Condition Monitoring and Pumps

Author:

Ali Saud Al Tobi Maamar1,Bevan Geraint2

Affiliation:

1. National University of Science and Technology Assistant Professor, , Muscat, Oman

2. Glasgow Caledonian University Senior Lecturer, , United Kingdom

Abstract

This chapter reviews and discusses previous work on the areas of rotating machinery and centrifugal pump fault diagnosis methods including conventional and automatic ones and those that apply artificial intelligence. Furthermore, critical discussion is provided based on the advantages and disadvantages of the applied feature processing, extraction, and selection methods. Finally, limitations of existing methods are identified.

Publisher

AIP Publishing LLCMelville, New York

Reference54 articles.

1. Abdulkarem, W., Amuthakkannan, R., and Al-Raheem, K. F., “Centrifugal pump impeller crack detection using vibration analysis,” in 2nd International Conference on Research in Science, Engineering and Technology, Dubai, UAE (ICARSET, 2014).10.15242/IIE.E0314606

2. Vibration analysis techniques for gearbox diagnostic: A review;Aherwar;Int. J. Adv. Eng. Technol.,2012

3. Diagnosis of centrifugal pump faults using vibration methods;Al-Braik;J. Phys.: Conf. Ser.,2012

4. Al-Braik, A., Hamomd, O., Gu, F., and Ball, A. D., “Diagnosis of impeller faults in a centrifugal pump based on spectrum analysis of vibration signals,” in Eleventh International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, Manchester, UK (British Institute of Non-Destructive Testing, 2014), Vol. 10.

5. Rolling bearing fault diagnostics using artificial neural networks based on Laplace wavelet analysis;Al-Raheem;Int. J. Eng. Sci. Technol.,2010

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