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| Feature extraction of cavitation acoustic emission signal of centrifugal pump based on improved variational mode decomposition |
| LIU Zhong*, ZHANG Xuyang, ZOU Shuyun, LI Zhipeng |
| School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha, Hunan 410114, China |
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Abstract Aiming at the problem that the decomposition layer and penalty factor in the variational mode decomposition(VMD)algorithm are difficult to be determined, an improved VMD(IVMD)algorithm was proposed and applied to extract the feature of cavitation acoustic emission(AE)signal of centrifugal pump. In the application of IVMD algorithm, first, the envelope entropy diffe-rence coefficient was used to determine the number of decomposition layers, and then the artificial bee colony algorithm was used to optimize the penalty factor which was employed as the optimum input parameter of VMD. The simulated signal was processed via IVMD algorithm, and the results were compared with those by ensemble empirical mode decomposition. AE signals collected from the inlet of centrifugal pump under 60% of its rating flow were chosen and processed via the IVMD algorithm. The frequency domain features of those signal components carrying a great deal of information in the original signals were analyzed, and so was the variation of their absolute energy with changing cavitation stages. The results show that the number of decomposition layers and the penalty factor could be determined optimally via the IVMD algorithm, which helps to decompose the unstable signals adaptively. The cha-racteristic frequency ranges of AE signal focus on 50, 100 kHz and their respective vicinities. With cavitation changing from scratch and from weak to strong, the absolute energies of AE signal components in the above frequency ranges remain at a certain level first, then decrease, and finally increase.
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Received: 21 August 2019
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