Numerical method to predict vibration characteristics induced by cavitation in centrifugal pumps

Vibration is a common side effect of cavitation in centrifugal pumps, which are also affected by other physical processes. Therefore, the study of cavitation based on raw vibration signals may introduce potential discrepancies under practical operating conditions. With the objective of accurately identifying the cavitation stages in a centrifugal pump, this study employs the wavelet packet transform (WPT) to process the original signal. Subsequently, the different vibration acceleration signals obtained by processing the raw signals using the proposed method under different working conditions are compared. The unequal interval weight grey (UIWG) model is proposed based on the measurements performed to reconstruct the functional relationship between cavitation and vibration, including in cases where the physical parameters of the research object are unavailable. The results reveal that the post-signal energy exhibits monotonic characteristics in certain frequency bands, despite the presence of interference under practical operating conditions. In addition, the UIWG model is verified to be robust as it is capable of self-correcting its monotonicity based on limited discrete data. In conclusion, the UIWG model equipped with WPT is an effective means to predict cavitation-induced vibrations.

Automated summary

This study utilizes wavelet packet transform to process original signals and establishes an unequal interval weight grey model to predict cavitation-induced vibrations in centrifugal pumps. Results show that post-signal energy exhibits monotonic characteristics in certain frequency bands under different working conditions, and the model demonstrates self-correction ability with limited data.