数据挖掘算法在焊接接头质量诊断任务中的应用

R. R. Akhmedyanov, K. F. Tagirova, A. M. Vulfin, V. V. Berkholts, R. Gayanov
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引用次数: 0

摘要

本文讨论了基于射线照相技术的焊接接头智能诊断系统的建立问题。这将加快解码图像的过程,并减少与人为因素相关的错误数量,因为此时解码图像的大部分工作都是手动完成的。这项工作的目标是开发一种智能系统,用于使用神经网络在射线摄影图像中发现焊接接头中的缺陷。所得结果为基于射线成像法的焊接接头智能诊断系统的运行算法,该系统是一种用于检测焊接接头缺陷的训练神经网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data mining algorithms in the task of diagnosing the welded joints quality
The paper discusses the issue of creating an intelligent diagnostic system for welded joints based on the radiographic method. This will speed up the process of decoding radiographic images and reduce the number of errors associated with human factors, since at this time most of the work on decoding images is done manually. The goal of the work is to develop an intelligent system for finding defects in a welded joint in a radiographic image using neural networks. The obtained results are the algorithm of operation of the intelligent diagnostic system for welded joints based on the radiographic method, a trained neural network for detecting defects of welded joints.
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