3/28/2023 0 Comments Scilab fft![]() ![]() A simple sine wave is shown below with these parameters identified. When analyzing vibration data in the time domain (acceleration/vibration amplitude plotted against time) we’re limited to a few parameters in quantifying the strength of a vibration profile: amplitude, peak-to-peak value, and RMS. Simple Vibration Analysis in the Time Domain You'll be doing your vibration analysis in the real world so we'll look at real world examples, and analyze data captured from an actual accelerometer.Īll data presented and the MATLAB scripts used to perform the vibration analysis are available to download so you can do your own vibration analysis. Let's go through the important differences between an FFT, PSD, and spectrogram and I'll try to illustrate when it is appropriate to use each type of vibration analysis tool. In order to effectively do your job of vibration analysis, you may be more interested in some practical information but it is important to understand a bit of the theory behind FFTs, PSDs and spectrograms. I'll provide an overview of the math behind the FFT, PSD and spectrogram (for more detail, check out our blog on Fourier Transforms) but I'll use plots to make my point instead of only equations and text.īy the end of the article you will be able to understand how to effectively utilize PSDs to quantify a vibration environment and have the tools to go out and calculate one for your own vibration testing! In this post I'll try to provide the right mix of theory and practical information, with examples, so that you can hopefully take your vibration analysis to the next level! And if you want an even deeper dive, check out our post Top 12 Vibration Metrics to Monitor & How to Calculate Them. Once you understand the basics they can really help with your vibration analysis. I did run the benchmarks for every program (Clean, Scilab, Yorick) 3 times to avoid outliers but the times have been constant for all 3 trials.FFT, PSD and spectrograms don't need to be so complicated. Yorick takes on the Sun for a 1024x0124 complex FFT: I did not try it with the new Clean Sun release. I am not a qualified Scilab programmer, but I think the figures would'nt change otherwise: The Scilab array is not exactly the same as the Clean array. ![]() On the same machine and nearly at the same time. Though there 3 users currently logged-in, I think a benchmark compared to Scilab is acceptable:ġ024x1024 complex FFT in Clean (unboxed arrays): Gonzi for the FFT code, but let me put in a few remarks. > The Yorick code itself is not very fast (compared to IDL or Matlab) okay IDL is very expensive I wouldn't be surprised that they have implemented a highly tuned one or even an assembler-version. The Yorick times are *always* constant! With Clean it can happen that the program runs 10sec, or often 5sec but 4sec are the best results. > Yorick takes for a 1024x1204 complex transform 2sec. The problem is that the output results (the DOS window) are always slightly higher than the timing results (maybe the timing-profile overhead is taken into > A 1024x1240 2-dimensional FFT takes in the best cases 4sec. ![]() The following is valid for a 450MHz Pentium III machine with 128MB RAM. ![]() 2 dimensional FFT code Siegfried Gonzi 13:02:10 +0100 ![]()
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