MATEC Web of Conferences
Volume 150, 2018Malaysia Technical Universities Conference on Engineering and Technology (MUCET 2017)
|Number of page(s)||5|
|Section||Electrical & Electronic|
|Published online||23 February 2018|
- M. Irfan, N. Saad, R. Ibrahim, V.S. Asirvadam, An intelligent diagnostic system for the condition monitoring of AC motors, 8th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp. 1248-1253 (2013) [Google Scholar]
- H. Wasif, A. Aboutalebi, D. Brown, L. Axel-Berg, Condition monitoring system for process industries a business approach, IEEE Symposium on Industrial Electronics and Applications (ISIEA), pp. 251-256 (2012) [Google Scholar]
- M.A.A. Elmaleeh, N. Saad. Acoustic emission techniques for early detection of bearing faults using LabVIEW, 5th International Symposium on Mechatronics and Its Applications, pp. 1-5 (2008) [Google Scholar]
- Ling Xiang, Lanlan Hou, Feature analysis of interaction on rub-impact and oil-film faults for a rotor-bearing system, 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), pp. 246-254 (2015) [CrossRef] [Google Scholar]
- G.A. Skrimpas et al. Detection of generator bearing inner race creep by means of vibration and temperature analysis, IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), pp. 303-309 (2015) [Google Scholar]
- Wei Feng et al., Modeling and Simulation of Process-Machine Interaction in Grinding of Cemented Carbide Indexable Inserts, Hindawi Publishing Corporation, Shock and Vibration, Article ID 508181 (2014) [Google Scholar]
- B.P. Graney, K. Starry, Rolling Element Bearing Analysis, The American Society for Nondestructive Testing Inc., Materials Evaluation, 70(1), pp. 78-85 (2012) [Google Scholar]
- L.S. Dhamande, M.B. Chaudhari, Detection of Combined Gear-Bearing Fault in Single Stage Spur Gear Box Using Artificial Neural Network, Procedia Engineering, Elsevier, 144, pp. 759-766 (2016) [CrossRef] [Google Scholar]
- Z.X. Li, J.J. Zhu, X.F. Shen, C. Zhang, J.W. Guo, Fault Diagnosis of Motor Bearing Based on the Bayesian Network, Procedia Engineering, Elsevier. 16, pp. 18-26 (2011) [CrossRef] [Google Scholar]
- H.S. Kumar, P.P. Srinivasa, N.S. Sriram, G.S. Vijay, ANN-based evaluation of performance of wavelet transform for condition monitoring of rolling element bearing, Procedia Engineering, Elsevier, 64, pp. 805- 814 (2013) [CrossRef] [Google Scholar]
- A.K Mahamad, T. Hiyama, Diagnosis and Prognosis of Bearing Failure in Rotating Machinery using Acoustic Emission and Artificial Neural Network, IEEJ Transactions on Industry Applications, 130, pp. 443-449 (2009) [CrossRef] [Google Scholar]
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