Prevent Twisting Wire Rope Inspection Based on Neural Network

被引：0

作者：

Chen Zhen ^{[1
]}

Chen Xianwei ^{[1
]}

Liu Tao ^{[1
]}

机构：

[1] Liaoning Power Transmiss & Transformat Engn Co, Shenyang 110021, Peoples R China

来源：

PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC) | 2018年

关键词：

Steel Rope; Broken Wire; Neural Network; Quantitative Inspection;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In view of the problem flow detection precision existed ill traditional qualitative inspection system of broken wire for the anti twisting wire rope, the paper proposed a design scheme of quantitative detection system of broken wire for steel rope based on BP neural network. The BP Neural Network is introduced to establish the model of discerning quantitative broken steel wires. Experimental results show that the method performs well in the identification of damage.

引用

页码：4341 / 4343

页数：3

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