Hi,
I'm having trouble with the application of filtering to real acceleration data. I have looked at a lot of recommendations, filtering through fft, butterworth high and low pass filters, and I'm not finding something thats working for my data and I'm looking for recommendations.
I think my problem is that I am looking at very slow accelerations, so the "drift" in the accelerometer is eliminated-but so is the trend in the data itself. I will be looking at the cases of relatively slow acceleration and velocity, and slow acceleration with pauses in between sequences. A low pass filter does okay-but does not provide an accurate map of displacement in the end. Using an fft seems to also eliminate the slower trend in the data.
I have also added in elimination of values less than the abolsute mean found for a static case. This seems to help a little bit, but I may be losing some data.
I have attached a couple of examples of what the problem is. I made a rectangle with the accelerometer pretty much and these are the results with no filters and a low pass filter.
First 2 are no filter. 2nd 1 is the LP filtered accel. (I can send velocity if interested-looks the same pretty much)
Are there any other filters I should be trying? Different methods of integration? (I am currently using a trapazoidal integrator). I'm pretty much looking for recommendations processing this type of data.
Thanks! (I also hope this is the correct thread for this).
I'm having trouble with the application of filtering to real acceleration data. I have looked at a lot of recommendations, filtering through fft, butterworth high and low pass filters, and I'm not finding something thats working for my data and I'm looking for recommendations.
I think my problem is that I am looking at very slow accelerations, so the "drift" in the accelerometer is eliminated-but so is the trend in the data itself. I will be looking at the cases of relatively slow acceleration and velocity, and slow acceleration with pauses in between sequences. A low pass filter does okay-but does not provide an accurate map of displacement in the end. Using an fft seems to also eliminate the slower trend in the data.
I have also added in elimination of values less than the abolsute mean found for a static case. This seems to help a little bit, but I may be losing some data.
I have attached a couple of examples of what the problem is. I made a rectangle with the accelerometer pretty much and these are the results with no filters and a low pass filter.
First 2 are no filter. 2nd 1 is the LP filtered accel. (I can send velocity if interested-looks the same pretty much)
Are there any other filters I should be trying? Different methods of integration? (I am currently using a trapazoidal integrator). I'm pretty much looking for recommendations processing this type of data.
Thanks! (I also hope this is the correct thread for this).