Leak Identification Based on CS-ResNet Under Different Leakage Apertures for Water-Supply Pipeline-Reference-Cited by-同舟云学术

Leak Identification Based on CS-ResNet Under Different Leakage Apertures for Water-Supply Pipeline

Published:2022 Issue: Volume:10 Page:57783-57795
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mei Lin¹,Zhou Jun¹,Li Shuaiyong²^ORCID,Cai Mengqian²^ORCID,Li Tong¹

Affiliation:

1. Chongqing Special Equipment Inspection and Research Institute, Chongqing, China

2. Key Laboratory of Industrial Internet of Things and Networked Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

National Natural Science Foundation Project of China

Natural Science Foundation Project of Chongqing

Chongqing Special Project of Technology Innovation and Application Development

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09780360.pdf?arnumber=9780360

Reference37 articles.

1. Compressive Sensing as Applied to Inverse Problems for Imaging: Theory, Applications, Current Trends, and Open Challenges.

2. Compressed sensing

3. Convolutional Neural Network Based Fault Detection for Rotating Machinery

4. Real-time vibration-based structural damage detection using one-dimensional convolutional neural networks

5. Ultra-Wideband Compressed Sensing: Channel Estimation

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