工业运动控制的分布式计算体系结构与PHM实现

Shrinivas Kulkarni, A. Guha, Suhas Dhakate, T.R. Milind
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引用次数: 2

摘要

对于许多工业应用程序来说,计算架构是实现“预测健康管理(PHM)”解决方案的主要挑战。特别是对于“工业4.0”的要求,计算架构应该根据相关设备的计算需求、计算能力和通信能力而发展。本文提出了一种分布式计算体系结构及其在工业应用中的应用。本文讨论了分布式控制的发展及其在工业应用中作为边缘智能的应用。提出了一种新的神经网络结构,可用于将工业领域知识与机器学习技术相结合,以实现PHM。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Computational Architecture for Industrial Motion Control and PHM Implementation
Computational architecture is a major challenge in implementing "Prognostic Health Management (PHM)" solutions, for many industrial applications. Specially for "Industry 4.0" requirements, the computational architectures should be evolving as per computational requirement, computational power and communication capability within the involved devices. This work proposes a distributed computational architecture and its utilization in industrial application. The distributed control development and its usage as edge intelligence for industrial applications, has been discussed. A novel neural network architecture is proposed, which could be used for integrating industrial domain knowledge with machine learning technique, in the context of PHM implementation.
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