Multi-Source Ensemble Learning With Acoustic Spectrum Analysis for Fault Perception of Direct-Buried Transformer Substations-Reference-Cited by-同舟云学术

Multi-Source Ensemble Learning With Acoustic Spectrum Analysis for Fault Perception of Direct-Buried Transformer Substations

Author:

Guo Siyuan¹^ORCID,Zhou Bin¹^ORCID,Yang Yun²^ORCID,Wu Qiuwei³^ORCID,Xiang Yue⁴^ORCID,He Yang¹^ORCID

Affiliation:

1. College of Electrical and Information Engineering, Hunan University, Changsha, China

2. Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong

3. Tsinghua-Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China

4. College of Electrical Engineering, Sichuan University, Chengdu, China

Funder

National Natural Science Foundation of China

Hunan Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Systems Engineering

Link

Reference43 articles.

2. Time-series generative adversarial networks;yoon;Adv Neural Inf Process Syst,2019

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2. Fault diagnosis method for distribution network transformer based on artificial intelligence;3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023);2023-07-21