该文采用Hilbert-Huang变换(HHT)对时变阻尼自由振动系统以及常见的Duffing振动系统和Van der Pol振动系统进行参数识别。首先通过经验模态分解将振动信号分解为自由振动信号和强迫振动信号,通过经验包络法得到分解后信号的振幅包络线...该文采用Hilbert-Huang变换(HHT)对时变阻尼自由振动系统以及常见的Duffing振动系统和Van der Pol振动系统进行参数识别。首先通过经验模态分解将振动信号分解为自由振动信号和强迫振动信号,通过经验包络法得到分解后信号的振幅包络线和瞬时频率。进而使用瞬时振幅及瞬时频率通过最小二乘法估计得到振动方程的各项参数。与小波识别结果进行对比,数值算例表明Hilbert-Huang变换可以有效地识别时变阻尼自由振动以及Duffing振动系统和Van der Pol振动系统的时变参数并且有较高精度。展开更多
Nonlinear lumped-parameter force factor Bl(x), stiffness Kms(x) and inductance Le(x) of electrodynamic loudspeakers change frequency responses and generate some nonlinear effects for large stimulus: harmonic and inter...Nonlinear lumped-parameter force factor Bl(x), stiffness Kms(x) and inductance Le(x) of electrodynamic loudspeakers change frequency responses and generate some nonlinear effects for large stimulus: harmonic and intermodulation distortion, DC component in diaphragm displacement, instability of vibration and jumping effects. By modeling the nonlinear system under large-signal conditions, relationship between the nonlinear parameters and large-signal behavior can be revealed and help to provide guidance to diagnose loudspeakers. Agreement between the measured and predicted responses of a real loudspeaker validates the modeling and enables new methods for loudspeaker diagnosis.展开更多
文摘该文采用Hilbert-Huang变换(HHT)对时变阻尼自由振动系统以及常见的Duffing振动系统和Van der Pol振动系统进行参数识别。首先通过经验模态分解将振动信号分解为自由振动信号和强迫振动信号,通过经验包络法得到分解后信号的振幅包络线和瞬时频率。进而使用瞬时振幅及瞬时频率通过最小二乘法估计得到振动方程的各项参数。与小波识别结果进行对比,数值算例表明Hilbert-Huang变换可以有效地识别时变阻尼自由振动以及Duffing振动系统和Van der Pol振动系统的时变参数并且有较高精度。
基金supported by the National Natural Science Foundation of China(Grant No. 11274172)
文摘Nonlinear lumped-parameter force factor Bl(x), stiffness Kms(x) and inductance Le(x) of electrodynamic loudspeakers change frequency responses and generate some nonlinear effects for large stimulus: harmonic and intermodulation distortion, DC component in diaphragm displacement, instability of vibration and jumping effects. By modeling the nonlinear system under large-signal conditions, relationship between the nonlinear parameters and large-signal behavior can be revealed and help to provide guidance to diagnose loudspeakers. Agreement between the measured and predicted responses of a real loudspeaker validates the modeling and enables new methods for loudspeaker diagnosis.
