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基于VMD的某涡轴发动机转子振动信号分析

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针对涡轴发动机转子振动特性,提出遗传算法优化的VMD方法.以VMD分量信息熵最小化为适应度函数,运用遗传算法优化VMD分量数量和惩罚因子,并采用仿真案例验证了方法的有效性.基于某涡轴发动机转子振动倍频幅值包络线、试车转速曲线,仿真进气机匣、涡轮机匣的振动信号,并采用优化的VMD对振动信号进行分解,对分解后的信号进行整周期重采样后再进行频谱分析.结合瀑布图对比分析原信号和VMD分解信号,同时以试车第100s时刻的频谱图进行分析.分析结果表明:遗传算法优化的VMD能够有效地对转子振动信号进行分析,且能够识别出各转子的主要倍频成分.
Analysis of Turbo-Shaft Engine Rotor Vibration Signal Based on VMD
Aiming at the analysis of the rotor vibration characteristics of turbo-shaft engine,a genetic algorithm(GA)optimized variational mode decomposition(VMD)is proposed.GA is used to optimize the number of VMD components and the penalty fac-tor by minimizing the information entropy of VMD components signal.And a simulation case is used to verify the effectiveness of method.The vibration signal of the intake casing and turbine casing is simulated based on frequency-doubled envelope curve and rotor speed curve of the turbo-shaft engine rotor vibration signal.The intake casing and turbine casing vibration signal is decom-posed by optimized VMD,which is full period synchronous re-sampling and then spectrum analysis is performed.Combine the wa-terfall chart to compare and analyze the original signal and the VMD decomposition signal,and analyze the spectrum at the 100th second of the test run.The results show that the VMD optimized by the genetic algorithm can effectively analyze the rotor vi-bration signal,and its component signal can identify the main frequency multiplication components of each rotor.

Turbo-Shaft EngineVMDRotor VibrationGenetic Algorithm

翟欢乐、黄磊

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江苏航空职业技术学院航空工程学院,江苏 镇江 212134

涡轴发动机 VMD 转子振动信号 遗传算法

2020年度江苏航空职业技术学院院级课题资助项目

JATC20010112

2024

机械设计与制造
辽宁省机械研究院

机械设计与制造

CSTPCD北大核心
影响因子:0.511
ISSN:1001-3997
年,卷(期):2024.(3)
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