基于VMD的某涡轴发动机转子振动信号分析
Analysis of Turbo-Shaft Engine Rotor Vibration Signal Based on VMD
翟欢乐 1黄磊1
作者信息
- 1. 江苏航空职业技术学院航空工程学院,江苏 镇江 212134
- 折叠
摘要
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.
Abstract
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.
关键词
涡轴发动机/VMD/转子振动信号/遗传算法Key words
Turbo-Shaft Engine/VMD/Rotor Vibration/Genetic Algorithm引用本文复制引用
基金项目
2020年度江苏航空职业技术学院院级课题资助项目(JATC20010112)
出版年
2024
NETL
NSTL
万方数据