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基于时空 EWMA 的图像数据监测和诊断方法

IF 2.3 2区 工程技术 Q3 ENGINEERING, INDUSTRIAL
Quality Technology and Quantitative Management Pub Date : 2024-03-12 DOI:10.1080/16843703.2024.2321813
Ling Zuo, Panpan Zhou
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引用次数: 0

摘要

随着机器视觉系统的应用日益广泛，监控工业产品图像以发现生产过程中的潜在异常至关重要。在目前的文献中，对机器视觉系统的研究主要集中在对图像的监控。
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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A temporal and spatial EWMA-based monitoring and diagnosing approach for image data
With the increasing application of machine vision systems, it is crucial to monitor images of industrial products for potential anomalies in the production process. In current literature, the resea...
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来源期刊
Quality Technology and Quantitative Management
Quality Technology and Quantitative Management ENGINEERING, INDUSTRIAL-OPERATIONS RESEARCH & MANAGEMENT SCIENCE
CiteScore
5.10
自引率
21.40%
发文量
47
审稿时长
>12 weeks
期刊介绍： Quality Technology and Quantitative Management is an international refereed journal publishing original work in quality, reliability, queuing service systems, applied statistics (including methodology, data analysis, simulation), and their applications in business and industrial management. The journal publishes both theoretical and applied research articles using statistical methods or presenting new results, which solve or have the potential to solve real-world management problems.
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