Vibrational Stability Based on Autocorrelation Analysis of Translating Window Signals

doi:10.11885/j.issn.1674-5086.2018.03.26.02

Abstract

Abstract: Targeting the limitations of the current analysis methods for vibration signals of electric submersible pumps, an autocorrelation analysis method based on translating window signals is proposed, and a stability index is defined to evaluate the stability of the vibration signals quantitatively. First, a window signal that can best represent the periodic characteristics of the vibration signals is obtained using the moving average method. Subsequently, the window signal is translated on the vibration signals while autocorrelation analysis is performed to obtain the autocorrelation coefficient series. Finally, the autocorrelation coefficient series is processed to obtain the stability index. Simulation and experiment results show that this method can effectively judge whether the signal has an unstable vibration amplitude or period to determine the electric pump with potential fault successfully, which verifies the feasibility and effectiveness of the method in evaluating the stability of vibration signals.

Key words: electric submersible pump, window signal, autocorrelation coefficient series, stability index, vibrational stability

CLC Number:

TE933

LIU Guangfu, ZHOU Kaidi, ZHU He, FENG Lianlei, YAO Aijun. Vibrational Stability Based on Autocorrelation Analysis of Translating Window Signals[J]. 西南石油大学学报(自然科学版), 2019, 41(4): 166-174.

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URL: http://journal15.magtechjournal.com/Jwk_xnzk/EN/10.11885/j.issn.1674-5086.2018.03.26.02

http://journal15.magtechjournal.com/Jwk_xnzk/EN/Y2019/V41/I4/166

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