I have 1000 Hz time series data for acceleration (512 data points), which I want to convert to velocity. I am trying to use the omega arithmetic method to achieve this. Following are the steps I am taking:
- Converting the acceleration-time data to its DFT.
- Converting the acceleration DFT to velocity DFT using the omega arithmetic formula(dividing each DFT value by i * omega (i.e. 2 * pi * i * freq))
- Taking the inverse FFT of the velocity DFT to get velocity-time data.
These steps can be seen in the picture above. I am using numpy's FFT functions, and not normalizing the DFT to avoid any confusion.
My question is: Why are the velocity values so low in the velocity-time plot? Am I making any mistake in my steps?