基于图像识别技术的随机线缆束建模及分布参数统计分析

戎帆; 钟龙权; 刘强; 闫丽萍; 赵翔

doi:10.11884/HPLPB202133.210007

基于图像识别技术的随机线缆束建模及分布参数统计分析

doi: 10.11884/HPLPB202133.210007

戎帆^1,,
钟龙权²,
刘强³,
闫丽萍¹,
赵翔^1, ,

1.
四川大学电子信息学院，成都 610064
2.
中国工程物理研究院应用电子学研究所，四川绵阳 621900
3.
北京应用物理与计算数学研究所，北京 100088

基金项目: 国家自然科学基金面上项目（61877041）

详细信息

作者简介:
戎　帆（1994—），男，硕士，主要从事电磁兼容方面的研究工作

通讯作者:
赵　翔（1973—），女，博士，主要从事电磁效应评估与电磁兼容方面的研究工作

中图分类号: TM152
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- 文章访问数: 908
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- PDF下载量: 59
- 被引次数: 0
出版历程
- 收稿日期: 2021-01-05
- 修回日期: 2021-03-20
- 网络出版日期: 2021-04-10
- 刊出日期: 2021-05-20

Modeling and statistical analysis of distribution parameters of random cable bundles based on image recognition technology

1.
College of Electronic Information, Sichuan University, Chengdu 610064, China
2.
Institute of Applied Electronics, CAEP, Mianyang 621900, China
3.
Beijing Institute of Applied Physics and Computational Mathematics, Beijing 100088, China

摘要

摘要: 提出了一种对实际弯曲随机捆扎线束的建模方法，该方法首先基于图像识别技术，使用实际线束在侧视和俯视方向的两幅照片来实现弯曲线束轴心三维坐标的重建，然后再基于随机转移路径方法实现弯曲线束的捆扎随机性。基于该建模方法，通过蒙特卡洛模拟来分析弯曲随机线束分布参数的统计特征，发现自电感、互电感和互电容均值沿线变化趋势与线束高度变化趋势一致，自电容均值则趋势相反；自电容、自电感和互电感的变异系数与线束高度存在负相关特征；捆扎随机性不会改变自电感和自电容均值，但是会降低互电容与互电感均值。
- 线束 /
- 随机 /
- 图像识别 /
- 分布参数
Abstract: In this paper, a modeling method of actual bending random bundled wire harness is proposed. Firstly, based on image recognition technology, the three-dimensional coordinates of bending wire harness axis are reconstructed by using two photos of actual wire harness in side view and top view; then the random bundled wire harness is realized based on random transfer path method. Based on this modeling method, this paper analyzes the statistical characteristics of distribution parameters of bending random wire harness by Monte Carlo simulation, and finds that the variation trend of self inductance, mutual inductance and mutual capacitance along the line is consistent with the variation trend of wire harness height, while the trend of self capacitance is opposite; the coefficient of variation of self capacitance, self inductance and mutual inductance has negative correlation with wire harness height; the bundling randomness is not obvious It will change the mean value of self inductance and self capacitance, but reduce the mean value of mutual capacitance and mutual inductance.
- wire-bundles /
- random /
- image recognition /
- distributed parameter

HTML全文

图 1 线束照片与建模效果图

Figure 1. Wiring harness photos and modeling drawings

下载: 全尺寸图片幻灯片

图 2 线束斜视照片与建模效果图

Figure 2. Squint photos and modeling drawings

下载: 全尺寸图片幻灯片

图 3 线束横截面示意图

Figure 3. Schematic diagram of wire harness cross section

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图 4 一组弯曲随机线束样本建模效果图

Figure 4. Modeling effect picture of a group of bending random harness samples

下载: 全尺寸图片幻灯片

图 5 本文分布参数计算与商业软件结果对比图

Figure 5. The comparison between the results of distribution parameter calculation and commercial software in this paper

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图 6 一组平直随机线束样本建模效果图

Figure 6. Modeling effect picture of a group of straight random harness samples

下载: 全尺寸图片幻灯片

图 7 弯曲未随机线束分布参数的沿线变化

Figure 7. Variation of distribution parameters of bending non random wire harness along the line

下载: 全尺寸图片幻灯片

图 8 平直随机线束分布参数沿线变化

Figure 8. Variation of distribution parameters of straight random wire harness along the line

下载: 全尺寸图片幻灯片

图 9 弯曲随机线束分布参数沿线变化

Figure 9. Variation of distribution parameters of bending random wire harness along the line

下载: 全尺寸图片幻灯片

图 10 4种线束分布参数均值沿线变化

Figure 10. The variation along the mean value of four kinds of harness distribution parameters

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参考文献(20)

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