基于知识-规则融合与动态置信度量化的双机器人钻铆智能参数推荐方法

doi:10.7527/S1000-6893.2025.32623

Abstract

Abstract:

To address the challenge of intelligent decision-making in dual-robot drilling and riveting， which is often hindered by reliance on manual expertise and fragmented process knowledge， this study proposes an intelligent parameter recommendation method that integrates knowledge graphs with rule reasoning. Initially， a multi-layer knowledge graph for dual-robot drilling and riveting is constructed. This graph comprises 292 entities and 711 relationships， organized across five layers： tool， workpiece， process， feature， and instance. It enables multimodal semantic associations among material properties， process parameters， and quality indicators. Based on this knowledge graph， a two-stage reasoning framework is introduced. In the first stage， similar cases are retrieved using a weighted cosine similarity algorithm， where the weights are determined via the analytic hierarchy process. In the second stage， a priority-based rule engine enforces parameter constraints and resolves conflicts. This framework enhances both the accuracy and consistency of parameter recommendations. Furthermore， a dynamic confidence evaluation model is developed by incorporating data- and rule-based constraints， establishing a four-dimensional assessment along the axes of data scale， data quality， data distribution， and rule conflicts. This dynamic weighting mechanism enhances the interpretability of the recommendation results. Experimental validation on a dual-robot drilling and riveting workstation at COMAC Shanghai Aircraft Manufacturing Co.， Ltd. demonstrates that the proposed method achieves a comprehensive confidence level of 0.93， with the recommended parameters satisfying physical process constraints. Overall， this method provides an effective approach for capturing and reusing process knowledge while supporting intelligent decision-making in complex manufacturing scenarios.

Key words: parameter recommendation, knowledge graph, drilling and riveting process, knowledge reasoning, knowledge modeling

CLC Number:

V262.4

Yong TAO, Xiaotong WANG, Yazui LIU, Haitao LIU, Yufan ZHANG, Lei XUE, Ruijun GUO, Fan REN, Hongxing WEI. Intelligent parameter recommendation method for dual-robot drilling and riveting with knowledge-rule fusion and dynamic confidence quantification[J]. Acta Aeronautica et Astronautica Sinica, 2026, 47(8): 432623.

Figures/Tables 23

Fig.1

Fig.2

Table 1

Fig.3

Table 2

Fig.4

Table 3

Fig.5

Table 4

Table 5

Search boundary setting of parameters

参数	描述	初值	下界	上界
$κ s$	安全规则权重	1.5	1.2	2.0
$κ q$	质量规则权重	1.2	1.0	1.8
$κ e$	效率规则权重	1.0	0.8	1.3
$N m a x$	案例上限	15	8	15
$τ$	分布阈值	0.2	0.05	0.3

Table 5

Table 6

Optimal parameter configuration

参数	描述	最优值
$κ s$	安全规则权重	1.59
$κ q$	质量规则权重	1.08
$κ e$	效率规则权重	0.88
$N m a x$	案例上限	8
$τ$	分布阈值	0.15

Table 6

Fig.6

Fig.7

Fig.8

Table 7

Table 8

Fig.9

Table 9

Table 10

Table 11

Table 12

Fig.10

Table 13

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关系	关系类型	关系定义
是ID	实体-子实体	各实体身份的唯一标识符
有关系	实体-子实体	实体与子实体间的组成关系及各实体包含的参数
有是	实体-实体	实体间的包含关系，二者互为对应
满足要求	层-实体	不同层内实体包含的质量要求，二者互为对应
使用机器人	层-层	链接实例层与工具层，包括机器人实体与刀具实体
使用刀具	层-层	链接实例层与工具层，包括机器人实体与刀具实体
有加工工件	层-层	链接实例层与工件层
使用钻孔工艺	层-层	链接实例层与工艺层，包括钻孔实体与铆接实体
使用铆接工艺	层-层	链接实例层与工艺层，包括钻孔实体与铆接实体
有钻铆质量	层-层	链接实例层与特征层

参数	特征/单位
X₁	墩头高度/mm
X₂	墩头直径/mm
X₃	铆接干涉量/mm
X₄	钉头平齐度/mm
X₅	材料强度/MPa
X₆	工件质量/kg

规则分类	规则编号	触发条件	推荐措施
安全规则	IC-01	连续3次干涉量>0.08 mm	更换高刚性刀具（抗弯≥2 000 MPa），分步钻削工艺
	RH-01	墩头高度>上限（2.05 mm）	铆接力×0.95
	RG-01	工件质量>550 kg	报警：更换更高负载机型
	…	…	…
质量规则	IC-02	叠层厚度差ΔH>0.1 mm	转速=基准转速×（1+0.075ΔH）
	SF-01	平齐度<0.05 mm	进给速度×0.9
	SF-02	平齐度<0.05 mm	振动幅度>3 μm时更换高负载机器人组
	SF-03	毛刺高度>0.04 mm	铆接力×0.9
	…	…	…
效率规则	MA-01	材料=钛合金	基准转速=4 000+孔径×500，铆接力≤1.2 kN，陶瓷刀具
	SF-04	毛刺高度>0.04 mm	进行刀具磨损检测
	…	…	…

