Bibliometric Analysis of Engine Vibration Detection
Author:
Affiliation:
1. Jiangsu Province Key Lab Aerospace Power System, College Energy & Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2. Shanghai Aircraft Design & Research Institute, Shanghai 201210, China
Abstract
Funder
National Natural Science Foundation of China
State Council, People’s Republic of China
Publisher
MDPI AG
Subject
Aerospace Engineering
Link
https://www.mdpi.com/2226-4310/10/9/819/pdf
Reference37 articles.
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2. Automotive Internal-Combustion-Engine Fault Detection and Classification Using Artificial Neural Network Techniques;Ahmed;IEEE Trans. Veh. Technol.,2015
3. Lee, H.J., and Oh, H. (2020). A Study on the Deduction and Diffusion of Promising Artificial Intelligence Technology for Sustainable Industrial Development. Sustainability, 12.
4. Bearing Fault Diagnosis Based on Multi-Scale CNN and Bidirectional GRU;Saghi;Vibration,2023
5. Pazdrii, O., and Bouraou, N. (2018, January 10–12). Two-Level Signal Processing of Vibroacoustical Signals for Condition Monitoring of Complex Rotary System. Proceedings of the 2018 New Trends in Signal Processing (NTSP), Demänovská Dolina, Slovakia.
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