Scopus
🔓 Açık Erişim YÖKSİS DOI Eşleşti
SJR Q2
An artificial neural network approach for sensorless speed estimation via rotor slot harmonics
Turkish Journal of Electrical Engineering and Computer Sciences · Ocak 2014
YÖKSİS Kayıtları
An artificial neural network approach for sensorless speed estimation via rotor slot harmonics
Turkish Journal of Electrical Engineering and Computer Sciences · 2014 SCI-Expanded
Prof. Dr. HAYRİ ARABACI →
YÖKSİS Kayıtları — ISSN Eşleşmesi
A fuzzy rule based system for predicting the live weight of Holstein cows whose body dimensions were determined by image analysis
2011 ISSN: 1300-0632 SCI-Expanded
Prof. Dr. ŞAKİR TAŞDEMİR →
A new ABC-based multiobjective optimization algorithm with an improvement approach (IBMO: improved bee colony algorithm for multiobjective optimization)
2016 ISSN: 13000632 SCI-Expanded
Doç. Dr. TAHİR SAĞ →
A new ABC based multiobjective optimization algorithm with an improvement approach IBMO improved bee colony algorithm for multiobjective optimization
2016 ISSN: 13000632 SCI-Expanded
Prof. Dr. MEHMET ÇUNKAŞ →
A Control Scheme Employing an Adaptive Hysteresis Current Controller and an Uncomplicated Reference Current Generator for a Single-Phase Shunt Active Power Filter
2014 ISSN: 1300-0632 SCI-Expanded
Dr. Öğr. Üyesi HÜSEYİN DOĞAN →
An artificial neural network approach for sensorless speed estimation via rotor slot harmonics
2014 ISSN: 1300-0632 SCI-Expanded
Prof. Dr. HAYRİ ARABACI →
Modeling and evaluation of SOC-based coordinated EV charging for power
management in a distribution system
2022 ISSN: 1300-0632 SCI-Expanded Q4
Dr. Öğr. Üyesi MURAT AKIL →
The analysis and optimization of CNN Hyperparameters with fuzzy tree model for image classification
2022 ISSN: 1300-0632 Inspec, Scopus, Ei Compendex, Engineering Source, Web of Science
Doç. Dr. İLKER ALİ ÖZKAN →
The analysis and optimization of CNN Hyperparameters with fuzzy tree model
for image classification
2022 ISSN: 1300-0632 SCI Q4
Prof. Dr. ŞAKİR TAŞDEMİR →
Comparison of ML algorithms to distinguish between human or human-like targets using the HOG features of range-time and range-Doppler images in through-the-wall applications
2022 ISSN: 1300-0632 SCI-Expanded Q4
Dr. Öğr. Üyesi YUNUS EMRE ACAR →
Makale Bilgileri
ISSN13000632
Yayın TarihiOcak 2014
Cilt / Sayfa22 · 1076-1084
Scopus ID2-s2.0-84902193536
Erişim🔓 Açık Erişim
Özet
In this paper, a sensorless speed estimation method with an artificial neural network for squirrel cage induction motors is presented. Motor current is generally used for sensorless speed estimation. Rotor slot harmonics are available in the frequency spectrum of the current. The frequency components of these determined harmonics are used to estimate the speed of the motor in which the number of rotor slots is given. In the literature, individual algorithms have been used to calculate the speed from the slot harmonics. Unlike the literature, in the proposed method, an artificial neural network is used to extract the speed from the rotor slot harmonic components in the spectrum. This experimental study is carried out to prove the method under steady-state conditions. The experimental results show that the proposed method is suitable for speed estimation and its average error is below 1.5 rpm.
Yazarlar (1)
1
Hayri Arabaci
Anahtar Kelimeler
Artificial neural network
Induction motor
Rotor slot harmonics
Sensorless speed estimation
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Turkish Journal of Electrical Engineering and Computer Sciences
Q2
OA
SJR Skoru0,360
H-Index45
YayıncıTUBITAK
ÜlkeTurkey
Computer Science (miscellaneous) (Q2)
Electrical and Electronic Engineering (Q3)
Metrikler
6
Atıf
1
Yazar
4
Anahtar Kelime