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Multisubspace Elastic Network for Multimode Quality-Related Process Monitoring

机译：多模质量相关过程监控的多机器弹性网络

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摘要

In this article, a novel multimode quality-related process monitoring method called multisubspace elastic network (MSEN) is proposed. To make mode partition more precisely, this article develops a novel clustering algorithm based on the neighborhood information and subtractive clustering algorithm. In each single mode, unlike conventional process monitoring models that only focus on whether the fault occurs, a novel elastic network based quality-related process monitoring model is established to judge whether the fault is quality related or not. In addition, to select the most suitable monitoring model for online data, the k-nearest neighbor rule and the voting strategy are applied. Once the fault is detected, the contribution plot method is used in both quality-related and quality-unrelated subspace for fault diagnosis. Finally, the proposed MSEN method is tested under the continuous stirred tank reactor to verify its superiority and advantage.
机译：在本文中，提出了一种名为MultiSumpace Elastic网络（MSEN）的新型多模质量相关过程监测方法。为了更准确地制作模式分区，本文通过邻域信息和减法聚类算法开发一种新型聚类算法。在每个单一模式中，与传统的过程监视模型不同，只关注故障是否发生，建立了一种新的弹性网络的质量相关过程监测模型，以判断故障是否与您有关的质量。此外，为在线数据选择最合适的监控模型，应用K-最近邻居规则和投票策略。一旦检测到故障，贡献绘图方法就在质量相关和质量无关的子空间中用于故障诊断。最后，在连续搅拌釜反应器下测试了所提出的汉氏方法，以验证其优越性和优势。

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