线束拓扑图纸快速签收方法

雷璐; 吴明宇; 郭智博; 乔晓利

doi:10.13700/j.bh.1001-5965.2023.0427

线束拓扑图纸快速签收方法

doi: 10.13700/j.bh.1001-5965.2023.0427

雷璐¹,
吴明宇¹,
郭智博¹,
乔晓利^{1, 2, ,}

1.
长春理工大学机电工程学院，长春 130022
2.
长春理工大学重庆研究院，重庆 401135

基金项目:

吉林省科技发展计划(20200401128GX)；重庆英才计划包干制项目(cstc2022ycjh-bgzxm0187)

详细信息

通讯作者:
E-mail：qiaoxiaoli@cust.edu.cn

中图分类号: TP391.7
计量
- 文章访问数: 133
- HTML全文浏览量: 45
- PDF下载量: 3
- 被引次数: 0
出版历程
- 收稿日期: 2023-06-29
- 录用日期: 2023-11-10
- 网络出版日期: 2023-12-09
- 整期出版日期: 2025-09-30

Fast sign-off method for wiring harness topology drawings

LEI Lu¹,
WU Mingyu¹,
GUO Zhibo¹,
QIAO Xiaoli^{1, 2
, ,}

1.
School of Mechanical and Electrical Engineering，Changchun University of Science and Technology，Changchun 130022，China
2.
Chongqing Research Institute of Changchun University of Science and Technology，Chongqing 401135，China

Funds:

Science and Technology Development Plan of Jilin Province (20200401128GX); Chongqing Talent Plan Contract System Project (cstc2022ycjh-bgzxm0187)

More Information

Corresponding author: E-mail：qiaoxiaoli@cust.edu.cn

摘要

摘要:
针对人工校验签收线束拓扑图纸效率低、失误率高且不能适应智能化生产的问题，提出了基于图文法和谓词逻辑的线束拓扑图纸快速签收方法。该方法主要由图重构和图解析组成。图重构过程中，为使图结构能更好反映图纸数据，引入谓词逻辑对图资源进行提取，将拓扑图重构为标准图。图解析包含图语法分析器和图语义分析器。图语法分析器使用图文法归约算法对图结构进行识别解析，判断设计过程中是否出现图纸结构性错误，实现制图逻辑检查；图语义分析器应用归约判断重构后的图信息描述是否正确，并参照信息唯一性准则，将路径信息解析后与电线表比对，完成轨迹信息匹配性检测。在此基础上开展了12组实物实验，结果表明：所提方法可以将线束拓扑图纸签收耗时从3 h降低为9 s，且在此过程中未出现漏识别现象。
- 线束拓扑图纸 /
- 签收 /
- 图文法 /
- 谓词逻辑 /
- 归约
Abstract:
To address the low efficiency, the high error rate, and inability to adapt to intelligent production when wiring harness drawings are manually verified and signed off, this paper proposed a fast sign-off method for wiring harness topology drawings based on graph grammar and predicate logic. The method mainly consisted of two parts: graph reconstruction and graph parsing. In the process of graph reconstruction, to make the graph structure better reflect drawing data, predicate logic was introduced to extract graph resources, and the topology drawing was reconstructed into a standard graph. Graph parsing involved a graph grammar analyzer and a graph semantic analyzer. In the graph grammar analyzer, a graph grammar reduction algorithm was used to identify and analyze the graph structure, so as to judge whether there were structural errors in the drawing during the design process and to realize the logic check of the drawing. The graph semantic analyzer applied the reduction judgment to reconstructed graph information description and refers to the information uniqueness criterion for comparing the path information with the wire table after parsing to complete the matching detection of the trajectory information. On this basis, 12 groups of physical experiments were carried out. The experimental results show that this method can reduce the time required for signing off the wiring harness drawings from 3 hours to 9 seconds, and there is no missing recognition phenomenon in the process.
- wiring harness topology drawings /
- sign-off /
- graph grammar /
- predicate logic /
- reduction

