التفاصيل البيبلوغرافية
| العنوان: |
基于小波变换和灰度-梯度共生矩阵的局部 放电特征提取及识别. (Chinese) |
| Alternate Title: |
Feature Extraction and Recognition of Partial Discharge Based on Wavelet Transform and GGCM. (English) |
| المؤلفون: |
杨攀烁, 贾文阁, 刘森, 李吉生, 张平, 李旭, 李彬, 安国庆, 安琪, 韩晓慧 |
| المصدر: |
Science Technology & Engineering; 2023, Vol. 23 Issue 27, p11673-11680, 8p |
| Abstract (English): |
In order to make full use of the characteristic information contained in the partial discharge (PD) signal and improve the recognition rate of the partial discharge type in the transformer, a partial discharge type recognition method based on wavelet transform (WT) and gray-gradient co-occurrence matrix (GGCM) algorithm was proposed. According to the internal structure characteristics of the transformer, four types of partial discharge defects were designed, and the transformer partial discharge experimental detection platform was built in the laboratory, and the high-frequency partial discharge current signal was collected by pulse current method. The flexibility of wavelet transform in non-stationary signal processing was used to construct time-frequency spectrum of partial discharge signal pulse. Then, combined with the GGCM algorithm, the 15-dimensional texture features of the time-frequency spectrum were extracted to form the feature vector. Input the feature vector into the support vector machine (SVM) classifier for pattern recognition. The results show that the recognition method combining wavelet transform and GGCM algorithm can effectively identify different types of partial discharge defects. [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
为了能够充分利用局部放电( partial discharge, PD)信号中包含的特征信息,提高变压器内部局部放电类型的识别 率,提出了一种基于小波变换(wavelet transform,WT)和灰度-梯度共生矩阵( gray-gradient co-occurrence matrix,GGCM)算法的 局部放电类型识别方法。 结合变压器内部结构特点,设计四种局部放电缺陷类型,在实验室搭建变压器局部放电实验检测平 台,通过脉冲电流法采集局部放电高频电流信号。 运用小波变换对非平稳信号处理时的灵活性对局部放电信号脉冲构建时 频谱图;然后结合 GGCM 算法提取时频谱图的15 维纹理特征组成特征向量;将特征向量输入到支持向量机(support vector machine,SVM)分类器进行模式识别。 结果表明,小波变换和 GGCM 算法结合的识别方法能够有效地对不同局部放电缺陷类型 进行识别。 [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |