Abstract
Cavitation is a major problem facing centrifugal pumps in industry today. Unable to constantly maintain operating conditions around the best efficiency point, centrifugal pumps are subject to conditions that may lead to vaporisation or flashing in the pipes upstream of the pump. The implosion of these vapour bubbles in the impeller or volute causes damaging effects to the pump. A new method of cavitation detection is proposed in this paper based on spectral methods. Data used to determine parameters were obtained under ideal conditions, while the method was tested using industry acquired data. Results were compared to knowledge known about the state of the pump, and the classification of the pump according to ISO 10816.
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Abdi H, Williams LJ (2010) Principal component analysis. Wiley Interdiscip Rev Comput Stat 2(4):433–459. doi:10.1002/wics.101
Amirat Y, Benbouzid MEH, Al-Ahmar E, Bensaker B, Turri S (2009) A brief status on condition monitoring and fault diagnosis in wind energy conversion systems. Renew Sustain Energy Rev 13(9):2629–2636. doi:http://dx.doi.org/10.1016/j.rser.2009.06.031
Bin L, Yaoyu L, Xin W, Yang Z (2009) A review of recent advances in wind turbine condition monitoring and fault diagnosis. In: Power Electronics and Machines in Wind Applications, PEMWA 24–26 June, 2009. IEEE, pp 1–7. doi:10.1109/pemwa.2009.5208325
Hameed Z, Hong YS, Cho YM, Ahn SH, Song CK (2009) Condition monitoring and fault detection of wind turbines and related algorithms: A review. Renew Sustain Energy Rev 13(1):1–39. doi:http://dx.doi.org/10.1016/j.rser.2007.05.008
Klema J, Flek O, Kout J, Novakova L (2005) Intelligent diagnosis and learning in centrifugal pumps. In: Emerging solutions for future manufacturing systems. Springer, New York, pp 513–522
McKee K, Forbes G, Mazhar I, Entwistle R, Howard I (2013) A review of machinery diagnostics and prognostics implemented on a centrifugal pump. In: Jay Lee JN, Jag Sarangapani, Joseph Mathew (ed) Proceedings of the 6th World Congress on Engineering Asset Management, Springer, Cincinnati, OH, USA, Oct 2 2011
McKee KK, Forbes G, Mazhar I, Entwistle R, Howard I (2012a) Modification of the ISO-10816 centrifugal pump vibration severity charts for use with Octave band spectral measurements. In: 7th Australasian Congress on Applied Mechanics, Adelaide, SA, Dec 9–12 2012. Engineers Australia, pp 276–283
McKee KK, Forbes G, Mazhar I, Entwistle R, Hodkiewicz M, Howard I (2012b) A single cavitation indicator based on statistical parameters for a centrifugal pump. In: World Congress on Engineering Asset Management, Daejon, South Korea
Palgrave R (2005) Centrifugal pump basics. World Pumps 2005(460):37–39
Peck JP (1994) On-line condition monitoring of rotating equipment using neural networks. ISA Trans 33(2):159–164
Rayner R (1995) Pump users handbook. Elsevier Advanced Technology Oxford
Rencher AC, Christensen WF (2012) Principal component analysis. In: Methods of multivariate analysis. Wiley, West Sussex, pp 405–433. doi:10.1002/9781118391686.ch12
Standardization IOf (1975) ISO 532: Method for calculating loudness level. International Organization for Standardization, Switzerland
Standardization IOf (1998) ISO 10816-3: Mechanical vibration—Evaluation of machine vibration by measurements on non-rotating parts—Part 3: Industrial machines with nominal power above 15 kW and nominal speeds between 120 r/min and 15,000 r/min when measured in situ ISO, Switzerland
Standardization IOf (2009) ISO 10816-7: Mechanical vibration-Evaluation of machine vibration by measurements on non-rotating parts. Part 7: Rotodynamic pumps for industrial applications, including measurements on rotating shafts. ISO, Switzerland
Wang H (2010) Intelligent diagnosis methods for plant machinery. Front Mech Eng China 5(1):118–124
Wang H, Chen P (2007) Sequential condition diagnosis for centrifugal pump system using fuzzy neural network. Neural Inf Process Lett Rev 11(3):41–50
Wang H, Chen P (2009) Intelligent diagnosis method for a centrifugal pump using features of vibration signals. Neural Comput Appl 18(4):397–405. doi:10.1007/s00521-008-0192-4
Wang Y, Liu Hou L, Yuan Shou Q, Tan Ming G, Wang K (2009) Prediction research on cavitation performance for centrifugal pumps. In: IEEE International Conference on Intelligent Computing and Intelligent Systems, ICIS 20–22 Nov 2009, pp 137–140. doi:10.1109/icicisys.2009.5357921
Wenxian Y, Tavner PJ, Crabtree CJ, Wilkinson M (2010) Cost-effective condition monitoring for wind turbines. IEEE Trans Indust Electr 57(1):263–271. doi:10.1109/tie.2009.2032202
Wold S, Esbensen K, Geladi P (1987) Principal component analysis. Chemom Intell Lab Syst 2(1–3):37–52. doi:http://dx.doi.org/10.1016/0169-7439(87)80084-9
Zouari R, Sieg-Zieba S, Sidahmed M (2004) Fault detection system for centrifugal pumps using neural networks and neuro-fuzzy techniques. In: Paper presented at the Surveillance 5 CETIM Senlis 11–13 Oct 2004
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McKee, K.K., Forbes, G., Mazhar, I., Entwistle, R., Hodkiewicz, M., Howard, I. (2015). Cavitation Sensitivity Parameter Analysis for Centrifugal Pumps Based on Spectral Methods. In: Tse, P., Mathew, J., Wong, K., Lam, R., Ko, C. (eds) Engineering Asset Management - Systems, Professional Practices and Certification. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-09507-3_8
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DOI: https://doi.org/10.1007/978-3-319-09507-3_8
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