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An improved binary tree algorithm is proposed for the practical problem of the relativity position of the data sets for oil-immersed transformer in the pattern feature space. And a fault diagnosis model of dissolved gas analysis (DGA) based on an improved binary tree multi-class support vector machine (SVM) is constructed. This method overcomes the disadvantage that the traditional binary tree, which...
Fault diagnosis of power transformer is important for safety of the device and relevant power system. In the study, support vector machine(SVM) classifiers combined with the form of binary tree are applied to construct diagnostic model of power transformer, and the diagnostic system structure of power transformer is presented on the basis of the model. SVM is a novel machine learning method based...
This paper presents an on-going project of developing a suite of intelligent diagnostic tools for evaluating power transformer insulation systems. Our ultimate goal is to exploit techniques for automatically processing the measurement data, extracting meaningful information and subsequently transforming the information into domain-specific knowledge which can be utilized for indicating power transformer...
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