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首页> 外文期刊>International journal of RF and microwave computer-aided engineering >Detection and classification of complex power quality disturbancesrnusing S‐transform amplitude matrix–based decision tree forrndifferent noise levels
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Detection and classification of complex power quality disturbancesrnusing S‐transform amplitude matrix–based decision tree forrndifferent noise levels

机译：使用基于S变换幅度矩阵的决策树对复杂噪声质量进行复杂功率质量扰动的检测和分类

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This paper presents a simple and effective method for detection of complex powerrnquality disturbances using S‐transform amplitude matrix. In this work, classificationrnof complex power quality disturbances has been implemented using a rule‐basedrndecision tree for different noise levels, such as with no noise, 30‐dB noise, andrn45‐dB noise. The S‐transform is distinct, which provides a frequency‐dependentrnresolution with direct relationship to the Fourier spectrum. The features obtainedrnfrom S‐transform amplitude matrix are dissimilar, clear, and immune to noise.rnAccording to a rule‐based decision tree, 7 types of single power disturbance andrn16 types of complex power disturbance are well identified in this work. Thernproposed work is simulated using MATLAB simulation, and the various resultsrnare found, which detect the single and complex power quality disturbances; and itrnproves that the proposed method is effective and unaffected against noise
机译：本文提出了一种使用S变换幅度矩阵检测复杂功率质量扰动的简单有效方法。在这项工作中，已经针对不同的噪声水平（例如无噪声，30 dB噪声和rn45 dB噪声）使用基于规则的决策树实现了复杂的电能质量扰动分类。 S变换是独特的，它提供与频率相关的分辨率，并与傅立叶频谱直接相关。从S变换幅度矩阵获得的特征不相似，清晰且不受噪声影响。根据基于规则的决策树，可以很好地识别7种类型的单一功率干扰和16种类型的复杂功率干扰。利用MATLAB仿真对提出的工作进行了仿真，发现了各种结果，可以检测出单一和复杂的电能质量扰动。并证明了所提方法是有效的并且不受噪声影响

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