采用模糊区间分析的柔性航空结构件装配偏差预测

杜丽,梅标,朱伟东,柯臻铮

Assembly variation prediction for compliant aeronautical structures using fuzzy interval analysis

Li DU,Biao MEI,Wei-dong ZHU,Zhen-zheng KE

表 1 基于模糊区间分析和区间分析的装配偏差分析方法的预测结果以及装配偏差实测数据比较

Tab.1 Comparison between measured and predicted assembly variation by fuzzy interval analysis and interval analysis based on assembly variation analysis methods

观测点编号	${U_{{\rm{fuz}}}}$/m						${U_{{\rm{int}}}}$/m	${U_{{\rm{mea}}}}$/m
观测点编号	λ=0	λ=0.2	λ=0.4	λ=0.6	λ=0.8	λ=1	${U_{{\rm{int}}}}$/m	${U_{{\rm{mea}}}}$/m
1	[−0.579 8，0.579 8]	[−0.580 6，0.580 6]	[−0.581 4，0.581 4]	[−0.582 2，0.582 2]	[−0.583 0，0.583 0]	[−0.583 7，0.583 7]	[−0.583 7，0.583 7]	−0.544
2	[−0.554 4，0.554 4]	[−0.554 4，0.554 4]	[−0.554 5，0.554 5]	[−0.554 5，0.554 5]	[−0.554 6，0.554 6]	[−0.554 6，0.554 6]	[−0.554 6，0.554 6]	−0.407
3	[−0.535 9，0.535 9]	[−0.536 0，0.536 0]	[−0.536 0，0.536 0]	[−0.536 1，0.536 1]	[−0.536 1，0.536 1]	[−0.536 2，0.536 2]	[−0.536 2，0.536 2]	−0.269
4	[−0.518 4，0.518 4]	[−0.518 5，0.518 5]	[−0.518 6，0.518 6]	[−0.518 7，0.518 7]	[−0.518 8，0.518 8]	[−0.518 9，0.518 9]	[−0.518 9，0.518 9]	−0.131
5	[−0.507 6，0.507 6]	[−0.507 7，0.507 7]	[−0.507 7，0.507 7]	[−0.507 7，0.507 7]	[−0.507 7，0.507 7]	[−0.507 7，0.507 7]	[−0.507 7，0.507 7]	0.007
6	[−0.581 2，0.581 2]	[−0.581 9，0.581 9]	[−0.582 7，0.582 7]	[−0.583 5，0.583 5]	[−0.584 2，0.584 2]	[−0.585 0，0.585 0]	[−0.585 0，0.585 0]	0.305
7	[−0.557 0，0.557 0]	[−0.557 1，0.557 1]	[−0.557 1，0.557 1]	[−0.557 2，0.557 2]	[−0.557 2，0.557 2]	[−0.557 3，0.557 3]	[−0.557 3，0.557 3]	0.259
8	[−0.539 1，0.539 1]	[−0.539 1，0.539 1]	[−0.539 1，0.539 1]	[−0.539 1，0.539 1]	[−0.539 1，0.539 1]	[−0.539 1，0.539 1]	[−0.539 1，0.539 1]	0.214
9	[−0.519 3，0.519 3]	[−0.519 4，0.519 4]	[−0.519 4，0.519 4]	[−0.519 5，0.519 5]	[−0.519 6，0.519 6]	[−0.519 6，0.519 6]	[−0.519 6，0.519 6]	0.168
10	[−0.500 8，0.500 8]	[−0.500 8，0.500 8]	[−0.500 8，0.500 8]	[−0.500 8，0.500 8]	[−0.500 8，0.500 8]	[−0.500 8，0.500 8]	[−0.500 8，0.500 8]	0.122
11	[−1.414 2，1.414 2]	[−1.514 2，1.514 2]	[−1.614 2，1.614 2]	[−1.714 2，1.714 2]	[−1.814 2，1.814 2]	[−1.914 2，1.914 2]	[−1.914 2，1.914 2]	0.657
12	[−1.051 9，1.051 9]	[−1.151 9，1.151 9]	[−1.251 9，1.251 9]	[−1.351 9，1.351 9]	[−1.451 9，1.451 9]	[−1.551 9，1.551 9]	[−1.551 9，1.551 9]	0.581
13	[−0.690 4，0.690 4]	[−0.690 4，0.690 4]	[−0.790 4，0.790 4]	[−0.890 4，0.890 4]	[−0.990 4，0.990 4]	[−1.090 4，1.090 4]	[−1.190 4，1.190 4]	0.505
14	[−0.810 3，0.810 3]	[−0.814 0，0.814 0]	[−0.817 6，0.817 6]	[−0.821 3，0.821 3]	[−0.825 0，0.825 0]	[−0.828 6，0.828 6]	[−0.828 6，0.828 6]	0.429
15	[−0.533 5，0.533 5]	[−0.533 5，0.533 5]	[−0.533 5，0.533 5]	[−0.533 5，0.533 5]	[−0.533 5，0.533 5]	[−0.533 6，0.533 6]	[−0.533 6，0.533 6]	0.353
16	[−1.409 8，1.409 8]	[−1.509 8，1.509 8]	[−1.609 8，1.609 8]	[−1.709 8，1.709 8]	[−1.809 8，1.809 8]	[−1.909 8，1.909 8]	[−1.909 8，1.909 8]	−0.869
17	[−1.049 0，1.049 0]	[−1.149 0，1.149 0]	[−1.249 0，1.249 0]	[−1.349 0，1.349 0]	[−1.449 0，1.449 0]	[−1.549 0，1.549 0]	[−1.549 0，1.549 0]	−0.728
18	[−0.686 7，0.686 7]	[−0.786 7，0.786 7]	[−0.886 7，0.886 7]	[−0.986 7，0.986 7]	[−1.086 7，1.086 7]	[−1.186 7，1.186 7]	[−1.186 7，1.186 7]	−0.588
19	[−0.806 8，0.806 8]	[−0.810 4，0.810 4]	[−0.814 1，0.814 1]	[−0.817 7，0.817 7]	[−0.821 4，0.821 4]	[−0.825 1，0.825 1]	[−0.825 1，0.825 1]	−0.447
20	[−0.536 7，0.536 7]	[−0.536 7，0.536 7]	[−0.536 7，0.536 7]	[−0.536 7，0.536 7]	[−0.536 7，0.536 7]	[−0.536 7，0.536 7]	[−0.536 7，0.536 7]	−0.307