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Research Article

Fault Diagnosis of Gearbox Using Machine Learning Approach

Open Access Peer Reviewed Crossref DOI

Authors

  • Ajinkya Aurangabadkar1
  • Saurabh Kolhe2
  • Safalya Shahakar3
  • Harsh Dubey4
  • Shankul Bhandare5
  • Dr. Pramod Lanjewar6

12345 Final year, B.E., Department of Mechanical Engineering, St. Vincent Pallotti College of Engineering and Technology, Maharashtra, India. 6Professor & Head, Department of Mechanical Engineering, St. Vincent Pallotti College of Engineering and Technology, Maharashtra, India.

Article Information

Published Online
March-April 2023
Pages
608-615
Article Type
Research Article
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References

[1]. He, Zhiyi, et al. "Improved deep transfer auto-encoder for fault diagnosis of gearbox under variable working conditions with small
training samples." Ieee Access 7 (2019): 115368-115377.
[2]. Widodo, Achmad, et al. "Health State Indicator-Based Vibration Signature for Gearbox Condition Monitoring and
Maintenance." IOP Conference Series: Materials Science and Engineering. Vol. 598. No. 1. IOP Publishing, 2019.
[3]. Van, Bui, et al. "Statistical Feature Extraction in Machine Fault Detection using Vibration Signal." 2020 International Conference on
Information and Communication Technology Convergence (ICTC). IEEE, 2020.
[4]. Senanayaka, Jagath Sri Lal, Huynh Van Khang, and Kjell G. Robbersmvr. "CNN based Gearbox Fault Diagnosis and Interpretation
of Learning Features." 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE). IEEE, 2021.
[5]. Qin, Bo, Zixian Li, and Yan Qin. "A Transient Feature Learning-Based Intelligent Fault Diagnosis Method for Planetary
Gearboxes." StrojniskiVestnik/Journal of Mechanical Engineering 66.6 (2020).
[6]. Hao, Wang, et al. "A sparse feature extraction method based on the shiftinvariable dictionary applied in the diagnosis of gearbox
with multiple faults." Journal of Physics: Conference Series. Vol. 2184. No. 1. IOP Publishing, 2022.
[7]. Yaw, Chong Tak, et al. "Fault Diagnosis in Wind Energy Management System using Extreme Learning Machine: A Systematic
Review." Journal of Physics: Conference Series. Vol. 2319. No. 1. IOP Publishing, 2022.
[8]. Chen, ZhiQiang, Chuan Li, and René-Vinicio Sanchez. "Gearbox fault identification and classification with convolutional neural
networks." Shock and Vibration 2015 (2015).
[9]. MohdGhazali, Mohamad Hazwan, and Wan Rahiman. "Vibration analysis for machine monitoring and diagnosis: a systematic
review." Shock and Vibration 2021 (2021): 1-25.
[10]. Elasha, Faris, et al. "Prognosis of a wind turbine gearbox bearing using supervised machine learning." Sensors 19.14 (2019): 3092.
[11]. Vrba, Jan, MatousCejnek, Jakub Steinbach, and Zuzana Krbcova. "A machine learning approach for gearbox system fault
diagnosis." Entropy 23, no. 9 (2021): 1130.
[12]. Koukoura, Sofia, et al. "Comparison of wind turbine gearbox vibration analysis algorithms based on feature extraction and
classification." IET Renewable Power Generation 13.14 (2019): 2549-2557.
[13]. Balachandar, K., R. Jegadeeshwaran, and D. Gandhikumar. "Condition monitoring of FSW tool using vibration analysis–A machine
learning approach." Materials Today: Proceedings 27 (2020): 2970-2974.
[14]. Hosseinpour-Zarnaq, Mohammad, Mahmoud Omid, and EbrahimBiabani-Aghdam. "Fault diagnosis of tractor auxiliary gearbox
using vibration analysis and random forest classifier." Information Processing in Agriculture 9.1 (2022): 60-67.
[15]. Praveenkumar, T., et al. "Fault diagnosis of automobile gearbox based on machine learning techniques." Procedia Engineering 97
(2014): 2092-2098.
[16]. Umbrajkaar, A. M., A. Krishnamoorthy, and R. B. Dhumale. "Vibration analysis of shaft misalignment using machine learning
approach under variable load conditions." Shock and Vibration 2020 (2020): 1-12.
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