参数	工艺要求
材料	铝锂合金2060 T8E
工件质量/kg	100
孔径/mm	5
墩头高度/mm	2
墩头直径/mm	7
铆接干涉量/mm	0.05
钉头平齐度/mm	0.03

参数	案例1	案例2	案例3	案例4	案例5
钻孔进给/（mm·min^-1）	100	125	225	125	260
制孔转速/（r·min^-1）	4 300	4 000	4 500	3 000	5 000
锪窝转速/（r·min^-1）	1 360	1 000	1 600	1 000	1 800
锪窝进给/（mm·min^-1）	140	110	180	100	240
铆接压力/kN	0.4	0.4	0.4	0.4	0.4
铆接气压/MPa	0.2	0.2	0.2	0.2	0.2
锤铆时间/s	2	2	2	2	2
压紧力/N	450	450	450	450	450
顶紧力/N	350	350	350	350	350
刀具	刀具3	刀具3	刀具3	刀具3	刀具3
机器人组合	KR500+IRB8700	KR500+IRB8700	KR500+IRB8700	KR500+IRB8700	KR500+IRB8700
相似度	0.90	0.88	0.90	0.89	0.87

Intelligent parameter recommendation method for dual-robot drilling and riveting with knowledge-rule fusion and dynamic confidence quantification

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参数	工艺要求
材料	钛合金TC4
工件质量/kg	120
孔径/mm	5
墩头高度/mm	2.20
墩头直径/mm	6.20
铆接干涉量/mm	0.10
钉头平齐度/mm	0.07

参数	基线推荐	PCA推荐	加权推荐	规则修正
钻孔进给/（mm·min^-1）	未找到相似案例	184	162	150
制孔转速/（r·min^-1）		3 994	4 500	6 500
锪窝转速/（r·min^-1）		1 539	1 520	1 500
锪窝进给/（mm·min^-1）		169	100	110
铆接压力/kN		0.6	0.4	0.4
铆接气压/MPa		0.2	0.2	0.2
锤铆时间/s		2.3	2.2	2.5
压紧力/N		500	450	450
顶紧力/N		260	350	350
刀具		刀具3	刀具3	更换陶瓷刀具
机器人组合		KR300+KR300	KR300+KR300	KR300+KR300
案例相似度		0.64	0.74	0.82
综合置信度		0.78	0.81	0.84

参数	推荐参数	历史最优参数
材料	7075 T6	2060 T8E
工件质量/kg	103	100
墩头高度/mm	2.50	2
墩头直径/mm	7.50	7
铆接干涉量/mm	0.05	0.05
钉头平齐度/mm	0.05	0.03
孔径/mm	5	5
钻孔进给/（mm·min^-1）	125	100
制孔转速/（r·min^-1）	4 720	4 300
锪窝转速/（r·min^-1）	1 200	1 360
锪窝进给/（mm·min^-1）	110	140
铆接压力/kN	0.4	0.4
铆接气压/MPa	0.35	0.2
锤铆时间/s	1.75	2
压紧力/N	500	450
顶紧力/N	350	350
刀具	刀具3	刀具3
机器人组合	KR300+KR300	KR300+KR300
案例相似度	0.91
综合置信度	0.93

序号	墩头高度/mm	墩头直径/mm	铆接干涉量/mm	钉头平齐度/mm
1	2.35	7.67	0.05	0.03
2	2.51	7.28	0.04	0.06
3	2.71	7.31	0.03	0.03
4	2.58	7.26	0.03	0.04
5	2.63	7.28	0.05	0.05
6	2.19	7.31	0.05	0.02
7	2.38	7.60	0.04	0.03
8	2.61	7.30	0.03	0.03
9	2.67	7.31	0.05	0.06
10	2.59	7.20	0.04	0.06
11	2.35	7.67	0.05	0.03
12	2.51	7.28	0.03	0.02
13	2.71	7.31	0.05	0.01
14	2.58	7.26	0.06	0.03
15	2.63	7.28	0.07	0.04
16	2.63	7.31	0.07	0.02
17	2.19	7.60	0.08	0.04
18	2.38	7.30	0.07	0.02
19	2.61	7.30	0.14	0.04
20	2.67	7.20	0.09	0.04
21	2.63	7.03	0.06	0.01
22	2.94	7.00	0.07	0.04
23	2.81	7.00	0.08	0.03
24	2.56	7.45	0.06	0.04
25	2.66	6.93	0.08	0.03
26	2.38	7.05	0.08	0.03
27	2.32	7.50	0.07	0.04
28	2.79	7.12	0.09	0.04
29	2.66	7.04	0.09	0.03
30	2.31	6.92	0.09	0.02
平均值	2.55	7.27	0.06	0.03
标准差	0.178	0.201	0.026	0.013

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