振动台功率谱复现算法
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摘要
传统的振动控制技术将初始辨识的系统频率响应函数贯穿使用于振动控制的过程中;针对液压振动台系统的时变特性,提出使用基于最小均方误差(least mean square,简称LMS)的自适应算法在线辨识系统的频响函数。平滑周期图功率谱估计法相对现代谱估计法分辨率较低,提出自回归(auto-regressive,简称AR)模型法对振动系统响应信号进行功率谱估计,利用尤利-沃克(Yule-Walker)方程求解AR模型参数,并给出AR模型阶次确定的方法。利用自行开发的基于DSP和ARM多处理器信号处理系统对功率谱复现进行软硬件仿真。结果表明,此方法对振动台功率谱进行复现,复现精度优于传统功率谱复现算法。
The frequency response function(FRF) estimation of the shaking system is adopted without any modification in the traditional process of vibration test.For the time-variant characteristic of the vibration control system,an adaptive method of FRF estimation is described in this paper.This strategy adjustes the variation of the system in every control cycle,which is based on the least mean square(LMS) algorithm,and then improves the performance of shaking control system.The classical means based on the periodogram is lack of resolution to estimate the power spectrum density(PSD) of the response signal of the shaking table.A modern method for PSD estimation named auto-recursive(AR) model is introduced.The parameters of the AR model are solved by Yule-Walker equation,and the method to determine the orders of the AR model is also formed.The experiment is carried out using the signal processing platform constructed by DSPs and ARM,and the results show that the algorithm provided in this paper is suitable.
引文
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