Vibration analysis of gearbox fault diagnosis using DWT and statistical feature
Joint Authors
Suresh, Setti
M Srinivas
Naidu, VPS
Source
Journal of Engineering Research
Issue
Vol. 10, Issue 3 B (30 Sep. 2022), pp.156-165, 10 p.
Publisher
Kuwait University Academic Publication Council
Publication Date
2022-09-30
Country of Publication
Kuwait
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
The gearbox is one of the critical subsystems in any rotating machinery, which plays a significant role in machine-driven power transmission in terms of change in speed and torque.
It plays a vital role in patching different industrial functionalities.
The advent of developing different gear technologies and the requirement to fulfil the desired mechanical benefits lead to adding more importance to the gearbox health condition monitoring from various types of fault occurrences at an earlier stage.
This study presents the vibration analysis of gearbox fault diagnosis using discrete wavelet transform (DWT) and statistical features.
It is observed that, using wavelet reconstruction in the fault diagnosis, a better fault classification is achieved.
The fault diagnosis has been presented with an emphasis in time-domain followed by two different approaches.
The approach-1 is illustrated as windowing of raw signal, feature extraction, and feature classification using support vector machine (SVM).
In the approach-2, after windowing the raw signal, each window of original vibration signal has converted into wavelet coefficients reconstructed signals (without leaving the time domain) using discrete wavelet transform (DWT) at different levels of decomposition followed by approach-1.
The fault diagnostic accuracy of SVM is presented with 100 Monte-Carlo runs to validate the consistency in the accomplished result.
By observing the success rates in two approaches, it is clear that approach2 with wavelet coefficient’s reconstructed signal is providing better classification accuracy, which can be practically deployed to diagnose the gearbox fault.
American Psychological Association (APA)
Suresh, Setti& M Srinivas& Naidu, VPS. 2022. Vibration analysis of gearbox fault diagnosis using DWT and statistical feature. Journal of Engineering Research،Vol. 10, no. 3 B, pp.156-165.
https://search.emarefa.net/detail/BIM-1495279
Modern Language Association (MLA)
Suresh, Setti…[et al.]. Vibration analysis of gearbox fault diagnosis using DWT and statistical feature. Journal of Engineering Research Vol. 10, no. 3 B (Sep. 2022), pp.156-165.
https://search.emarefa.net/detail/BIM-1495279
American Medical Association (AMA)
Suresh, Setti& M Srinivas& Naidu, VPS. Vibration analysis of gearbox fault diagnosis using DWT and statistical feature. Journal of Engineering Research. 2022. Vol. 10, no. 3 B, pp.156-165.
https://search.emarefa.net/detail/BIM-1495279
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 164-165
Record ID
BIM-1495279