通过船舶电力系统中电力电子元件的自动监测来诊断和定位故障的机器学习技术

2009 IEEE Electric Ship Technologies Symposium Pub Date : 2009-04-20 DOI:10.1109/ESTS.2009.4906553

A. J. Mair, E. Davidson, S. Mcarthur, S. Srivastava, K. Schoder, D. Cartes

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引用次数: 18

摘要

船舶中压交流(MVAC)和中压直流(MVDC)电力系统架构在故障条件下的管理和控制提出了许多挑战。在网状配电体系结构中，多个电力电子元件的使用及其相互作用可能导致整个系统都能检测到故障的影响，例如，在具有高电阻接地的直流系统中，线路到船体的故障。

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Machine learning techniques for diagnosing and locating faults through the automated monitoring of power electronic components in shipboard power systems

The management and control of shipboard medium voltage AC (MVAC) and medium voltage DC (MVDC) power system architectures under fault conditions present a number of challenges. The use and resulting interaction of multiple power electronic components in mesh-like power distribution architectures possibly result in the effects of faults being detectable throughout the system, for example, line-to-hull faults on DC systems with high resistive grounding.

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2009 IEEE Electric Ship Technologies Symposium

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