Vibration Data Analysis for Fault Detection in Manufacturing Systems - A Systematic Literature Review-Reference-Cited by-同舟云学术

Vibration Data Analysis for Fault Detection in Manufacturing Systems - A Systematic Literature Review

Published:2022-12-16 Issue: Volume: Page:
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Container-title:2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA)
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Author:

Lorenz Aske¹,Siewertsen Bende¹,Kyhe Clemmensen Victor¹,Blaamann Petersen Josephine¹,Friederich Jonas¹,Lazarova-Molnar Sanja²

Affiliation:

1. University of Southern Denmark,Mærsk Mc-Kinney Møller Institute,Odense,Denmark,5230

2. Karlsruhe Institute of Technology,Karlsruhe,Germany,76133

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10005874/10005887/10006127.pdf?arnumber=10006127

Reference35 articles.

1. Bearing Fault Detection and Diagnosis Using Case Western Reserve University Dataset With Deep Learning Approaches: A Review

2. A Comprehensive Modeling of Centrifugal Compressor Vibrations for Early Fault Detection;libeyre;Proceedings of the ASME Turbo Expo,2021

3. A Review of Artificial Intelligence Methods for Condition Monitoring and Fault Diagnosis of Rolling Element Bearings for Induction Motor

4. Bearing Fault Detection Using Thomson’s Multitaper Periodogram;gaikwad;Proceedings of the 2nd International Conference on Intelligent Computing and Control Systems,2018

5. Organizing knowledge syntheses: A taxonomy of literature reviews

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1. A noise-robust CNN architecture with global attention and gated convolutional Kernels for bearing fault detection;Measurement Science and Technology;2024-05-30

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