Indian Journal of Science and Technology
DOI: 10.17485/ijst/2016/v9i47/107933
Year: 2016, Volume: 9, Issue: 47, Pages: 1-8
Original Article
A. Joshuva1 , V. Sugumaran1 *, M. Amarnath2 and Sang-Kwon Lee3
1 School of Mechanical and Building Sciences (SMBS), VIT University, Chennai Campus, Vandalur–Kelambakkam Road, Chennai – 600127, Tamil Nadu, India; [email protected], [email protected] 2 Department of Mechanical Engineering, Indian Institute of Information Technology Design and Manufacturing, Airport Road, IIITDM Jabalpur Campus, Khamaria, Jabalpur – 482005, Madhya Pradesh, India; [email protected] 3 Department of Mechanical Engineering, Inha University, Republic of Korea; [email protected]
*Corresponding author
V. Sugumaran
School of Mechanical and Building Sciences (SMBS), VIT University, Chennai Campus, Vandalur–Kelambakkam Road, Chennai – 600127, Tamil Nadu, India; [email protected]
Objectives: The main objective of this study is to develop a model which can able to predict the remaining life time working of a gearbox using vibration signals. Method: This study is considered as a machine learning problem which consists of three phases, namely feature extraction, feature selection and feature classification. In this research, histogram features are extracted from vibration signals, feature selection are carried out using J48 algorithm and different regression models were built to predict the reaming lifetime assessment of a gearbox. Findings: In this study, the J48 algorithm was used and the regression was found to be 0.8944 for Gaussian model. This is a novel approach to finding the life prediction of gearbox using histogram and regression model. Improvements: This algorithm is applicable for real-time analysis and further the condition monitoring can be carried out using different algorithms with less computation time.
Keywords: Assessment, Fault Diagnosis, Gearbox, Histogram Features, Life Time, Multiple Regression, Sound Signals
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