The week's pick
Reseach Article
Classification of Vibration Signal to Detect Pump Cavitation using Discrete Wavelet Transform
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 93 - Number 10 |
| Year of Publication: 2014 |
| Authors: Ramadevi. R |
10.5120/16254-5864
|
Ramadevi. R . Classification of Vibration Signal to Detect Pump Cavitation using Discrete Wavelet Transform. International Journal of Computer Applications. 93, 10 ( May 2014), 36-39. DOI=10.5120/16254-5864
Abstract
This paper concentrates on cavitation detection using discrete wavelet transform by classifying the pump vibration signal. Vibration signal acquired from centrifugal pump cavitation test rig carry more information about the cavitation classes. In this paper two classes has been defined namely, no cavitation class and developed cavitation class. This method uses the deviation from zero mean value of detailed components of wavelet coefficients, obtained from five level decomposition of vibration signal to detect the signal belongs to normal class or cavitation class in centrifugal pump. The main advantage of this proposed algorithm is it requires no training. In addition to this advantage a more robust results show that this algorithm has better detection response.
References
- Roggers R. S. and Moore R. D. (1969), "Method for Prediction of Pump Cavitation Performance for Various Liquids, Liquid Temperatures, and Rotative Speeds", NASA TN D-5292, NASA Scientific and Technical Publications, Lewis Research Centre, Cleveland, Ohio.
- Saeid Farokhzad, Naeim Bakhtyari, Hojjat Ahmadi,"Vibration Signals Analysis and Condition Monitoring of Centrifugal Pump", Technical Journal of Engineering and Applied Sciences, pp 1081 – 1085, Vol. 3, No. 12, 2013.
- Bruno Schiavello and Frank C. Visser (2009), "Pump Cavitation – Various NPSHR Criteria, NPSHA Margins, and Impeller Life Efficiency", Proceedings of the Twenty-Fifth International Pump Users Symposium, 23 – 26th Feb 2009, Houston, Texas, USA, pp. 113-144.
- Huaqing Wang, Peng Chen " Sequential Condition Diagnosis for centrifugal pump system using Fuzzy Neural Network", Neural Information Processing – Letters and Reviews, Vol11, No. 3, March 2007.
- H. Q. Wang, P. Chen " Fault Diagnosis of Centrifugal Pump using Symptom Parameters in frequency Domain" Agricultural Engineering International:the CIGR Ejournal, Vol. IX, Nov 2007.
- Guillermo Palacios J. , Ramon Beltran and Raquel Lacuesta (2005), "Multi resolution Approaches for Edge Detection and Classification based on Discrete Wavelet Transform", Discrete Wavelet Transforms: Algorithms and Applications", pp. 81-100.
- Yasaman Zandi Mehran, "New Application of Wavelet Transform in Classification the Arterial Pulse Signals, Proceedings of the 5th WSEAS international Conference on system science and simulation in Engineering, Spain, Dec 2006, pp448 – 453.
- Henrique Mohallem Paiva, Roberto Kawakami Harrop Galvao, Luis Rodrigues " A Wavelet based Multivariable Approach for fault detection in dynamic systems", Sba Controle & Automacao, Vol. 20, No. 4 Natal Oct / Dec 2009.
- ZHOU Hongbin, LI Hui " Diagnosis of preliminary cavitation in pumps by wavelet analysis" Energy Resource and Power Engineering, 2010, pp 394 – 398.
- GaoY. and Ron J Patton (2003), "Applications of Wavelet Analysis for Performance monitoring and Diagnosis of a Hydraulic Pump", 5th IFAC symposium on Fault Detection, Supervision and Safety of Technical Processes, Washington, USA, pp. 333 - 338.
- Juan Jose Gonzalez de la Rosa, Lloret I. , Moreno A. , Puntonet C. G. and Gorriz J. M. (2006), "Wavelets and Wavelet Packets Applied to Detect and Characterize Transient Alarm Signals from Termites", Elsevier, Measurement, Vol. 39, pp. 553-564.
- Mukesh Sahdev (2010), "Centrifugal Pumps: Basic Concepts of Operation, Maintenance and Trouble Shooting, Part II", The Chemical Engineering's Resource Page, WWW. Chersources. com .
- Paul S Addison (2005), "Wavelet Transforms and the ECG: a review", Institute of Physics Publishing Physiological Measurement 26, pp. R155– R199.
- Emily K. Lada, Jye – Chyi (JC) Lu, James R. Wilson "A Wavelet based procedure for process Fault Detection," IEEE Transactions on Semi Conductor Manufacturing , pp 1 – 31.
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