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A modified neighborhood preserving embedding-based incipient fault detection with applications to small-scale cyber-physical systems

机译:一种修改的邻域,保留基于嵌入的初期的故障检测,其中应用于小型网络物理系统

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摘要

Industrial cyber-physical systems (ICPSs) are backbones of the Industrial 4.0 where control, physical entities, and monitoring are intensively interacted. Aiming to improve safety of a small-scale ICPS whose physical entity is an electrical drive system, this paper will develop a new detection strategy for incipient faults in neighborhood preserving embedding (NPE) framework that can provide stable solutions. The proposed modified NPE can not only extract local information effectively on data manifold of the ICPS but also solve the singularity problem caused by generalized eigenvalue decomposition skills. Additional advantages of this design for ICPSs include the enhanced fault detectability, inherent scalability, and accelerated computation efficiency. The proposed method is firstly evaluated by mathematical deviations and then is evaluated by its application to a small-scale ICPS. Three sets of experimental results show the efficacy of the proposed method in dealing with online detection of incipient faults in the ICPS. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.
机译:工业网络物理系统(ICPS)是工业4.0的骨干,其中控制,物理实体和监测集中互动。旨在提高其物理实体是电动驱动系统的小型ICP的安全性,本文将对嵌入嵌入(NPE)框架的局部初始故障开发新的检测策略,可以提供稳定解决方案。所提出的修改的NPE不仅可以在ICP的数据歧管上有效提取本地信息,而且还解决了由广义特征值分解技能引起的奇点问题。这种ICPS设计的其他优点包括增强的故障可检测性,固有的可扩展性和加速的计算效率。通过数学偏差首先评估所提出的方法,然后通过其应用于小规模ICP来评估。三组实验结果表明了提出的方法在在线检测ICP中的初始故障的在线检测的功效。 (c)2019 ISA。 elsevier有限公司出版。保留所有权利。

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