基于正交设计的协作机器人全域结构优化设计

doi:10.13229/j.cnki.jdxbgxb20190838

Abstract

Abstract:

To dispose of the influence of time-varying configurations and modeling accuracy on robot structural optimization， a Real-time Modal Analysis （RMA） method for collaborative robots was propose， which combines the finite element method and analytical method. This method could real-time obtain the natural frequencies and mode shapes of robots in any pose with high efficiency and precision. To reduce the calculating amount and realize global structure optimization， based on orthogonal design， a global structural optimization design method of collaborative robots was proposed with the structure parameters as optimization variables and the ratio of robot mass to the global first natural frequency index （M/GF） as optimization objective. The M/GF indexes of SHIR5 robot before and after optimization are calculated. The index after optimization is 9.90% higher than that before optimization， and the global first natural frequency index （GFNFI） is increased by 0.91Hz compared with that before optimization.

Key words: mechatronic engineering, orthogonal design, collaborative robots, natural frequency

CLC Number:

TP241

Ming-wei HU,Hong-guang WANG,Xin-an PAN. Global structural optimization design of collaborative robots using orthogonal design[J].Journal of Jilin University(Engineering and Technology Edition), 2021, 51(1): 370-378.

Figures/Tables 10

Fig.1

Fig.2

Fig.3

Table 1

Table 2

L27(313) orthogonal array"

No.	T₁	T₂	T₃	T₄	T₅	T₆	T₇	T₈	T₉	T₁₀	T₁₁	L1	L2	M/kg	GFNFI/Hz	M/GF
1	1	1	1	1	1	1	1	1	1	1	1	1	1	21.06	7.90	2.67
2	1	1	1	1	2	2	2	2	2	2	2	2	2	21.62	8.21	2.63
3	1	1	1	1	3	3	3	3	3	3	3	3	3	22.20	8.37	2.65
4	1	2	2	2	1	1	1	2	2	2	3	3	3	21.41	7.89	2.71
5	1	2	2	2	2	2	2	3	3	3	1	1	1	21.93	8.22	2.67
6	1	2	2	2	3	3	3	1	1	1	2	2	2	21.84	8.26	2.64
7	1	3	3	3	1	1	1	3	3	3	2	2	2	21.77	7.94	2.74
8	1	3	3	3	2	2	2	1	1	1	3	3	3	21.67	8.01	2.71
9	1	3	3	3	3	3	3	2	2	2	1	1	1	22.19	8.34	2.66
10	2	1	2	3	1	2	3	1	3	2	1	2	3	21.73	7.97	2.73
11	2	1	2	3	2	3	1	2	1	3	2	3	1	21.70	8.16	2.66
12	2	1	2	3	3	1	2	3	2	1	3	1	2	21.85	8.23	2.65
13	2	2	3	1	1	2	3	2	1	3	3	1	2	21.67	8.07	2.68
14	2	2	3	1	2	3	1	3	2	1	1	2	3	21.75	8.33	2.61
15	2	2	3	1	3	1	2	1	3	2	2	3	1	21.76	7.86	2.77
16	2	3	1	2	1	2	3	3	2	1	2	3	1	21.78	8.23	2.64
17	2	3	1	2	2	3	1	1	3	2	3	1	2	21.78	8.04	2.71
18	2	3	1	2	3	1	2	2	1	3	1	2	3	21.72	8.18	2.66
19	3	1	3	2	1	3	2	1	2	3	1	3	2	21.78	7.97	2.73
20	3	1	3	2	2	1	3	2	3	1	2	1	3	21.93	8.08	2.72
21	3	1	3	2	3	2	1	3	1	2	3	2	1	21.93	8.24	2.66
22	3	2	1	3	1	3	2	2	3	1	3	2	1	21.89	8.18	2.68
23	3	2	1	3	2	1	3	3	1	2	1	3	2	21.87	8.25	2.65
24	3	2	1	3	3	2	1	1	2	3	2	1	3	21.87	8.04	2.72
25	3	3	2	1	1	3	2	3	1	2	2	1	3	21.84	8.33	2.62
26	3	3	2	1	2	1	3	1	2	3	3	2	1	21.86	7.88	2.77
27	3	3	2	1	3	2	1	2	3	1	1	3	2	21.92	8.20	2.67
R	0.14	0.09	0.27	0.11	0.11	0.37	0.04	0.54	0.38	0.29	0.19	0.10	0.06
Level	7	11	5	9	8	3	13	1	2	4	6	10	12
最优水平	1	1	1	1	3	3	2	3	1	1	1	1	3
T	0.32	0.11	1.09	0.18	0.20	2.31	0.03	6.77	2.42	1.34373	0.5120	0.155	0.06
Influence	No	No	No	No	No	No	No	Yes	No	No	No	No	No
Significance level 方正汇总行 $α = 0.1 ? ? ? ? ? ? ? ? ? F α (r - 1, n - r) = F 0.1 (2,24) = 2.54$

Table 2

Fig.4

Table 3

Fig.5

Fig.6

Fig.7

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