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ComputerAided_Design_Engineering_amp_Manufactur.pdf

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deviation between the nominal CAD data and the converted measurement data. The measured data<br />

�1<br />

can be converted to the nominal CAD coordinate system, by multiplying T1 to the measured data,<br />

MM. Thus, the relationship can be formed as,<br />

(4.21)<br />

The T2 matrix of 4�4 can be determined by the least squares technique, minimizing the sum of<br />

�1 squares of distance between the converted measurement data ( T1 MM)<br />

and the nominal CAD data (D<br />

� rN). The sum, E, is<br />

E � S|T1 (4.22)<br />

The variational principle can be applied to solve the components of T 2 matrix. A convenient method<br />

for the evaluation of T 2 matrix is to use the pseudo-inverse technique for computational efficiency.<br />

Therefore, T 2 matrix can be calculated as follows<br />

T 2<br />

�<br />

(4.23)<br />

where MM is the CMM measurement data for the surface, and ( )T indicates the transposed matrix. The<br />

calculated T 2 matrix is now used to generate the updated CNC codes downloaded into the CMM, and<br />

the second measurement data, MM(2), are obtained. When the generated measurement path still fails<br />

to measure the thin section of parts, further iterative procedures can be introduced.<br />

Based on the second measurement data MM(2), the second iterative T2(2) matrix can be evaluated<br />

in that case. Prior to going to further iterations, ERR, the sum of squares of distance can be used as a<br />

criterion. That is,<br />

where ERR � sum of squares of distance<br />

�1 T1 MM � T2 D�rN �1 MM T2 D�rN 1<br />

T1 ( )<br />

� ( )| 2 for all measurement points<br />

�<br />

MM( D � rN )T[ ( D�rN) ( D�rN)T] � 1<br />

�<br />

� |T 1<br />

ERR £ TOL<br />

�1 ( k)<br />

MM<br />

�<br />

( k)<br />

T2 D � rN<br />

( )|<br />

(4.24)<br />

(4.25)<br />

and is the kth iterative measurement data, and is the kth iterative T2 matrix. When the<br />

criterion is not met, further iterations can be performed, and finer alignment procedures can be followed.<br />

Figure 4.5 shows the flowchart for a typical alignment system using the rough- and fine-phase alignments.<br />

The illustrated alignment technique can be applied to practical manufacturing of turbine blades, for<br />

ex<strong>amp</strong>le. A turbine blade is modeled into four features such as two chord-length-based cubic spline<br />

curves and two very small edge circles of around 0.15 mm radius. After locating on a CMM, the turbine<br />

blade is probed around the reference block by the six points based on the rough alignment procedure.<br />

The transformation matrix T1 of the rough phase alignment is calculated, and initial measurement<br />

procedures are performed on the pressure/suction surfaces. Based on the measurement data, the T2 transformation matrix is calculated using the least squares technique. The sum of squares of distance<br />

are calculated as a criterion for further iterative measurement procedures. Figure 4.6 shows a typical<br />

distance deviation between the nominal CAD data points and the measured points. It is noteworthy<br />

that, in this figure, the sum of squares of distance is greatly reduced at the first iteration, and further<br />

iterations are not needed. Figure 4.7 shows a typical measurement path before and after the fine phase<br />

alignment; the measurement path is slightly changed so as to measure the thin edges after the fine<br />

alignment procedure. 12<br />

MM k ( )<br />

T2 ( k)<br />

2

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