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首页> 外文期刊>Research journal of applied science, engineering and technology >A Comparative Study about the Effectiveness of Observers and Bayesian Belief Networks for the Fault Detection and Isolation in Power Electronics
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A Comparative Study about the Effectiveness of Observers and Bayesian Belief Networks for the Fault Detection and Isolation in Power Electronics

机译:电力电子设备故障检测与隔离的观测者与贝叶斯信念网络有效性比较研究

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摘要

The aim of this study is to highlight the capabilities of Bayesian Belief Network (BBN) in the domain of Fault Detection and Isolation (FDI) in DC/DC converter. Reliable electrical supplying systems are those which can provide continuously electrical energy to the consumers. This continuity requires fault free processes during all the phases of energy production, transfer and conversion. In order to achieve a fault free process it is mandatory to have an FDI system that holds on the faulty cases. In this study a Bayesian Naive Classifier (BNC) structure was selected and used as a first attempt to use BBNs for DC/DC power converter FDI.
机译:这项研究的目的是强调DC / DC转换器中故障检测和隔离(FDI)领域中的贝叶斯信念网络(BBN)的功能。可靠的电力供应系统是可以连续地向用户提供电能的系统。这种连续性要求在能源生产,转移和转换的所有阶段都实现无故障的过程。为了实现无故障的过程,必须拥有一个能够保留故障案例的FDI系统。在这项研究中,选择了贝叶斯朴素分类器(BNC)结构,并将其作为将BBN用于DC / DC电源转换器FDI的首次尝试。

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