HTML全文

图 1 航空线束拓扑示意图

Figure 1. Aviation wiring harness topology

下载: 全尺寸图片幻灯片

图 2 线束拓扑图纸图重构起始图-结果图

Figure 2. Start diagram-result diagram of graph reconstruction of wiring harness topology drawing

下载: 全尺寸图片幻灯片

图 3 图文法RGG产生式集合

Figure 3. Graph grammar RGG production set

下载: 全尺寸图片幻灯片

图 4 图归约过程

Figure 4. Graph reduction process

下载: 全尺寸图片幻灯片

图 5 归约完成的3种错误情况

Figure 5. Three error situations for completion of reduction

下载: 全尺寸图片幻灯片

图 6 线束路径解析

Figure 6. Wiring harness path analysis

下载: 全尺寸图片幻灯片

图 7 路径查找过程

Figure 7. Path lookup process

下载: 全尺寸图片幻灯片

图 8 签收效率对比

Figure 8. Comparison of sign-off efficiency

下载: 全尺寸图片幻灯片

图 9 签收准确性对比

Figure 9. Comparison of sign-off accuracy

下载: 全尺寸图片幻灯片

表 1 谓词逻辑设计

Table 1. Predicate logic design

函数	参数	释义
Circle(V_i)	V_i为点对象	V_i为圆
Radius(V_i, R₀)	V_i为点对象， R₀为固定半径	V_i半径为R₀
Node(V_i)	V_i为点对象	V_i为结点
Line(E_i)	E_i为边对象	边为直线
SamePoint($O_{V_i} $, $O_{V_j} $)	V_i、V_j为点对象	两点重合
Outer(V_i)	V_i为点对象	V_i为外结点
Knee(V_i)	V_i为点对象	V_i为拐点
EquipInfoTable(g)	g为图元	元素为设备信息表成员
PinHoleTable(g)	g为图元	元素为针孔表成员
Text(g)	g为图元	元素为文本
Table(g)	g为图元	元素为表格
GreatThanNumber(m, N₀)	m为数值，N₀为常数	m大于N₀
EqualsNumber(m, N₀)	m为数值，N₀为常数	m等于N₀
NaturalNumber(t)	t为文本对象	文本为自然数
SameChar(C₀, C₁)	C₀、C₁为字符	两字符相同
Unique(t)	t为文本对象	文本内容唯一存在

下载: 导出CSV

表 2 过程函数设计

Table 2. Process function design

函数	参数	释义
ConnectedCount(V_i)	V_i为点对象	获取点V_i相连边的数量
Dis(V_j, V_i)	V_j、V_i为点对象	获取两者距离
Sub(g, 0, 1)	g为图元	获取首字母
Length(g)	g为图元	获取元素长度
Min(d)	d为两者距离	匹配距离最短元素
Identifier(g)	g为图元	获取对应元素唯一标识码

下载: 导出CSV

表 3 图重构过程耗时

Table 3. Time consumption of graph reconstruction process

实验编号	线束拓扑图纸边数/条	图重构时间/s
1	17	1.97
2	31	2.23
3	45	2.87
4	62	2.95
5	80	3.18
6	89	3.20
7	116	3.28
8	137	3.82
9	169	4.03
10	203	4.29
11	217	4.59
12	262	6.77

下载: 导出CSV

表 4 图语法分析结果

Table 4. Graph grammar analysis results

实验编号	线束拓扑图纸边数/条	制图逻辑检查时间/s
1	17	0.85
2	31	1.09
3	45	1.32
4	62	1.39
5	80	1.53
6	89	1.54
7	116	1.76
8	137	2.17
9	169	2.61
10	203	3.25
11	217	3.37
12	262	4.28

下载: 导出CSV

表 5 图语义分析结果

Table 5. Graph semantic analysis results

实验编号	线束拓扑图纸边数/条	轨迹信息匹配性检查时间/s
1	17	0.19
2	31	2.21
3	45	2.76
4	62	2.94
5	80	3.17
6	89	3.26
7	116	3.34
8	137	3.76
9	169	3.89
10	203	4.28
11	217	4.91
12	262	6.55

