Sugumaran V

Mechanical

School of Mechanical Engineering

Chennai Campus

M amarnath

Deepak jain

Hemantha kumar

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

International Journal of Decision Support Systems

Fulltext

Indian Journal of Science and Technology

Fault Diagnostics of a Gearbox via Acoustic Signal using Wavelet Features, J48 Decision Tree and Random Tree Classifier

Acoustic Signal Based Condition Monitoring of Gearbox using Wavelets and Decision Tree Classifier

Gears are machine elements that transmit motion by means of successively engaging teeth. In purely scientific terms, gears are used to transmit motion. A faulty gear is a matter of serious concern as it affects the functionality of a machine to a great extent. Thus it is essential to diagnose the faults at an initial stage so as to reduce the losses that might be incurred. This necessitates the need for continuous monitoring of the gears. The vibrations produced by gears from good and simulated faulty conditions can be effectively used to detect the faults in these gears. The introduction of Variational Mode Decomposition (VMD) as a new signal pre-processing technique along with the different decision trees have provided good classification performance. VMD allows decomposition of the signal into various modes by identifying a compact frequency support around its central frequency, such that adding all the modes reconstructs the original signal. Alternating direction multiplier method (ADMM) is used by VMD to find the intrinsic mode functions on central frequencies. Meaningful statistical features can be extracted from VMD processed signals. J48 decision tree algorithm was used to identify the useful features and the selected features were used for classification using the decision trees namely, Random Forest, REP Tree and Logistic Model Tree algorithms. The performance analyses of various algorithms are discussed in detail. Copyright © 2014 Tech Science Press.

Fault diagnosis of helical gear box using variational mode decomposition and J48 algorithm

Mechanical Systems and Signal Processing

Statistical fault diagnosis based on vibration analysis for gear test-bench under non-stationary conditions of speed and load

Multivariate and multiscale monitoring of large-size low-speed bearings using Ensemble Empirical Mode Decomposition method combined with Principal Component Analysis

Expert Systems with Applications

Studies on Bayes classifier for condition monitoring of single point carbide tipped tool based on statistical and histogram features

Applied Soft Computing

Fault diagnosis of spur bevel gear box using artificial neural network (ANN), and proximal support vector machine (PSVM)

Applied Acoustics

Condition monitoring of a single-stage gearbox with artificially induced gear cracks utilizing on-line vibration and acoustic emission measurements

Fault diagnosis of helical gear box using naïve Bayes and Bayes net

Journal	International Journal of Decision Support Systems
Publisher	Inderscience Publishers
ISSN	2050-6988
Open Access	0