From the class data file postings, download the mat file lab5test.mat and load this into your workspace. This mat file contains 3 A-scans (in vectors (ta1, ta2, ta3) acquired with the same scanner used to collect the training data. Use the 2 filters developed in the previous problems to find the flaw locations for each A-scan. Indicate the estimated flaw position in millimeters for each file and include these results in the results section, as well as the plots of filtered A-scans used to locate the flaws. In estimating the location, the filter delay will cause a shift between the peak in the filtered signal and the actual position. Use the estimated filter delay computed in the previous exercise to correct for this delay in your location estimates. In the discussion section describe how confident you can be about your detection and estimation for each case. Clearly indicate what you are basing your confidence (or lack thereof) on. For the filters determined in Part 1, compute the group delay of the filter. This can be done with command >>[G,f] = grpdelay(b,a,N,fs). See Matlab’s the help files on it. This works similar to the freqz() command but it shows the delay in samples that an input signal frequency component will undergo in passing through the filter. For FIR filter the group delay will be constant over all frequencies resulting in an undistorted shift in time of the filtered flaw echo. For IIR filters the delay will be variable over the filter frequency range, but should be relatively constant over the passband. In determining the delay for the IIR filter, you should focus on the spectral region where the input signal contains the most energy. Plot the group delays for the 2 filters used in Part 1 in the results section. In the discussion section, describe whether these delays are consistent with the delays you actually found in Part 1.
From the class data file postings, download the mat file lab5test.mat and load this into your workspace. This mat file contains 3 A-scans (in vectors (ta1, ta2, ta3) acquired with the same scanner used to collect the training data. Use the 2 filters developed in the previous problems to find the flaw locations for each A-scan. Indicate the estimated flaw position in millimeters for each file and include these results in the results section, as well as the plots of filtered A-scans used to locate the flaws. In estimating the location, the filter delay will cause a shift between the peak in the filtered signal and the actual position. Use the estimated filter delay computed in the previous exercise to correct for this delay in your location estimates. In the discussion section describe how confident you can be about your detection and estimation for each case. Clearly indicate what you are basing your confidence (or lack thereof) on. For the filters determined in Part 1, compute the group delay of the filter. This can be done with Matlab’s command >>[G,f] = grpdelay(b,a,N,fs). See the help files on it. This works similar to the freqz() command but it shows the delay in samples that an input signal frequency component will undergo in passing through the filter. For FIR filter the group delay will be constant over all frequencies resulting in an undistorted shift in time of the filtered flaw echo. For IIR filters the delay will be variable over the filter frequency range, but should be relatively constant over the passband. In determining the delay for the IIR filter, you should focus on the spectral region where the input signal contains the most energy. Plot the group delays for the 2 filters used in Part 1 in the results section. In the discussion section, describe whether these delays are consistent with the delays you actually found in Part 1.