工业网络物理系统的可观测性保证分布式智能传感

IF 4.6 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Signal Processing Pub Date : 2024-11-04 DOI:10.1109/TSP.2024.3490838
Zhiduo Ji;Cailian Chen;Xinping Guan
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引用次数: 0

摘要

分布式传感是在工业网络物理系统(ICPS)的网络环境中获取系统状态信息的关键过程。考虑到未知的复杂工业系统模型,分布式传感的智能方法受到广泛关注。在现有的大多数研究中,首先要严格假设系统的可观测性,以获得完整的传感信息,用于后续的状态估计。但随着工业监测网络规模的扩大,可观测性要求越来越难以提前满足。因此,本文针对 ICPS 提出了一种新的具有可观测性保证的分布式智能传感方法。具体来说,本文设计了一种基于现场级数据的分布式学习机制,以动态逼近分布式传感过程。然后,提供了学习权重完全更新条件来主动保证可观测性,并提出了新颖的凸集构造方法来处理该条件的非凸特性。此外,还详细分析了学习收敛速度和误差约束。最后,基于已建立的仿真系统,将所提出的方法应用于工业热轧层流冷却过程。与最先进的分布式智能传感方法相比,所提出的方法能在保证可观测性的前提下,积极降低传感成本,同时提高传感性能。在归一化传感性能和传感终端选择数量上实现了平均 24.1% 的整体提升,为类似 ICPS 关键工序智能传感的升级提供了解决方案。
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Observability Guaranteed Distributed Intelligent Sensing for Industrial Cyber-Physical System
Distributed sensing is a key process for acquiring system state information in the network environments of industrial cyber-physical system (ICPS). Considering the unknown complex industrial system models, the intelligent methods for distributed sensing are received extensive attention. In most existing works, the system observability is assumed strictly first to obtain complete sensing information for subsequent state estimation. But with the expansion of industrial monitoring network scale, the observability requirement is increasingly difficult to be satisfied in advance. Therefore, a new distributed intelligent sensing method with guaranteed observability is proposed for ICPS in this paper. Specifically, a distributed learning mechanism based on field level data is designed to dynamically approximate the distributed sensing process. Then, the learning weight complete update condition is provided to actively guarantee the observability, and the novel convex-set construction approach is proposed to handle the non-convex property of this condition. Besides, the learning convergence speed and error bound are analyzed in detail. Finally, the proposed method is applied into the industrial hot rolling laminar cooling process based on the established simulation system. Compared with state-of-the-art methods in distributed intelligent sensing, the proposed method can actively reduce the sensing cost while improving the sensing performance with guaranteed observability. An average overall improvement of 24.1% in the normalized sensing performance and selection number of sensing terminals is achieved, which provides a solution for the upgrade of intelligent sensing of key processes in similar ICPS.
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来源期刊
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing 工程技术-工程:电子与电气
CiteScore
11.20
自引率
9.30%
发文量
310
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.
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