%0 Journal Article
%T Characterization of cavitation and seal damage during pump operation by vibration and motor current signal spectra
%A Hui Sun
%A Shouqi Yuan
%A Yin Luo
%J Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy
%@ 2041-2967
%D 2019
%R 10.1177/0957650918769761
%X Cyclic spectral analysis is conducted to extract the frequency characteristic components from nonstationary current signals under cavitation and seal damage conditions as indicators of fault characterization. Specifically, vibration and current signals are both acquired and pre-processed by envelope extraction and singular value decomposition methods, respectively. Since there are more noise waves in vibration power spectral density spectra in comparison with current signals, the cyclic spectral analysis is conducted for the current signal analysis. Cyclic autocorrelation functions of signals are firstly calculated then corresponding slices are extracted from the cyclic autocorrelation functions and processed by fast Fourier transform method. Consequently from the spectra, indicators for characterization are extracted to demonstrate the occurrence and severity of faults. Results show that the rotating frequency component shows obvious tendency as the flow rate deviates from the designed point without any faults. The indicators for seal damage characterization are 250£¿Hz and 350£¿Hz frequency components related with rotating frequency and blade passing frequency in the current signals. Meanwhile, the occurrence and development status of cavitation are indicated by the frequency component of 100£¿Hz in the slice spectra of cyclic autocorrelation functions. Additionally, the effect of instability caused by off-design, seal damage, as well as cavitation operation conditions is distinguished by cyclic spectral analysis. Characteristic components are innovatively extracted at specific frequencies to avoid the effect from modulated and noise components in the current signals. And the results about the recognition of different types of faults could provide important evidences for fault detection during pump operation
%K Pumps
%K cavitation
%K seal damage
%K fault characterization
%K spectral analysis
%U https://journals.sagepub.com/doi/full/10.1177/0957650918769761