Analyzing Transient Phenomena in the Time Domain Using Empirical Mode Decomposition(EMD)

The feature selection verification algorithm is the core method of the electromagnetic simulation credibility evaluation system established by IEEE standard 1597.1. However, the problem of feature selection validation algorithm’s failure in transient data needs to be solved. This article conducts in-depth research on this and applies the Empirical Mode Decomposition (EMD) algorithm to transient data trustworthiness verification, and verifies the effectiveness of this method.

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Published
2024-09-22
DOI
https://doi.org/10.1109/apcap62011.2024.10881315
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Analyzing Transient Phenomena in the Time Domain Using Empirical Mode Decomposition(EMD)

Huapeng Zhao, Jun Hu, Zhiwei Gao, Jiaxin Shi et al.
Machine Fault Diagnosis Techniques
article

Analyzing Transient Phenomena in the Time Domain Using Empirical Mode Decomposition(EMD)

Huapeng Zhao, Jun Hu, Zhiwei Gao, Jiaxin Shi, Wei Chen, Min Zhang
article en

Abstract

The feature selection verification algorithm is the core method of the electromagnetic simulation credibility evaluation system established by IEEE standard 1597.1. However, the problem of feature selection validation algorithm’s failure in transient data needs to be solved. This article conducts in-depth research on this and applies the Empirical Mode Decomposition (EMD) algorithm to transient data trustworthiness verification, and verifies the effectiveness of this method.

University of Electronic Science and Technology of China (CN), Harbin Institute of Technology (CN), Shijiazhuang Tiedao University (CN)
Nature
Reduced inequalities
Openalex Percentile: Top 66%
Machine Fault Diagnosis Techniques
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Analyzing Transient Phenomena in the Time Domain Using Empirical Mode Decomposition(EMD) — Huapeng Zhao, Jun Hu, et al. · (2024) | TGRS Research Map | TGRS