CNN/Bi‐LSTM‐based deep learning algorithm for classification of power quality disturbances by using spectrogram images

This paper, using an inverse signal approach, presents a novel deep learning algorithm based on a convolutional neural network (CNN) and bidirectional long short‐term memory (Bi‐LSTM) together with spectrograms for the classification of power quality disturbances (PQDs). The proposed method focuses...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	International transactions on electrical energy systems Jg. 31; H. 12
Hauptverfasser:	Özer, İlyas, Efe, Serhat Berat, Özbay, Harun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken John Wiley & Sons, Inc 01.12.2021
Schlagworte:	Algorithms Artificial neural networks bi‐LSTM Classification convolutional neural network Deep learning Disturbances energy quality Image classification Image quality Machine learning power system analysis Sine waves spectrogram Spectrograms
ISSN:	2050-7038, 2050-7038
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!