【摘要】 传统的的设备模态参数提取多是建立在频谱计算的基础上,提取精度受采样频率和时域截断产生的能量泄漏的影响较大。为此,提出了一种基于信号匹配追踪的模态参数提取方法,该方法将Laplace小波作为信号匹配追踪的基元函数;同时引入粒子群算法来实现Laplace小波的参数寻优,克服了传统算法计算复杂的缺点。仿真和实际应用表明,该方法可有效地提取设备的模态参数;且比传统的半功率带宽法具有更高的精度。更多还原

【Abstract】 Conventional method of modal parameters extraction is based on frequency spectrum,sampling frequency of signal and power leakage caused by truncation in time domain have a strong effect on the precision of the extraction.A new method of modal parameters extraction based on signal matching pursuit is presented.Because of similarity between the real part of Laplace wavelet and the impulse response function,the real part of Laplace wavelet is employed for construction of elementary function library,in the meantime,particle swarm optimizer is applied to optimize parameters of Laplace wavelet.It overcomes shortcomings of conventional computation algorithm.Simulation results and applications show that the new method can effectively extract modal parameters of equipments and possess better precision than that of classical method based on half power band.更多还原