Open Access
| Issue |
E3S Web Conf.
Volume 519, 2024
5th Talenta Conference on Engineering, Science and Technology (TALENTA CEST-5 2024)
|
|
|---|---|---|
| Article Number | 03027 | |
| Number of page(s) | 4 | |
| Section | Environment Science | |
| DOI | https://doi.org/10.1051/e3sconf/202451903027 | |
| Published online | 01 May 2024 | |
- C.S. Kallesoe et al., “Aalborg Universitet Model Based Fault Diagnosis in a Centrifugal Pump Application using Structural Analysis Model Based Fault Diagnosis in a Centrifugal Pump Application using Structural Analysis.” [Google Scholar]
- D. Siano and M. A. Panza, “Diagnostic method by using vibration analysis for pump fault detection,” Energy Procedia, vol. 148, no. Ati, pp. 10–17, 2018, doi: 10.1016/j.egypro.2018.08.013. [CrossRef] [Google Scholar]
- G. Betta, M. D’Apuzzo, C. Liguori, and A. Pietrosanto, “An intelligent FFT-Analyzer,” IEEE Trans Instrum Meas, vol. 47, no. 5, pp. 1173–1179, 1998, doi: 10.1109/19.746578. [CrossRef] [Google Scholar]
- M. H. Mohd Ghazali and W. Rahiman, “Vibration Analysis for Machine Monitoring and Diagnosis: A Systematic Review,” Shock and Vibration, vol. 2021, 2021, doi: 10.1155/2021/9469318. [CrossRef] [Google Scholar]
- M. Vishwakarma, R. Purohit, V. Harshlata, and P. Rajput, “Vibration Analysis & Condition Monitoring for Rotating Machines: A Review,” in Materials Today: Proceedings, Elsevier Ltd, 2017, pp. 2659–2664. doi: 10.1016/j.matpr.2017.02.140. [CrossRef] [Google Scholar]
- M. Vishwakarma, R. Purohit, V. Harshlata, and P. Rajput, “Vibration Analysis & Condition Monitoring for Rotating Machines: A Review,” Mater Today Proc, vol. 4, no. 2, pp. 2659–2664, 2017, doi: 10.1016/j.matpr.2017.02.140. [CrossRef] [Google Scholar]
- S. Chatterton, P. Borghesani, P. Pennacchi, and A. Vania, “Monitoring of the damage in rolling element bearings,” in Mechanisms and Machine Science, Kluwer Academic Publishers, 2015, pp. 977–986. doi: 10.1007/978-3-319-09918-7_86. [CrossRef] [Google Scholar]
- S. Rajakarunakaran, P. Venkumar, D. Devaraj, and K. S. P. Rao, “Artificial neural network approach for fault detection in rotary system,” Applied Soft Computing Journal, vol. 8, no. 1, pp. 740–748, 2008, doi: 10.1016/j.asoc.2007.06.002. [CrossRef] [Google Scholar]
- Siano, D., & Panza, M. A. (2018). Diagnostic method by using vibration analysis for pump fault detection. Energy Procedia, 148(Ati), 10–17 [CrossRef] [Google Scholar]
- Wheeler, W. H., & Wheeler, W. H. (2014). The Centrifugal Pump. The Drainage of Fens and Low Lands, 92–105. [Google Scholar]
- Zhang, N., Yang, M. G., Gao, B., & Li, Z. (2015). Investigation on vibration characteristics in a centrifugal pump with special slope volute. Advances in Mechanical Engineering, 7(2). [Google Scholar]
- Jijian, L., Xiuwei, Y., Haijun, W., (2023). Propagation characteristics analysis of high-frequency vibration in pumped storage power station based on a 1D fluid-solid coupling model. Journal of Energy Storage, Volume 68. [Google Scholar]
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