Intelligent Prediction of Fault Severity of Tractor’s Gearbox by Time-domain and Frequency-domain (FFT phase angle and PSD) Statistics Analysis and ANFIS

Authors

  • Mostafa Bahrami Department of Mechanical Engineering of Agricultural Machinery, Faculty of Agriculture, Razi University, Kermanshah, Iran
  • Hossein Javadikia Department of Mechanical Engineering of Agricultural Machinery, Faculty of Agriculture, Razi University, Kermanshah, Iran
  • Ebrahim Ebrahimi Department of Mechanical Engineering, Faculty of Engineering, Kermanshah Branch Islamic Azad University, Kermanshah, Iran

DOI:

https://doi.org/10.3329/jme.v47i1.35421

Abstract

This study presents an approach to intelligent fault prediction based on time-domain and frequency-domain (FFT phase angle and PSD) statistical analysis, Principal component analysis (PCA) and adaptive Neuro-fuzzy inference system (ANFIS). After vibration data acquisition, the approach consists of three stages is conducted. First, different features, including time-domain statistical characteristics, and frequency-domain statistical characteristics are extracted to get more fault detection information. Second, three components by a principal component analysis are obtained from the original feature set. Finally, these three components are inputted into ANFIS for a development model of identifying different abnormal cases. The proposed approach is applied to fault diagnosis of gearbox's number one gear of MF285 tractor, and the testing results show that the proposed model can reliably predict different fault categories and severities.

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Published

2018-05-01

How to Cite

Bahrami, M., Javadikia, H., & Ebrahimi, E. (2018). Intelligent Prediction of Fault Severity of Tractor’s Gearbox by Time-domain and Frequency-domain (FFT phase angle and PSD) Statistics Analysis and ANFIS. Journal of Mechanical Engineering, 47(1), 51–61. https://doi.org/10.3329/jme.v47i1.35421

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Articles