自适应滤波算法在微弱振动测量中的应用

将递归最小二乘自适应滤波算法应用于激光多普勒测振技术中,搭建了相应的微弱振动测量装置。模拟仿真与实验中,通过与设计的切比雪夫低通滤波算法对比,结果表明:该递归最小二乘自适应滤波算法能够有效抑制随机高斯白噪声,还原出原始信号;能够对简谐振动信号实现有效滤波,并且可以还原出淹没在噪声中的低频20 Hz信号;文中算法可以去除语音噪声,使声音更加纯净,增强语音信号,以此验证了该算法在外差振动测量中的可行性。该算法简单易用、收敛性强、速度快,尤其对于随机噪声的去除比普通的低通滤波器更加有效。

Application of adaptive filtering algorithm in the weak vibration measurement

The adaptive filtering algorithm based on recursive least square algorithm was applied to a laser Doppler vibrometer and the corresponding weak vibration measuring devices were built up. Compared with Chebyshev low-pass filtering algorithm, simulation and experimental results show that this adaptive filtering algorithm can suppress the random Gaussian white noise and restore the original signal; the RLS algorithm can effectively filter out noise from the vibration signal, and restore the low-frequency 20 Hz signal drowned out in the noise; the RLS algorithm also can filter out noise from voice leading voice to being pure and enhance speech signal. The above verifies the feasibility of this algorithm in the heterodyne vibration measurement. The algorithm is simple and easy to use, fast and has strong convergence. In the aspect of filtering random noise, the RLS algorithm is more effective than low-pass filter.