Displacement from Acceleration data

AI Thread Summary
Displacement can be derived from acceleration data using the Fast Fourier Transform (FFT) method, which involves several key steps. First, the mean of the acceleration data is removed, followed by taking the Fourier transform of the data. The transformed data is then converted to displacement by dividing each element by -omega^2, where omega represents the frequency band. Finally, an inverse FFT is performed to return to the time domain, and the results are scaled appropriately. This method provides an alternative to traditional double integration techniques for obtaining displacement from acceleration measurements.
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I was looking for some help on getting displacement from acceleration data (using an accelerometer). I found this old PF thread - https://www.physicsforums.com/archive/index.php/t-123128.html
I am familiar with the double integration/trapezoidal integration. It isn't much help.
The FFT method seems interesting. I don't understand it though.
Is there an explanation of this method. Does it have a name.

Please see FFT method mention by wolfpackdiver in the link above -
1. Remove the mean from the accel. data
2. Take the Fourier transform (FFT) of the accel. data.
3. Convert the transformed accel. data to displacement data by dividing each element by -omega^2, where omega is the frequency band.
4. Now take the inverse FFT to get back to the time-domain and scale your result.
 
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