Non-Contact Fault Diagnosis of Bearings using Ensemble and NaÏve Bayes Classifiers-Reference-Cited by-同舟云学术

Non-Contact Fault Diagnosis of Bearings using Ensemble and NaÏve Bayes Classifiers

Published:2023-06-15 Issue: Volume: Page:
ISSN:
Container-title:2023 5th International Conference on Energy, Power and Environment: Towards Flexible Green Energy Technologies (ICEPE)
language:
Short-container-title:

Author:

Gill Kanwarpartap Singh¹,Goyal Deepam¹,Chaudhary Anurag²,Senthil V.³,Goyal Tarun⁴,Dang Rajeev Kumar⁵

Affiliation:

1. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

2. School of Interdisciplinary Research, Indian Institute of Technology,Delhi

3. Government College of Engineering,Department of Mechanical Engineering,Bodinayakanur,Tamilnadu

4. IKGPTU,Department of Mechanical Engineering,Jalandhar

5. PUSSGRC,Department of Mechanical Engineering,Hoshiarpur,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10201476/10201477/10201632.pdf?arnumber=10201632

Reference12 articles.

1. Multidomain Bearing Fault Diagnosis using Support Vector Machine;mishra;2021 IEEE 4th International Conference on Computing Power and Communication Technologies GUCON 2021,2021

2. Model based fault diagnosis of a rotor–bearing system for misalignment and unbalance under steady-state condition

3. Amplitude and phase interaction in Hilbert demodulation of vibration signals: Natural gear wear modeling and time tracking for condition monitoring

4. Vibration Signals Analysis by Explainable Artificial Intelligence (XAI) Approach: Application on Bearing Faults Diagnosis

5. Vibration Response Based Intelligent Non-Contact Fault Diagnosis of Bearings;goyal;ASME Journal of Nondestructive Evaluation Diagnostics and Prognostics of Engineering Systems,2020