Disclaimer: I'm a beginner at all of this.
I am working with vibration data from accelerometers recorded at a sampling rate of 1600 Hz and the vibrations are induced by a source within the range of 20-40 Hz. I snip out about 60-80 seconds of data and use it for analysis. I have the following work flow to perform some basic analysis on this vibration data, where I run the data through a series of digital band passes (all 5Hz - 500Hz) and integrate it:
I am able to generate plots that look this this:
My questions are:
The strange peaks in the overview at the extreme ends : I understand from a bit of reading around, that this is due to passing my snipped signal through a digital band pass filter without padding it on both sides. Another method that I have read which could solve this is - subtract the mean value of the input signal, pass it through the DBP and then add the average back to the output from the filter. Is this the correct solution? Can someone explain why this happens, from a mathematical PoV please?
When I snip my main signal into chunks of 60-80s, am I already kind of performing a window function? If not, is it always essential to use a window function before I perform an FFT? Because, the smaller chunks that I snip out are already fully relevant for performing an FFT and I don't see how a window function would be relevant in this case.