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150965

Enhancement of Neural Networks Novelty Filters with Genetic Algorithms.

Article

Last updated: 22 Jan 2023

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Subjects

-

Tags

Electronics and Communications Engineering

Abstract

In this paper a method for enhancing the capabilities of Neural Networks novelty filters using genetic algorithms is described, and a method for detecting shorted turns in rotating machines using such computational intelligence techniques (neural network and genetic algorithm) is presented. The methods of signal processing and detection of faults in operating machines is discussed. The use of novelty filters for the detection of shorted turns and mechanical failures in operating machines is described. Genetic algorithm has been used to train the neural network to enhance its Capabilities as a novelty detector. The proposed technique has been applied on an induction machine and the simulation results have been presented to show the effectiveness of the proposed technique. 

DOI

10.21608/bfemu.2021.150965

Authors

First Name

Hamed

Last Name

Elsimary

MiddleName

-

Affiliation

Electronics Research Institute., Dokki, Giza., Egypt.

Email

-

City

Giza

Orcid

-

Volume

22

Article Issue

4

Related Issue

22114

Issue Date

1997-12-01

Receive Date

1997-09-10

Publish Date

2021-12-01

Page Start

14

Page End

23

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 22_Issue 4_Pages 14-23.pdf

PDF . 88.2kB

Link

https://bfemu.journals.ekb.eg/article_150965.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=150965

Order

6

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023