- As a dataset 15 (.csv) data and 11 of them are taken under similar conditions. They will be converted from time domain to freq domain by fourier transform to construct a reference frame for remaining four.
- .csv files contain position, angle and time data. Velocity and acceleration will be calculated and transformed into freq domain.
- After freq domain reference is obtained for position and its derivatives and angles. An appropriate filtering will be decided (Kalman and low pass filter is a prerequisite) each variable will be filtered accordingly.
- Remaining four data sets will be correlated by variance analysis(ANOVA).
- This process should be available for any other data sets when provided.
All data extracted from .csv files via another matlab (.m) program. They will be provided when needed. (slight modification on program would be probably enough to get velocity and acceleration)
I am a graduate mechanical engineering student studying control systems and vibrations and experienced with Matlab. I have used Kalman and low pass filters in previous projects and I believe I can complete all the requirements except probably the variance analysis.