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Enhanced canonical variate analysis with slow feature for dynamic process status analytics
Journal of Process Control ( IF 4.2 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.jprocont.2020.09.005
Jiale Zheng , Chunhui Zhao

Abstract Process dynamics is widely presented in industrial processes, which can be perceived as temporal correlations. Negligence of dynamic information may result in misleading monitoring results. Therefore, explicit exploration of dynamic information is crucial to process monitoring. In this paper, a new data-driven algorithm called enhanced canonical variate analysis with slow feature (ECVAS) and corresponding monitoring strategy are proposed for dynamic process monitoring. First, a new objective function is defined with two goals, which attempts to extract slowly varying latent variables in addition to high temporal correlation. Hence, the latent variables called slow canonical variables (SCVs) would capture valuable dynamic information and be isolated from static information and fast-varying noises. Second, the process dynamics has been explored in detail by concurrently monitoring of temporal correlations and varying speed. Therefore, the proposed method achieves in-depth understanding of process dynamics under control actions and helps identify normal changes in operating conditions. Third, process static information and dynamic information have been separately monitored, contributing to a fine-scale identification of process variations. Finally, the validity of the proposed strategy is illustrated with an industrial scale multiphase flow experimental rig and a real thermal power process.

中文翻译:

具有用于动态过程状态分析的慢速功能的增强型规范变量分析

摘要 过程动力学广泛存在于工业过程中,可以被视为时间相关性。动态信息的疏忽可能导致误导性的监测结果。因此,动态信息的显式探索对于过程监控至关重要。在本文中,提出了一种新的数据驱动算法,称为具有慢特征的增强规范变量分析(ECVAS)和相应的监控策略,用于动态过程监控。首先,定义了一个具有两个目标的新目标函数,除了高时间相关性之外,它还试图提取缓慢变化的潜在变量。因此,称为慢规范变量 (SCV) 的潜在变量将捕获有价值的动态信息,并与静态信息和快速变化的噪声隔离。第二,通过同时监测时间相关性和变化的速度,详细探讨了过程动态。因此,所提出的方法可以深入了解控制动作下的过程动态,并有助于识别操作条件的正常变化。第三,过程静态信息和动态信息被分开监控,有助于精细识别过程变化。最后,通过工业规模的多相流实验台和真实的火力发电过程说明了所提出策略的有效性。过程静态信息和动态信息被分别监控,有助于精细识别过程变化。最后,通过工业规模的多相流实验台和真实的火力发电过程说明了所提出策略的有效性。过程静态信息和动态信息被分别监控,有助于精细识别过程变化。最后,通过工业规模的多相流实验台和真实的火力发电过程说明了所提出策略的有效性。
更新日期:2020-11-01
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