault detection for driving systems using self-organizing neural networks

Gheorghe Puscasu, Vasile Palade, Alexandru Stancu

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Abstract

In the paper it is proposed a neural network based procedure for the recognition of faults to a DC driving system. The analysis procedure of the faults can be used to warn the human user when a new class of faults is detected.

Original language	English
Title of host publication	Proceedings of the Mediterranean Electrotechnical Conference - MELECON
Publisher	IEEE
Pages	446-448
Number of pages	3
Volume	2
ISBN (Print)	0-7803-6290-X
DOIs	https://doi.org/10.1109/MELCON.2000.879966
Publication status	Published - 2000
Externally published	Yes
Event	10th Mediterranean Electrotechnical Conference - Lemesos, Cyprus Duration: 29 May 2000 → 31 May 2000

Conference

Conference	10th Mediterranean Electrotechnical Conference
Abbreviated title	MALECON2000
Country/Territory	Cyprus
City	Lemesos
Period	29/05/00 → 31/05/00

Keywords

Fault detection
Neural networks
DC motors
Data mining
Transfer functions
Pattern recognition
Fault diagnosis
Induction motors
Equations
Optimization methods
electric machine analysis computing
DC motor drives
fault diagnosis
machine theory
self-organising feature maps
learning (artificial intelligence)
fault class
DC motor drive system
fault detection
self-organizing neural networks
analysis procedure
fault recognition

ASJC Scopus subject areas

Electrical and Electronic Engineering

Access to Document

10.1109/MELCON.2000.879966

Cite this

@inproceedings{eac17df737e9481bad69c52550a9fe44,

title = "Procedure of fault detection for driving systems using self-organizing neural networks",

abstract = "In the paper it is proposed a neural network based procedure for the recognition of faults to a DC driving system. The analysis procedure of the faults can be used to warn the human user when a new class of faults is detected.",

keywords = "Fault detection, Neural networks, DC motors, Data mining, Transfer functions, Pattern recognition, Fault diagnosis, Induction motors, Equations, Optimization methods, electric machine analysis computing, DC motor drives, fault diagnosis, machine theory, self-organising feature maps, learning (artificial intelligence), fault class, DC motor drive system, fault detection, self-organizing neural networks, analysis procedure, fault recognition",

author = "Gheorghe Puscasu and Vasile Palade and Alexandru Stancu",

year = "2000",

doi = "10.1109/MELCON.2000.879966",

language = "English",

isbn = "0-7803-6290-X",

volume = "2",

pages = "446--448",

booktitle = "Proceedings of the Mediterranean Electrotechnical Conference - MELECON",

publisher = "IEEE",

address = "United States",

note = "10th Mediterranean Electrotechnical Conference, MALECON2000 ; Conference date: 29-05-2000 Through 31-05-2000",

}

TY - GEN

T1 - Procedure of fault detection for driving systems using self-organizing neural networks

AU - Puscasu, Gheorghe

AU - Palade, Vasile

AU - Stancu, Alexandru

PY - 2000

Y1 - 2000

N2 - In the paper it is proposed a neural network based procedure for the recognition of faults to a DC driving system. The analysis procedure of the faults can be used to warn the human user when a new class of faults is detected.

AB - In the paper it is proposed a neural network based procedure for the recognition of faults to a DC driving system. The analysis procedure of the faults can be used to warn the human user when a new class of faults is detected.

KW - Fault detection

KW - Neural networks

KW - DC motors

KW - Data mining

KW - Transfer functions

KW - Pattern recognition

KW - Fault diagnosis

KW - Induction motors

KW - Equations

KW - Optimization methods

KW - electric machine analysis computing

KW - DC motor drives

KW - fault diagnosis

KW - machine theory

KW - self-organising feature maps

KW - learning (artificial intelligence)

KW - fault class

KW - DC motor drive system

KW - fault detection

KW - self-organizing neural networks

KW - analysis procedure

KW - fault recognition

UR - http://www.scopus.com/inward/record.url?scp=0034476514&partnerID=8YFLogxK

U2 - 10.1109/MELCON.2000.879966

DO - 10.1109/MELCON.2000.879966

M3 - Conference proceeding

AN - SCOPUS:0034476514

SN - 0-7803-6290-X

VL - 2

SP - 446

EP - 448

BT - Proceedings of the Mediterranean Electrotechnical Conference - MELECON

PB - IEEE

T2 - 10th Mediterranean Electrotechnical Conference

Y2 - 29 May 2000 through 31 May 2000

ER -

Procedure of fault detection for driving systems using self-organizing neural networks

Abstract

Conference

Keywords

ASJC Scopus subject areas

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