Centrifugal pump impeller defect identification by processing vibration signal

In the field of machine diagnosis, the utilization of vibration signals is effective in the detection of fault, because the signals carry dynamic information about the machine state. This paper presents a diagnosis method for a centrifugal pump using features of vibration signals. Monoblock centrifugal pumps are employed in a variety of critical engineering applications. Continuous monitoring of such machine component becomes essential in order to reduce the unnecessary break downs. At the outset, vibration based approaches are widely used to carry out condition monitoring tasks, but not too much in the field of centrifugal pumps.

Aiming at the non-stationary and non-linearity characteristics of the vibration signals of centrifugal pump, a new method based on complexity feature of Wavelet Decomposition Technique (WDT) and envelope is put forward. First of all, raw signal is recorded using the data acquisition card (DAQ) then with the help of LabView programming the raw signal is decomposed using WDT sym5 up to five levels and then the complexity features of each level is extracted. The extracted information is tabulated so that features can be compared with the others levels of the decomposed raw signals. Here kurtosis criterion is employed for further diagnosis. On the basis of the kurtosis criterion envelope is imposed on that level, which is having the highest kurtosis value. After applying the WDT and envelope the result of the different cases is validated.