Fault detection using topological case based modelimg and its application to chiller performance deterioration

H. Tsutsui, A. Kurosaki, T. Sato, Y. Hiraide
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引用次数: 4

Abstract

We apply a new modeling technique, Topological Case Based Modeling (TCBM), to fault diagnosis. In this paper we propose a new model which represents a continuous input/output relation using a set of numerical data, and it is possible to describe nonlinear systems. We employ the idea of case based reasoning (CBR). CBR infers a new case from stored cases and these relation.[1] It is important to define the similarity, that is a relation among the cases. We propose to define the similarity as the neighbourhood in input space corresponding to output accuracy and its accuracy is arbitrarily set before constructing the model. We name this technique Topological Case Based Modeling. In addition, we describe that TCBM has several advantages over other models. Finally we also show the example of TCBM to detect the deterioration for a chiller system.<>
基于拓扑案例建模的故障检测及其在冷水机组性能劣化中的应用
我们将一种新的建模技术——基于拓扑案例的建模(TCBM)应用于故障诊断。本文提出了一种用一组数值数据表示连续输入/输出关系的新模型,它可以用来描述非线性系统。我们采用基于案例推理(CBR)的思想。CBR从存储的案例和这些关系中推断出一个新的案例。[1]重要的是定义相似度,即案例之间的关系。我们提出将相似度定义为输入空间中与输出精度相对应的邻域,其精度在构建模型之前是任意设置的。我们将这种技术命名为拓扑案例建模。此外,我们描述了TCBM比其他模型有几个优点。最后,我们还展示了TCBM检测冷水机系统劣化的例子。
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