Analysis of Aeroengine Vibration Signal

Authors

Pi Jun, 1. College of General Aviation, Civil Aviation University of China, Tianjin 300300, China;;
Jiaze Chang, 2. Sino-European Institute of Aviation Engineering, Civil Aviation University of China, Tianjin 300300, China;
Guangcai Liu, 1. College of General Aviation, Civil Aviation University of China, Tianjin 300300, China;;

Abstract

Abstract: Aiming at the analysis of the vibration characteristics of aeroengine rotor, an improved blind source separation algorithm based on cumulant independent component analysis (ICA) is proposed. The new algorithm is used to separate the rotor vibration signal and identify the rotor fault types. The effectiveness of this algorithm is verified by the aeroengine rotor vibration signal simulation. Comparing with the existing algorithms based on second-order cumulants and high-order cumulants, the new method improves the performance index and the signal similarity coefficient. This algorithm is used to separate the vibration signal collected by the engine rotor platform and the rotor fault is set as the outer ring fault. The vibration signal measured by this algorithm has a higher recognition, and the fault types of rotor vibration can be identified.

Recommended Citation

Jun, Pi; Chang, Jiaze; and Liu, Guangcai (2020) "Analysis of Aeroengine Vibration Signal," Journal of System Simulation: Vol. 32: Iss. 3, Article 21.
DOI: 10.16182/j.issn1004731x.joss.18-0216
Available at: https://dc-china-simulation.researchcommons.org/journal/vol32/iss3/21

First Page

525

Revised Date

2018-11-08

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.18-0216

Last Page

532

CLC

TP391.9

Recommended Citation

Pi Jun, Chang Jiaze, Liu Guangcai. Analysis of Aeroengine Vibration Signal[J]. Journal of System Simulation, 2020, 32(3): 525-532.

DOI

10.16182/j.issn1004731x.joss.18-0216