下载: 导出CSV

表 6 签收效率

Table 6. Sign-off efficiency

实验编号	线束拓扑图纸边数/条	计算机判图总时长/s	人工判图总时长/h
1	17	3.01	1
2	31	5.53	1.2
3	45	6.95	1.5
4	62	7.28	2.1
5	80	7.88	2.7
6	89	8.00	2.8
7	116	8.38	3.1
8	137	9.75	3.9
9	169	10.53	4.5
10	203	11.82	6.1
11	217	12.87	6.2
12	262	17.60	6.7

下载: 导出CSV

表 7 签收准确性

Table 7. Sign-off accuracy

实验编号	线束拓扑图纸边数/条	人工判图失效次数	计算机判图失效次数
1	17	0	0
2	31	1	0
3	45	0	0
4	62	2	0
5	80	0	0
6	89	4	0
7	116	3	0
8	137	5	0
9	169	4	0
10	203	7	0
11	217	6	0
12	262	12	0

下载: 导出CSV

参考文献(22)

[1]	李伟, 闫静. 基于CATIA二次开发的线束设计数据提取和结构识别[J]. 电子元器件与信息技术, 2020, 4(1): 71-72. LI W, YAN J. Data extraction and structure identification of wire harness design based on CATIA secondary development[J]. Electronic Component and Information Technology, 2020, 4(1): 71-72(in Chinese).
[2]	王萍, 张晓茜, 罗苑琪. 面向工艺的飞机线束精准设计技术探索[J]. 航空计算技术, 2022, 52(6): 16-20. doi: 10.3969/j.issn.1671-654X.2022.06.004 WANG P, ZHANG X X, LUO Y Q. Process oriented precision design technology for aircraft harness[J]. Aeronautical Computing Technique, 2022, 52(6): 16-20(in Chinese). doi: 10.3969/j.issn.1671-654X.2022.06.004
[3]	王春阳. 航空线束产品三维全信息模型定义与应用研究[D]. 北京: 北京理工大学, 2017: 73-82. WANG C Y. Research on the definition and application of three-dimensional full information model of aviation wire harness products[D]. Beijing: Beijing Institute of Technology, 2017: 73-82(in Chinese).
[4]	LARKIN J H, SIMON H A. Why a diagram is (sometimes) worth ten thousand words[J]. Cognitive Science, 1987, 11(1): 65-100.
[5]	武鹏, 张一哲, 闻敬谦, 等. 面向航空线束的数字化制造关键问题探讨[J]. 航空制造技术, 2017, 60(14): 97-100. WU P, ZHANG Y Z, WEN J Q, et al. Discussion on key issues of digital manufacturing for aircraft wire harness[J]. Aeronautical Manufacturing Technology, 2017, 60(14): 97-100(in Chinese).
[6]	王小辉, 朱丽, 车程, 等. 电气线路互联系统安全性设计与分析方法研究[J]. 西北工业大学学报, 2022, 40(3): 690-698. doi: 10.3969/j.issn.1000-2758.2022.03.026 WANG X H, ZHU L, CHE C, et al. Research on safety design and analysis method of electrical line interconnection system[J]. Journal of Northwestern Polytechnical University, 2022, 40(3): 690-698(in Chinese). doi: 10.3969/j.issn.1000-2758.2022.03.026
[7]	胡波, 赵猛, 卢山, 等. EWIS数字化设计技术分析[J]. 飞机设计, 2019, 39(2): 56-59. HU B, ZHAO M, LU S, et al. Analysis of EWIS digital design technology[J]. Aircraft Design, 2019, 39(2): 56-59(in Chinese).
[8]	YANG S, TONG W, TIAN W. Lilium joins forces with GKN aerospace for lilium jet’s electrical wiring interconnection system (EWIS)[EB/OL]. (2023-01-31)[2023-06-20]. http://www.proquest.com/magazines/lilium-joins-forces-with-gkn-aerospace-jet-s/docview/2771207620/se-2.
[9]	石旭东, 张和茂, 赵宏旭, 等. 复杂线束在双BCI耦合下的终端响应机理[J]. 北京麻豆精品秘国产传媒学报, 2021, 47(9): 1739-1747. SHI X D, ZHANG H M, ZHAO H X, et al. Terminal response mechanism of complex wiring harness under double BCI coupling[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(9): 1739-1747(in Chinese).
