Centrifugal Pump Cavitation Detection Using Machine Learning Algorithm Technique

Abstract

Cavitation is one of the major disadvantages in pumping system, which enhance to form bubbles in the pipeline and it reduces the efficiency of the pump. So it should be identified and take the preventive measure. Machine Learning is a fast and computational method which can easily detect any faults in the pumping system. Still now lots of work has been done on a detection of fault in the pumping system, but mainly those work has done based on vibration details and variation of speed. The paper presents how by the help of machine learning algorithm by varying the speed and pressure cavitation can be identified. It is the comparative study between how the vibration and speed together affects the cavitation result and variation of speed and pressure affects the cavitation. Support Vector Machine is one of the classification methods in machine learning algorithm where it can be easily classified the cavitation problem. So this paper analyses how the method of SVM can more efficiently detect the cavitation problem with the centrifugal water pump.