Multi-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approach

Author:

Ravikumar S.,Kanagasabapathy H.,Muralidharan V.

Publisher

Centre for Evaluation in Education and Science (CEON/CEES)

Subject

Mechanical Engineering,Mechanics of Materials

Reference19 articles.

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2. Xia X., Zhou J., Xiao J., Xiao H.:A novel identification method of Volterra series in rotor-bearing system for fault diagnosis, Mechanical systems and signal processing,No. 66, pp:557-567, 2016.;

3. Dolenc B., Boškoski P., Juričić D.:Distributed bearing fault diagnosis based on vibration analysis,Mechanical Systems and Signal Processing, No. 66, pp: 521-532, 2016.;

4. Yuwono M., Qin Y., Zhou J., Guo Y., Celler B.G., Su S.W.:Automatic bearing fault diagnosis using particle swarm clustering and Hidden Markov Model,Engineering Applications of Artificial Intelligence, No. 47, pp:88-100,2016.;

5. Muralidharan V., Sugumaran V.:Selection of discrete wavelets for fault diagnosis of monoblock centrifugal pump using the J48 algorithm, Applied Artificial Intelligence, No. 27 (1), pp:1-19, 2013.;

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