Hi;
I have an algorithm in VBA that:
-takes the sampled (500-1000 Hz) Torque signal, and splits it up into
sections that correspond to each revolution of the machine.
- For each revolution of torque data, I interpolate the data to fit a
power of 2 samples for the FFT algorithm.
- I take the FFT of each revolution of torque data, and then chop all but
the 1st 4 orders of the spectrum.
- I then take the IFFT to obtain the reconstructed torque signal (1st 4
orders only).
-The purpose of this routine is to determine the maximum variation in the
reconstructed torque signal (called brake torque variation) for each
revolution of the machine.
This has worked well many times in the past, but recently I discovered
sets of data which cause the "spectral leakage" problem, causing spikes
near the beginning and end of the reconstructed signal.
If I apply a heavy enough low pass filter to the original torque signal
(before I take the FFT) it also remedies this problem but this is not a
permanent solution (as heavy low pass filtering of the data skews the
result).
I know proper windowing can remedy this problem, but I am not sure what
windowing strategy to apply for this order analysis/tracking problem.
Any suggestions of what to do or where to look for answers would be much
appreciated.
-Matt
