In order to monitor the conditions of tapping tools, the autocorrelation (X) and the
RMS value (Y) of the torque signals are used as indirect indices. The tapping tools are classified as
two categories, usable and worn-out. The obtained data after next-to-last and the last holes were
tapped are listed as follows :
Test No. Next-to-last Last
1. Autocorrelation 0.57 0.67
RMS 0.7 2.5
2. Autocorrelation 0.61 0.7
RMS 0.9 2.3
3. Autocorrelation 0.63 0.77
RMS 0.8 1.8
4. Autocorrelation 0.6 0.74
RMS 1.5 2.2
5. Autocorrelation 0.64 0.71
RMS 1.1 2.7
6. Autocorrelation 0.58 0.72
RMS 1.7 2.6
7. Autocorrelation 0.66 0.76
RMS 1.4 2.4
8. Autocorrelation 0.59 0.78
RMS 1.9 2.1
9. Autocorrelation 0.68 0.81
RMS 1.2 1.6
10. Autocorrelation 0.67 0.8
RMS 1.6 2.0
Find the linear discriminant function to classify tapping tools into
two categories: usable and worn-out.
You should hand in:
(1) Flow Chart of your algorithm
(2) Computer program
(3) Computer Input and Output
(4) A cover page describe the initial weight vector, the
obtained linear discriminant function, etc.,
