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ZEMAX中的默认公差
怎样看公差分析中的Text view,例如在默认公差中选取RMS斑点尺寸作为评价标准,ields: Y Symmetric Angle in degrees
# X-Field Y-Field Weight VDX VDY VCX VCY
1 0.000E+000 0.000E+000 2.000E+000 0.000 0.000 0.000 0.000
2 0.000E+000 1.750E+000 1.000E+000 0.000 0.000 0.000 0.000
3 0.000E+000 -1.750E+000 1.000E+000 0.000 0.000 0.000 0.000
4 0.000E+000 2.500E+000 1.000E+000 0.000 0.000 0.000 0.000
5 0.000E+000 -2.500E+000 1.000E+000 0.000 0.000 0.000 0.000
Sensitivity Analysis:
Detailed printing off.
Worst offenders:
Type Value MF Change
TTHI 4 5 0.050000 0.002614 0.000166
TTHI 3 5 0.050000 0.002603 0.000155
TTHI 5 7 -0.050000 0.002600 0.000152
TRAD 5 -0.050000 0.002524 0.000076
TRAD 6 0.050000 0.002517 0.000069
TRAD 4 -0.050000 0.002465 0.000016
TRAD 2 -0.050000 0.002464 0.000016
TRAD 7 0.050000 0.002462 0.000014
TRAD 9 -0.050000 0.002459 0.000011
TTHI 6 7 0.050000 0.002459 0.000011
Nominal RMS Spot Radius : 0.002448
Estimated change : 0.000213
Estimated RMS Spot Radius: 0.002662
Merit Statistics:
Mean : 0.002460
Standard Deviation : 0.000042
Compensator Statistics:
Change in back focus:
Minimum : -0.421427
Maximum : 0.421753
Mean : 0.000023
Standard Deviation : 0.154018
Monte Carlo Analysis:
Number of trials: 20
Initial Statistics: Normal Distribution
Trial Merit Change
1 0.002512 0.000063
2 0.002505 0.000056
3 0.002407 -0.000041
4 0.002446 -0.000002
5 0.002431 -0.000017
6 0.002649 0.000201
7 0.002685 0.000237
8 0.002547 0.000099
9 0.002465 0.000017
10 0.002439 -0.000009
11 0.002457 0.000009
12 0.002473 0.000025
13 0.002599 0.000151
14 0.002425 -0.000023
15 0.002446 -0.000002
16 0.002411 -0.000038
17 0.002484 0.000036
18 0.002450 0.000002
19 0.002458 0.000010
20 0.002446 -0.000002
Nominal 0.002448
Best 0.002407
Worst 0.002685
Mean 0.002487
Std Dev 0.000075
Compensator Statistics:
Change in back focus:
Minimum : -0.582748
Maximum : 0.460942
Mean : -0.102078
Standard Deviation : 0.267300
90% of Monte Carlo lenses have a merit function below 0.002599.
50% of Monte Carlo lenses have a merit function below 0.002457.
10% of Monte Carlo lenses have a merit function below 0.002411.
End of Run
这样的结果可以吗?
若不行,请指出哪里需要改进?
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