Fault diagnosis of antifriction bearing in internal combustion engine gearbox using data mining techniques

K. N. Ravikumar, Suhas S. Aralikatti, Hemantha Kumar (), G. N. Kumar and K. V. Gangadharan
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K. N. Ravikumar: National Institute of Technology Karnataka
Suhas S. Aralikatti: National Institute of Technology Karnataka
Hemantha Kumar: National Institute of Technology Karnataka
G. N. Kumar: National Institute of Technology Karnataka
K. V. Gangadharan: National Institute of Technology Karnataka

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 3, No 7, 1134 pages

Abstract: Abstract Ball bearing failure are most common failure in rotating machinery, which can be catastrophic. Hence obtaining early failure warning along with precise fault detection technique is at most important. Early detection and timely intervention are the key in condition monitoring for long term endurance of machine components. The early research has used signal processing and spectral analysis extensively for fault detection however data mining with machine learning is most effective in fault diagnosis, the same is presented in this paper. The vibration signals are acquired for an output shaft antifriction bearing in a two-wheeler gearbox operated at various loading conditions with healthy and fault conditions. Data mining is employed for these acquired signals. Statistical, discrete wavelet and empirical mode decomposition are employed for feature extraction process and J48 decision tree for feature selection. Classification is carried out using K*, Random forest and support vector machine algorithm. The classifiers are trained and tested using tenfold cross validation method to diagnose the bearing fault. A comparative study of feature extraction and classifiers are done to evaluate the classification accuracy. The results obtained from K* classifier with wavelet feature yielded better accuracy than rest other classifiers with classification accuracy 92.5% for bearing fault diagnosis.

Keywords: Ball bearing; Data mining techniques; IC engine; Gearbox (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-021-01407-1

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