CEEMD-LSTM-based diagnosis method for off-design working conditions of centrifugal pump

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Journal of Vibration and Shock ›› 2022, Vol. 41 ›› Issue (19) : 114-121.

LIU Rongwei1, HE Weiting2, WANG Linlin1, YANG Shuai1, WU Peng1, WU Dazhuan1

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Abstract

Centrifugal pumps are widely used in various industries and consume power heavily. When centrifugal pump operates under partial working conditions, the internal flow tends to be chaotic, resulting in a decline in efficiency and an increase in energy consumption. In this paper, according to weak variation and strong interference of vibration signals in off-working condition of centrifugal pump, two-channel information fusion and complementary set empirical mode decomposition(CEEMD) were adopted to extract the time-series features of vibration signals. Combined with the intelligent recognition of long-short time memory(LSTM) model, a diagnostic model was established for off-working condition of centrifugal pump. The simulation signals are compared with different preprocessing methods to highlight the feature extraction ability of CEEMD. The correlation is verified between working conditions and low-frequency vibration signals. The superiority of the model is further verified through comparative analysis of experimental data, and the test accuracy rate reaches 98.5%. This method can monitor the running condition of centrifugal pump and ensure the running efficiency.
Key words: Partial conditions; Empirical mode of complementary set; Long and short time memory model

Key words

Partial conditions / Empirical mode of complementary set / Long and short time memory model

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LIU Rongwei1, HE Weiting2, WANG Linlin1, YANG Shuai1, WU Peng1, WU Dazhuan1. CEEMD-LSTM-based diagnosis method for off-design working conditions of centrifugal pump[J]. Journal of Vibration and Shock, 2022, 41(19): 114-121

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