| Presentation | 2021-06-11 Defective Judgment Method for Automotive Wire Harness Using Convolutional Neural Network Hiromi Itaya, Tadatoshi Sekine, Shin Usuki, Kenjiro T. Miura, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This report proposes a defective judgment method, where a common mode current is used as an performance index, by a deep learning technique based on a convolutional neural network (CNN). In the proposed method, a CNN is trained by using a data set of which each sample is a combination of a cross-sectional shape image of an automotive wire harness and the common mode current calculated from the shape. Then, we consider several patterns of the input and output of the CNN and discuss which input-output pattern is useful for the defective judgment. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | automotive wire harness / common mode current / convolutional neural network / deep learning |
| Paper # | EMCJ2021-11 |
| Date of Issue | 2021-06-04 (EMCJ) |
| Conference Information | |
| Committee | EMCJ |
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| Conference Date | 2021/6/11(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | EMC |
| Chair | Atsuhiro Nishikata(NagTokyo Inst. of Tech.oya Inst. of Tech.) |
| Vice Chair | Kimihiro Tajima(NTT-AT) |
| Secretary | Kimihiro Tajima(HITACHI) |
| Assistant | Hiroyoshi Shida(EMC Tech) / Kiyoto Matsushima(HITACHI) / Tohlu Matsushima(Kyutech) |
| Paper Information | |
| Registration To | Technical Committee on Electromagnetic Compatibility |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Defective Judgment Method for Automotive Wire Harness Using Convolutional Neural Network |
| Sub Title (in English) | |
| Keyword(1) | automotive wire harness |
| Keyword(2) | common mode current |
| Keyword(3) | convolutional neural network |
| Keyword(4) | deep learning |
| 1st Author's Name | Hiromi Itaya |
| 1st Author's Affiliation | Graduate School of Integrated Science and Technology, Shizuoka University(Shizuoka Univ.) |
| 2nd Author's Name | Tadatoshi Sekine |
| 2nd Author's Affiliation | Shizuoka University(Shizuoka Univ.) |
| 3rd Author's Name | Shin Usuki |
| 3rd Author's Affiliation | Shizuoka University(Shizuoka Univ.) |
| 4th Author's Name | Kenjiro T. Miura |
| 4th Author's Affiliation | Shizuoka University(Shizuoka Univ.) |
| Date | 2021-06-11 |
| Paper # | EMCJ2021-11 |
| Volume (vol) | vol.121 |
| Number (no) | EMCJ-63 |
| Page | pp.pp.1-6(EMCJ), |
| #Pages | 6 |
| Date of Issue | 2021-06-04 (EMCJ) |