Decoupling Identification Method of Continuous Working Conditions of Diesel Engines Based on a Graph Self-Attention Network-Reference-Cited by-同舟云学术

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Decoupling Identification Method of Continuous Working Conditions of Diesel Engines Based on a Graph Self-Attention Network

Published:2023-11-22 Issue: Volume: Page:49-54
ISSN:
Container-title:2023 7th International Conference on Electronics, Communication and Aerospace Technology (ICECA)
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Author:

Vijayasharathi N¹,Selukar N. B.²,Ganesh Kumar G.³,Chauhan Amit⁴,Ramachandran Lalitha⁵,Ravindra Sonawane Pavankumar⁶

Affiliation:

1. Panimalar Engineering College,chennai,Tamilnadu,India

2. SGB Amravati University,Chemical Technology Department,Amravati,Maharashtra,India

3. Kakatiya Institute of Technology and Science,Department of Mechanical Engineering,Warangal,Telangana,India

4. Department of life sciences, Christ University Bangalore, Karnataka, India.

5. R.M.K.Engineering College, Kavaraipettai, Tiruvallur, Tamilnadu, India

6. JSPM'S Rajarshi Shahu College of Engineering Tathawade,Mechanical Engineering,Pune,Maharashtra,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10394672/10394681/10394998.pdf?arnumber=10394998

Reference15 articles.

1. Random convolutional neural network structure: An intelligent health monitoring scheme for diesel engines

2. Intelligent fault diagnosis of diesel engine via adaptive VMD-Rihaczek distribution and graph regularized bi-directional NMF

3. A feature extraction and visualization method for fault detection of marine diesel engines

4. Multi-task Bayesian compressive sensing for vibration signals in diesel engine health monitoring

5. Detection of engine misfire using characteristic harmonics of angular acceleration

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