装配过程中起止点识别的神经网络结构

Q2 Engineering

Journal of Machine Engineering Pub Date : 2023-04-19 DOI:10.36897/jme/163318

I. Kutschenreiter-Praszkiewicz

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引用次数: 0

摘要

本文提出了一种使用机器学习进行基于视频的装配分析的方法。神经网络是在许多工程领域中广泛研究的机器学习方法之一。本文的目的是开发一种深度神经网络结构，用于识别选定零部件装配过程的起点和终点。提出了一种有效识别起点-终点的神经网络结构，并给出了一个工业实例。该方法可用于装配过程分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Development of a neural network structure for identifying begin-end points in the assembly process

The paper presents an approach to video-based assembly analysis using machine learning. A neural network is one of the machine learning methods that is widely studied in many engineering fields. The purpose of this paper is to develop a deep neural network structure for identifying begin-end points for a selected component assembly process. A neural network structure that effectively identifies begin-end points is proposed and an example from industry is presented. The proposed approach can prove useful in the assembly process analysis.

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来源期刊

Journal of Machine Engineering Engineering-Industrial and Manufacturing Engineering

CiteScore

2.70

自引率

0.00%

发文量

审稿时长

25 weeks

期刊介绍： ournal of Machine Engineering is a scientific journal devoted to current issues of design and manufacturing - aided by innovative computer techniques and state-of-the-art computer systems - of products which meet the demands of the current global market. It favours solutions harmonizing with the up-to-date manufacturing strategies, the quality requirements and the needs of design, planning, scheduling and production process management. The Journal'' s subject matter also covers the design and operation of high efficient, precision, process machines. The Journal is a continuator of Machine Engineering Publisher for five years. The Journal appears quarterly, with a circulation of 100 copies, with each issue devoted entirely to a different topic. The papers are carefully selected and reviewed by distinguished world famous scientists and practitioners. The authors of the publications are eminent specialists from all over the world and Poland. Journal of Machine Engineering provides the best assistance to factories and universities. It enables factories to solve their difficult problems and manufacture good products at a low cost and fast rate. It enables educators to update their teaching and scientists to deepen their knowledge and pursue their research in the right direction.