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Advances in Signal Processing and Artificial Intelligence Technologies in the Classification of Power Quality Events: A Survey

机译:电能质量事件分类中信号处理和人工智能技术的进展:一项调查

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Power quality monitoring has advanced from strictly problem solving to ongoing monitoring of system performance. The increased amount of data being collected requires more advanced analysis tools. New intelligent system technologies using expert systems and artificial neural networks provide some unique advantages regarding fault analysis. The purpose of this article is to review and discuss various tools and methodologies aimed at providing more flexible and efficient ways of assessing power quality. Advances in signal processing and artificial intelligence tools will be examined for their role in the detection and classification of events, the application of various mathematical transforms and the implementation of rules-based expert systems. We focus further on the review on several implementation methodologies, and a performance comparison of existing implementations are presented. Recommendations for future study are also outlined. This review opens the path for researchers to future comparative studies between different architectures, and as a reference point for developing more powerful and flexible structures.
机译:电能质量监控已从严格的问题解决发展到了对系统性能的持续监控。越来越多的数据收集需要更先进的分析工具。使用专家系统和人工神经网络的新智能系统技术在故障分析方面提供了一些独特的优势。本文的目的是回顾和讨论各种工具和方法论,旨在提供更灵活,更有效的评估电源质量的方法。信号处理和人工智能工具的进步将在事件检测和分类,各种数学变换的应用以及基于规则的专家系统的实施中发挥作用,并将对其进行研究。我们将进一步集中于对几种实现方法的审查,并介绍现有实现的性能比较。还概述了未来研究的建议。这篇综述为研究人员将来在不同体系结构之间进行比较研究开辟了道路,并为开发更强大和灵活的结构提供了参考。

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