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基于参数优化变分模态分解的瞬时模态参数识别

Instantaneous modal parameter identification based on parameter optimized variational mode decomposition
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摘要 针对变分模态分解的模态数和二次惩罚因子难以确定的问题,提出了基于正交性指标、能量比值和变分能量熵的参数优化算法;对于分解得到的单分量信号,发展了基于多项式调频小波变换的瞬时频率识别方法和基于能量法的瞬时阻尼比识别方法。开展了三自由度时变结构仿真研究和时变钢梁实验研究。研究结果表明:优化后的变分模态分解法能够精确分离多自由系统的各阶时变分量,具有较强的抗噪性能;基于多项式调频小波变换的瞬时频率识别方法具有很强的时变频率追踪性能、抗噪声能力强,时变频率识别精度高,平均误差不超过1%;能量法能够较准确地识别结构的瞬时阻尼比,识别误差保持在10%左右,抗噪优势明显。 In view of the problem of determining the modal number and quadratic penalty factor of variational mode decomposition(VMD),a parameter optimization algorithm based on orthogonality index,energy ratio and variational energy entropy(VEE)was proposed.For the decomposed single component signal,the instantaneous frequency identification method based on polynomial chirplet transform(PCT)and the instantaneous damping ratio identification method based on energy method were developed.The simulation research of 3-DOF(degree of freedom)time-varying structure and the experimental research of time-varying steel beam were carried out.The results showed that the optimized VMD method can accurately separate the time-varying components of the multi-DOF system with strong anti-noise performance.The instantaneous frequency identification method based on PCT had strong time-varying frequency tracking performance,strong anti-noise ability,and high accuracy of time-varying frequency identification,and the average error was less than 1%.The energy method can accurately identify the instantaneous damping ratio of the structure with obvious anti-noise advantage,and the identification error was maintained at about 10%.
作者 陈祥祥 史治宇 赵宗爽 CHEN Xiangxiang;SHI Zhiyu;ZHAO Zongshuang(State Key Laboratory of Mechanics and Control of Mechanical Structures,College of Aerospace Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Shanghai Aircraft Manufacturing Company,Limited,Commercial Aircraft Corporation of China,Limited,Shanghai 201324,China)
出处 《航空动力学报》 EI CAS CSCD 北大核心 2024年第4期143-150,共8页 Journal of Aerospace Power
基金 国家自然科学基金(12272172)。
关键词 模态参数识别 参数优化 变分能量熵 变分模态分解 多项式调频小波变换 能量法 modal parameter identification parameter optimization variational energy entropy variational mode decomposition polynomial chirplet transform energy method
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