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Pressure fluctuation signal analysis of pump based on ensemble empirical mode decomposition method 被引量:3

Pressure fluctuation signal analysis of pump based on ensemble empirical mode decomposition method
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摘要 Pressure fluctuations, which are inevitable in the operation of pumps, have a strong non-stationary characteristic and contain a great deal of important information representing the operation conditions. With an axial-flow pump as an example, a new method for time-frequency analysis based on the ensemble empirical mode decomposition (EEMD) method is proposed for research on the characteristics of pressure fluctuations. First, the pressure fluctuation signals are preprocessed with the empirical mode decomposition (EMD) method, and intrinsic mode functions (IMFs) are extracted. Second, the EEMD method is used to extract more precise decomposition results, and the number of iterations is determined according to the number of IMFs produced by the EMD method. Third, correlation coefficients between IMFs produced by the EMD and EEMD methods and the original signal are calculated, and the most sensitive IMFs are chosen to analyze the frequency spectrum. Finally, the operation conditions of the pump are identified with the frequency features. The results show that, compared with the EMD method, the EEMD method can improve the time-frequency resolution and extract main vibration components from pressure fluctuation signals. Pressure fluctuations, which are inevitable in the operation of pumps, have a strong non-stationary characteristic and contain a great deal of important information representing the operation conditions. With an axial-flow pump as an example, a new method for time-frequency analysis based on the ensemble empirical mode decomposition (EEMD) method is proposed for research on the characteristics of pressure fluctuations. First, the pressure fluctuation signals are preprocessed with the empirical mode decomposition (EMD) method, and intrinsic mode functions (IMFs) are extracted. Second, the EEMD method is used to extract more precise decomposition results, and the number of iterations is determined according to the number of IMFs produced by the EMD method. Third, correlation coefficients between IMFs produced by the EMD and EEMD methods and the original signal are calculated, and the most sensitive IMFs are chosen to analyze the frequency spectrum. Finally, the operation conditions of the pump are identified with the frequency features. The results show that, compared with the EMD method, the EEMD method can improve the time-frequency resolution and extract main vibration components from pressure fluctuation signals.
出处 《Water Science and Engineering》 EI CAS CSCD 2014年第2期227-235,共9页 水科学与水工程(英文版)
基金 supported by the National Natural Science Foundation of China(Grant No.51076041) the Fundamental Research Funds for the Central Universities(Grant No.2010B25114) the Natural Science Foundation of Hohai University(Grant No.2009422111)
关键词 pressure fluctuation ensemble empirical mode decomposition intrinsic modefunction correlation coefficient pressure fluctuation ensemble empirical mode decomposition intrinsic modefunction correlation coefficient
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