[10]	SOHAIL M, PFEIFFER H, WEVERS M. Addressing safety concerns in hybrid electric aircrafts: in-flight icing detection, moisture detection in fuselage and electrical wiring and interconnect system (EWIS)[J]. IOP Conference Series: Materials Science and Engineering, 2022, 1226(1): 012060.
[11]	NIKOLAEV S, ROMANOV O, NYSHCHUK A. Method of modified depth-first search in a graph for constructing all possible gray codes of a specified length[J]. Cybernetics and Systems Analysis, 2023, 59(3): 359-364.
[12]	PANAFIEU É. Analytic combinatorics of connected graphs[J]. Random Structures & Algorithms, 2019, 55(2): 427-495.
[13]	乔晓利, 李林, 刘贡平, 等. 基于谓词逻辑的飞机线束工装图版设计[J]. 北京麻豆精品秘国产传媒学报, 2021, 47(9): 1756-1764. QIAO X L, LI L, LIU G P, et al. Predicate logic based tooling drawing design of aircraft harness[J]. Journal of Beijing University of Aeronautics and Astronautics, 2021, 47(9): 1756-1764(in Chinese).
[14]	LIU Y F, YANG F. EGG+: a graph grammar formalism with uncertain structure processing mechanism[J]. Journal of Logic and Computation, 2021, 31(7): 1800-1819.
[15]	郝国舜, 刘静华, 李士才. 基于对象的P&ID设计软件无向图模型[J]. 北京麻豆精品秘国产传媒学报, 2004, 30(2): 122-126. HAO G S, LIU J H, LI S C. Object-oriented undirected graph model in P & ID design system[J]. Journal of Beijing University of Aeronautics and Astronautics, 2004, 30(2): 122-126(in Chinese).
[16]	邹阳, 吕建, 曹春, 等. 上下文相关图文法的表达能力分析[J]. 软件学报, 2012, 23(7): 1635-1655. ZOU Y, LV J, CAO C, et al. Analysis of expressive ability of context-correlated grammar[J]. Journal of Software, 2012, 23(7): 1635-1655(in Chinese).
[17]	YEH C H, SMITH R E, DHOLLANDER T, et al. Connectomes from streamlines tractography: assigning streamlines to brain parcellations is not trivial but highly consequential[J]. NeuroImage, 2019, 199: 160-171.
[18]	CLARK G J, THOMAZ F, STEPHEN A T. Comparing the principal eigenvector of a hypergraph and its shadows[J]. Linear Algebra and Its Applications, 2023, 673: 46-68.
[19]	REKERS J, SCHÜRR A. Defining and parsing visual languages with layered graph grammars[J]. Journal of Visual Languages & Computing, 1997, 8(1): 27-55.
[20]	KONG J, ZHANG K, DONG J, et al. Specifying behavioral semantics of UML diagrams through graph transformations[J]. Journal of Systems and Software, 2009, 82(2): 292-306.
[21]	陈晋音, 黄国瀚, 张敦杰, 等. 一种面向图神经网络的图重构防御方法[J]. 计算机研究与发展, 2021, 58(5): 1075-1091. doi: 10.7544/issn1000-1239.2021.20200935 CHEN J Y, HUANG G H, ZHANG D J, et al. A graph reconfiguration defense method for graph neural networks[J]. Computer Research and Development, 2021, 58(5): 1075-1091(in Chinese). doi: 10.7544/issn1000-1239.2021.20200935
[22]	SHI Z Y, SUN Y Q, GU Y W, et al. The study about parsing of RGG grammar[J]. Advanced Materials Research, 2011, 204-210: 255-258.