Designing Evolutionary Wavelet Neural Network for Estimating Foaming Slag Quality in Electric Arc Furnace Using Power Quality Indices

Hamzeh Rezvani; Hamed Khodadadi

doi:10.17775/CSEEJPES.2020.02450

欢迎来到能源电力期刊网！

English Version 期刊登录

您当前的位置：

首页 >

文章列表页 >

Designing Evolutionary Wavelet Neural Network for Estimating Foaming Slag Quality in Electric Arc Furnace Using Power Quality Indices

Regular Papers | 更新时间：2026-10-15

- Designing Evolutionary Wavelet Neural Network for Estimating Foaming Slag Quality in Electric Arc Furnace Using Power Quality Indices
- Designing Evolutionary Wavelet Neural Network for Estimating Foaming Slag Quality in Electric Arc Furnace Using Power Quality Indices
- 中国电机工程学会电力与能源系统学报(英文) 2022年8卷第4期页码：1165-1174
- 作者机构：
  
  Department of Electrical Engineering, Khomeinishahr Branch, Islamic Azad University, Isfahan,Iran
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2020.02450
  中图分类号：
- 纸质出版：2022-07-01
- 稿件说明：
移动端阅览
Hamzeh Rezvani, Hamed Khodadadi. Designing Evolutionary Wavelet Neural Network for Estimating Foaming Slag Quality in Electric Arc Furnace Using Power Quality Indices[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(4):1165-1174.

Hamzeh Rezvani, Hamed Khodadadi. Designing Evolutionary Wavelet Neural Network for Estimating Foaming Slag Quality in Electric Arc Furnace Using Power Quality Indices[J]. CSEE Journal of Power and Energy Systems, 2022, 8(4): 1165-1174.
Hamzeh Rezvani, Hamed Khodadadi. Designing Evolutionary Wavelet Neural Network for Estimating Foaming Slag Quality in Electric Arc Furnace Using Power Quality Indices[J]. 中国电机工程学会电力与能源系统学报(英文), 2022,8(4):1165-1174. DOI： 10.17775/CSEEJPES.2020.02450.

Hamzeh Rezvani, Hamed Khodadadi. Designing Evolutionary Wavelet Neural Network for Estimating Foaming Slag Quality in Electric Arc Furnace Using Power Quality Indices[J]. CSEE Journal of Power and Energy Systems, 2022, 8(4): 1165-1174. DOI： 10.17775/CSEEJPES.2020.02450.

摘要

Abstract

In the present study

a novel approach based on an evolutionary wavelet neural network (EWNN) is proposed to estimate the slag quality in an electric arc furnace (EAF) employing power quality indices. In the EWNN

an evolutionary method is applied to train the parameters for a combination of neural networks and wavelets. For this purpose

all of the electrical parameters for six melting processes are measured with a power quality analyzer

attached to the secondary component of an EAF transformer at a Saba steel complex

to estimate the foaming slag quality. Experimental results on various combinations of measured electrical parameters

applying the designed EWNN estimator

demonstrate that utilizing five leading indicators leads to the highest precision. The obtained 99% accuracy for estimating the foaming slag quality by EWNN compared to the other methods illustrates the proposed method's efficiency.

关键词

Keywords

references

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

Suppression Strategy of Background Harmonic Voltage Based on Cooperative Control in Weak Grid

Location of Asymmetric Ground Fault Using Virtual Injected Current Ratio and Two-stage Recovery Strategy in Distribution Networks

Continuous Mixed p-norm Control Scheme with Reweighted L0 norm Variable Step Size for Mitigating Power Quality Problems of Grid Coupled Solar PV Systems

Multifunctional Bidirectional Charging System for EVs and Grid with Improved Power Quality Using a Sparse Proportionate-NLMF Based Method

Grid Tied Solar PV System with Power Quality Enhancement Using Adaptive Generalized Maximum Versoria Criterion