学习公差分析的时间不长,其实很多时候真的感到很疑惑,好像有时候在最差的十项里面未必就是最差的,好像有时候会出现比这里面其中的一些还敏感的却没有出现在最差的十项里面,最近一直不求甚解,但今天遇到一问题实在不得不让我去求甚解。事情是这样的,我对一个镜头进行分析,公差分析结果贴在下面,其中第10到11面的空气间隔就是L5-L6的间隔,按照最差的十项来说,应该是变化这个间距MTF会下降比较大,可实际上MTF却没有什么下降,而4到6面的间距(L2和L3之间的空气间隔)变化MTF下降的确比较明显,真不明白这是为什么,镜头的镜片排序大致如下面所示。还有,我请教了前辈,前辈说公差模拟是随机的,不一定正确的,只是有参考价值而已,而且他还说假如公差分析设置的操作数一样,那每次公差分析的结果也不一定相同,这让我有点疑惑,好像我印象中不是这样的,我好像这么做过,但分析的结果是一样的,当然这个我自己去试试就知道了,只是现在太晚了,不想去试一试,想睡觉了,所以对于其他问题,希望各位不吝赐教,谢谢!还有,希望各位看看我公差分析的结果,看看里面是否有设置不对的地方,有的话请指正,再次谢过。 d=8.cQL:E
njZ vi}m~
bKK'U4
-sZ'<(3
L3前面两竖线是光阑 9[&ByEAK
"+Ys}t~2
公差分析结果: 7CSz
Im!b-1
Units are Millimeters. :4Nv6X61
Y<(7u`F
Paraxial Focus compensation is on. In this mode, all GYiL}itD=3
compensators are ignored, except paraxial back focus change. r79P|)\
2yZ~j_AF[
WARNING: Boundary constraints on compensators are ignored when ebNRZJ?C,
using fast mode or user-defined merit functions. VS ;y
vV$^`WY4
Criteria : Diffraction MTF average S&T at 180.0000 lp/mm &"gX
7cK8
Mode : Sensitivities )\VuN-d
Sampling : 3 <Opw"yY&q]
Optimization Cycles : Automatic mode TbT/ 5W3
Nominal Criteria : 0.38686619 &~/g[\Y
Test Wavelength : 0.5460 Ta/zDc"e
[OUV!o
Fields: User Defined Real Image height in Millimeters W2h4ej\s
# X-Field Y-Field Weight VDX VDY VCX VCY 5S!j$_(
1 0.000E+000 0.000E+000 1.000E+000 0.000 0.000 0.000 0.000 OPE+:TvW^
2 0.000E+000 1.151E+000 1.000E+000 0.000 0.000 0.000 0.000 WQ.{Ag?1
3 0.000E+000 1.918E+000 1.000E+000 0.000 0.000 0.000 0.000 km5gO|V>m
4 0.000E+000 2.685E+000 1.000E+000 0.000 0.000 0.000 0.000 9a`~ K L
5 0.000E+000 3.452E+000 1.000E+000 0.000 -0.105 0.002 0.105 6SE^+@jR
6 0.000E+000 3.836E+000 1.000E+000 0.000 -0.217 0.014 0.217 "=C~IW
s-'~t#h
Sensitivity Analysis: 2)\MxvfOh
E'D16Rhp
|------------ Minimum ------------| |------------ Maximum ------------| E3[9!L8gb
Type Value Criteria Change Value Criteria Change }` H{;A
h
TTHI 2 3 -0.010000 0.386393 -0.000473 0.010000 0.380196 -0.006670 C9MK3vtD.
TTHI 4 6 -0.010000 0.380717 -0.006149 0.010000 0.378999 -0.007867 !jU{ }RCR
TTHI 7 8 -0.010000 0.380585 -0.006282 0.010000 0.386480 -0.000386 Bhx.q,X
TTHI 10 11 -0.010000 0.375901 -0.010965 0.010000 0.385879 -0.000987 ohyq/u+y~A
TTHI 12 13 -0.010000 0.386971 0.000105 0.010000 0.386709 -0.000158 ^>!&]@
TTHI 14 15 -0.010000 0.386958 0.000092 0.010000 0.386722 -0.000144 vO~w~u5
"nfi:A1
Worst offenders: \o2l;1~
Type Value Criteria Change zA+0jhuG
TTHI 10 11 -0.010000 0.375901 -0.010965 lX2:8$?X
TTHI 4 6 0.010000 0.378999 -0.007867 &=M4Z/Ao
TTHI 2 3 0.010000 0.380196 -0.006670 &Z!y>k%6
TTHI 7 8 -0.010000 0.380585 -0.006282 mbX'*up
TTHI 4 6 -0.010000 0.380717 -0.006149 \),f?f-m
TTHI 10 11 0.010000 0.385879 -0.000987 dMsS OP0E
TTHI 2 3 -0.010000 0.386393 -0.000473 iHc(e(CB<
TTHI 7 8 0.010000 0.386480 -0.000386 }:{ @nP
TTHI 12 13 0.010000 0.386709 -0.000158 >@cBDS<6R
TTHI 14 15 0.010000 0.386722 -0.000144 bc~WJ+
$|&<cenMT
cpw=2vnD
Estimated Performance Changes based upon Root-Sum-Square method: _=`DzudE
Nominal MTF : 0.3869 WHOy\j},V
Estimated change : -0.0124 "fhQ{b$i
Estimated MTF : 0.3745 z)v o
lc~c=17
Compensator Statistics: 2vG
X\W%3
Change in back focus: !s/qqq:g
Minimum : -0.008974 'q~<ZO
Maximum : 0.008997 "K9[P:nw
Mean : 0.000002 jck(cc=R
Standard Deviation : 0.004372 u*5}c7)uId
-:'%YHxX
Hf1b&8&:K
Monte Carlo Analysis: I9aiAD0s
Number of trials: 20 sKKc_H3YSH
3WwCo.q;m
Initial Statistics: Normal Distribution d/Wp>A@dob
F@Wi[K
Trial Criteria Change =L1%gQJJ&
1 0.381931 -0.004936 %(6+{'j~#
2 0.386597 -0.000269 ;vPFRiFK
3 0.380763 -0.006103 3kUb cm
4 0.385898 -0.000968 qc)+T_m
5 0.379542 -0.007324 we!w5./Xm
6 0.386121 -0.000745 rr(kFQ"
7 0.388123 0.001257 gpzFY"MS=
8 0.385172 -0.001695 `^on`"\{u
9 0.386426 -0.000440 Kf(Px%G6K
10 0.387614 0.000748 rwW"B
11 0.375242 -0.011624 )G, S7A
12 0.386008 -0.000859 }1V+8'D
13 0.388606 0.001740 sGNHA(;
14 0.383519 -0.003347 FYE(lEjxi
15 0.381154 -0.005712 NYg&