Machine Learning-Based Fault Diagnosis for Rotating Machinery in Industrial Settings-Reference-Cited by-同舟云学术

Machine Learning-Based Fault Diagnosis for Rotating Machinery in Industrial Settings

Published:2024-04-04 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)
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Author:

G Arun Francis¹,Alamanda Sophia²,Babu S. B G Tilak³,Kavita K.⁴,Pesaru Prathyusha Reddy⁵,L Natrayan⁶

Affiliation:

1. Karpagam College of Engineering,Electronics and Communication Engineering,Coimbatore,Tamil Nadu

2. Satya institute of technology and management,CSE,Vizianagaram,Andhra Pradesh

3. Aditya Engineering College,Department of ECE,Surampalem

4. JNTU Hyderabad technological University, BVRIT Hyderabad College of Engineering for Women,Hyderabad,Telangana,India,500090

5. Sumathi Reddy Institute of Technology for Women,CSE Department,Telangana,India

6. Saveetha School of Engineering, SIMATS,Department of Mechanical Engineering,Chennai,Tamil Nadu,India,602105

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10568576/10568577/10568891.pdf?arnumber=10568891

Reference12 articles.

1. Machine Learning-Based Fault Diagnosis of Self-Aligning Bearings for Rotating Machinery Using Infrared Thermography

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4. Optimization of Solar Hybrid Power Generation Using Conductance-Fuzzy Dual-Mode Control Method

5. Efficient employment of Yb doped multi-mode fiber amplifiers based pumped laser with advanced light sources in high speed modulated optical communication systems