# Selection Strategy of Vibration Feature Target under Centrifugal Pumps Cavitation
###### Abstract  
The cavitation states among centrifugal pumps can be mirrored by corresponding vibration features. To select the vibration feature target scientifically and objectively for monitor the cavitation states in real time, the analysis method of grey slope correlation with weight entropy was proposed in this paper to explore the relevance between cavitation and vibration features. Thus, the net positive suction head (NPSH) and vibration signal from centrifugal pumps under multiple operation conditions were captured. Moreover, the universal feature targets were extracted from the vibration signal. The grey slope correlation method was applied in the analysis of the positive and negative relevance between NPSH and the multiple operation conditions in a different stage. These feature targets are transformed into the same numerical scale by standardization process. In the end, the final comprehensive coefficient can be attached after endowing power by weight entropy method. These methods can be used to determine the feature targets which have intensive relevance with NPSH. The analysis results indicate that the kurtosis factor, variance, absolute mean, and root mean square obtained from the vibration acceleration signal have stable relevance with NPSH. These feature targets can be used for the proper detection and evaluation of cavitation states in centrifugal pumps. Therefore, the analysis method of grey slope correlation with weight entropy can be used to pre-select the feature targets based on the calculated grey incidence. This method is effective in establishing the relevance between NPSH and vibration. c 2020  
the running of analysis code enable the scholar to pay more attention in digging valuable results from vast amount of data. Currently available results indicated that the suction pressure difference might change the pump vibration states [7; 8; 9], although this sort of vibration feature has a different appearance in different working flow rates [10; 11; 12; 13; 14; 15; 16]. However, cavitation can be defined as the rupture of a liquid due to a pressure drop [17]. It can be identified by vibration feature due to bubble burst. In these cited works of signal process, the feature target is a key element which should be considered and determined. Thus, root mean square (RMS) might be the most popular and universal parameter since it can be extracted from a historical vibration signal and reflect the cavitation occurrence. For instance, [PERSON] et al. [18] and [PERSON] et al. [19] selected the concept of energy developed from the RMS to establish the potential variation caused by suction pressure and working flow rates. Similarly, to acquire the situations in different net positive suction head (NPSH), the RMS of acceleration in different monitor points displaced on the pump was captured to mirror the cavitation states [20]. Moreover, the parameters like the mean, variance, standard deviation, skewness, kurtosis, and crest factor were also used to carry out this kind of work [21]. In the literature [22], empirical mode decomposition (EMD) method with these parameters was used to decompose original signals into a number of intrinsic mode functions (IMFs). In the process of diagnosing the flow instabilities [23], the most troubling and confusion things were that different feature target selection might disturb the evaluation while the pump is working in the cavitation or air injection mode. The result points out the fact that the feature target might have different sensitivity under various circumstances. As mentioned in the first part, all the feature target selections were based on perceptual cognizance and personal experience. The details of strict mathematical explanation about why these targets can be used to evaluate the vibration manner were not adequately captured in the literature.