Performance Judgment of Automotive Wire Harness Based on Convolutional Neural Network

被引：1

作者：

Sekine, Tadatoshi ^{[1
]}

Itaya, Hiromi ^{[2
]}

Usuki, Shin ^{[1
]}

Miura, Kenjiro T. ^{[1
]}

机构：

[1] Shizuoka Univ, Dept Mech Engn, Hamamatsu, Shizuoka, Japan

[2] Shizuoka Univ, Grad Sch Integrated Sci & Technol, Dept Engn, Hamamatsu, Shizuoka, Japan

来源：

2022 IEEE INTERNATIONAL SYMPOSIUM ON ELECTROMAGNETIC COMPATIBILITY & SIGNAL/POWER INTEGRITY, EMCSI | 2022年

关键词：

D O I：

10.1109/EMCSI39492.2022.10050223

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper describes a performance judgment method based on a convolutional neural network (CNN) for an automotive wire harness. The proposed method uses the CNN to represent the correlation between the cross-sectional shape of the wire harness and its electric performance. We consider combinations of a few patterns of the inputs and outputs of the CNN and discuss about the usefulness of each input-output pattern for the proper judgment.

引用

页码：335 / 335

页数：1