论文部分内容阅读
在振动试验台上进行多自由度(MDOF)随机振动激励时,传统的控制方法生成的驱动信号及试验台的响应信号都是高斯信号。但真实的振动干扰信号多是超高斯的;而相比于高斯激励,亚高斯激励可降低驱动信号的最大幅值。为实现多自由度亚高斯和超高斯振动控制,提出一种多自由度非高斯随机振动控制方法,该方法采用系统辨识解决系统耦合问题,而后通过选择特殊的相位生成非高斯伪随机驱动信号,再经过时域随机化得到真随机非高斯驱动信号。基于Hexapod平台的多自由度微振动试验台的亚高斯和超高斯实验表明,在试验台的响应功率谱(PSD)满足工程中常用的±3dB精度的同时,亚高斯驱动信号的最大幅值相比于高斯驱动信号的最大幅值降低了20%以上;超高斯响应信号的峭度与参考峭度的误差在0.2之内。实验结果验证了所提方法的有效性。
When a multi-degree-of-freedom (MDOF) random vibration excitation is performed on a vibration test rig, the drive signal generated by the conventional control method and the response signal of the test rig are Gaussian signals. However, the real vibration interference signals are mostly super-Gaussian; compared with Gaussian excitation, sub-Gaussian excitation can reduce the maximum amplitude of the driving signal. In order to realize multi-degree-of-freedom Gaussian and super-Gaussian vibration control, a multi-degree-of-freedom non-Gaussian random vibration control method is proposed, which uses system identification to solve the system coupling problem and then generates non-Gaussian pseudo-random drive signals by selecting special phases. After randomization in the time domain, a true random non-Gaussian driving signal is obtained. Sub-Gaussian and super-Gaussian experiments on a multi-degree-of-freedom micro-vibration test bed based on the Hexapod platform show that when the response power spectrum (PSD) of the test bench meets the accuracy of ± 3dB commonly used in engineering, the maximum amplitude of the sub-Gaussian drive signal Which is more than 20% lower than the maximum amplitude of the Gaussian drive signal. The error between the kurtosis of the Gaussian response signal and the reference kurtosis is within 0.2. The experimental results verify the effectiveness of the proposed method.