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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 disturbancesusing S‐transform amplitude matrix–based decision tree fordifferent noise levels
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Detection and classification of complex power quality disturbancesusing S‐transform amplitude matrix–based decision tree fordifferent noise levels

机译：复杂电能质量障碍的检测与分类使用基于S转换幅度矩阵的决策树不同的噪音水平

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This paper presents a simple and effective method for detection of complex powerquality disturbances using S‐transform amplitude matrix. In this work, classificationof complex power quality disturbances has been implemented using a rule‐baseddecision tree for different noise levels, such as with no noise, 30‐dB noise, and45‐dB noise. The S‐transform is distinct, which provides a frequency‐dependentresolution with direct relationship to the Fourier spectrum. The features obtainedfrom S‐transform amplitude matrix are dissimilar, clear, and immune to noise.According to a rule‐based decision tree, 7 types of single power disturbance and16 types of complex power disturbance are well identified in this work. Theproposed work is simulated using MATLAB simulation, and the various resultsare found, which detect the single and complex power quality disturbances; and itproves that the proposed method is effective and unaffected against noise
机译：本文提出了一种简单有效的复杂功率方法使用S转换幅度矩阵的质量扰动。在这项工作中，分类复杂的电能质量扰动已经使用基于规则实现的决策树不同噪声水平，例如没有噪声，30-dB噪声，和45-dB噪音。 S-Transform是不同的，它提供频率依赖性解决与傅里叶谱的直接关系。获得的功能从S变换振幅矩阵异常，清晰，免受噪音。根据基于规则的决策树，7种单功率干扰和在这项工作中，16种复杂的电力干扰是很好的。这使用MATLAB仿真模拟所提出的工作，以及各种结果被发现，检测单一和复杂的电能质量障碍;它证明所提出的方法有效，不受噪音影响

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