Effectiveness Analysis of the Mel spectrum features of AE signals in the detection of partial discharge faults-Reference-Cited by-同舟云学术

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Effectiveness Analysis of the Mel spectrum features of AE signals in the detection of partial discharge faults

Published:2022-11-30 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD)
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Author:

Lu Li'an¹,Tao Wanning¹,Liu Guangyu¹,Xiao Hui¹,Li Xuefeng²

Affiliation:

1. College of Electronic and Information Engineering, Tongji University,Shanghai,P. R. China

2. College of Electronic and Information Engineering; Frontiers Science Center for Intelligent Autonomous Systems, Tongji University,Shanghai,P. R. China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10058187/10058056/10058210.pdf?arnumber=10058210

Reference18 articles.

1. Optimized Denoising Method for Weak Acoustic Emission Signal in Partial Discharge Detection

2. Partial Discharge Recognition Based on Optical Fiber Distributed Acoustic Sensing and a Convolutional Neural Network

3. Deep Residual Learning for Image Recognition

4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift;ioffe;International Conference on Machine Learning,0

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1. Drive-by damage detection methodology for high-speed railway bridges using sparse autoencoders;Railway Engineering Science;2024-08-29

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