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Fault detection of univariate non-Gaussian data with Bayesian network

机译:贝叶斯网络对单变量非高斯数据的故障检测

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The purpose of this article is to present a new method for fault detection with Bayesian network. The interest of this method is to propose a new structure of Bayesian network allowing to detect a fault in the case of a non-Gaussian signal. For that, a structure based on Gaussian mixture model is proposed. This particular structure allows to take into account the non-normality of the data. The effectiveness of the method is illustrated on a simple process corrupted by different faults.
机译:本文的目的是提出一种使用贝叶斯网络进行故障检测的新方法。该方法的目的是提出一种贝叶斯网络的新结构,该结构允许在非高斯信号的情况下检测故障。为此,提出了一种基于高斯混合模型的结构。这种特殊的结构允许考虑数据的非正常性。该方法的有效性在被不同故障破坏的简单过程中得到了说明。

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