Power Quality Transient Disturbance Diagnosis Based on Dynamic Large Convolution Kernel and Multi-Level Feature Fusion Network
Author:
Affiliation:
1. Electric Power Research Institute, State Grid Henan Electric Power Company, No. 85 Songshan South Road, Erqi District, Zhengzhou 450001, China
2. Zhengzhou Power Supply Bureau, State Grid Henan Electric Power Company, Zhengzhou 450001, China
Abstract
Funder
National Natural Science Foundation of China
Science and Technology Program of the State Grid Corporation
Publisher
MDPI AG
Link
https://www.mdpi.com/1996-1073/17/13/3227/pdf
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3. Raza, A., Benrabah, A., Alquthami, T., and Akmal, M. (2020). A Review of Fault Diagnosing Methods in Power Transmission Systems. Appl. Sci., 10.
4. Undervoltage Identification in Three Phase Induction Motor Using Low-Cost Piezoelectric Sensors and STFT Technique;Carvalho;Proceedings,2020
5. Power data prediction method of new energy system based on wavelet transform and adaptive hybrid optimization;Xiong;Int. J. Low-Carbon Technol.,2024
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