FFT/PSD/IFFT analysis on single axis piezoelectric accelerometer signals for curb impacts I'm trying to denoise the signal by performing PSD analysis and followed by IFFT. Ultimately, I want to generate Force and Displacement plots from the denoised acceleration signal.
Noisy Acceleration Signal($a_z$ vs t):

PSD analysis of the signal:

Setting a PSD &gt; 0.001 in the code to filter out frequencies having less power than 0.001.
After IFFT($a_z$ vs t):

The denoised signal makes sense since I'm recording z-acceleration on curb impacts which comes out to be a series of impulses.
I'm a novice in signal processing and I don't know whether a windowing would have given a better result or not?
Further questions: Is it possible to find force distribution from the acceleration signal? I've been searching to find answers but none have given me a good idea.
Filtering by zeroing out bins is not a recommended approach as it will introduce significantly more time domain ringing, as detailed here
Why is it a bad idea to filter by zeroing out FFT bins?
Consider using the firls function available in MATLAB / Octave or Python scipy.signal to design optimized multiband filters around your frequencies of interest.
However the frequency content will be driven by repetition in the data; if the actual application will repeat (or not) at unknown and variable intervals, any such filtering techniques will not be useful.