Estimating Low-Bias Frequency Response Using Random Decrement

Abstract

It is well known that in order to minimize the influence of leakage bias in frequency response function (FRF) estimates, smooth windows should be applied in the FFT processing. It is also normal practice to use self windowing excitation signals whenever possible. However, in many cases FRFs have to be estimated on systems where the excitation signal cannot be altered. Since random data can be compressed in a random decrement function, and since this procedure introduces a natural window, using this technique significantly reduces the influence of leakage bias, and thus, can be used as an alternative to Welch based estimates in cases where the signals involved are random. This means that almost bias-free FRF estimates can be obtained from stationary random excitation. In the paper it is shown how the random decrement technique can be applied to process the time series, and the level of bias on the FRF is estimated and compared to normal Welch based FRF estimates.