摘要
针对电能质量扰动识别准确率低的问题,提出基于同态滤波优化二维离散正交S变换振幅图像的电能质量扰动识别方法。首先把一维的扰动信号映射为等行列的二维信号,将二维离散正交S变换方法应用到二维扰动信号中,通过时频变换出振幅矩阵,进行振幅矩阵的同态滤波优化处理,随后对特征块分别提取相关特征,最终使用支持向量机进行分类。实验结果表明,优化的同态滤波+二维离散正交S变换方法相较原二维离散正交S变换方法对电能质量扰动识别准确率有显著提升,同时识别效率和抗噪性更强。
To address the problem of low accuracy of power quality disturbance recognition,a power quality disturbance recognition method based on homomorphic filtering optimized two-dimensional discrete orthogonal S-transform amplitude image was proposed.Firstly,the one-dimensional perturbation signal was mapped to a two-dimensional signal with equal ranks,the two-dimensional discrete orthogonal S-transform method was applied to the two-dimensional perturbation signal,the amplitude matrix was derived by timefrequency transformation.Then the homomorphic filtering optimization of the amplitude matrix was performed,and the relevant features were extracted separately for the feature blocks.Finally the support vector machine was used for classification.The experimental results show that the optimized homomorphic filtering+twodimensional discrete orthogonal S-transform method has significantly improved the accuracy of power quality disturbance recognition compared with the original two-dimensional discrete orthogonal S-transform method,while the recognition efficiency and noise immunity are stronger.
作者
刘辉
黄海林
唐珊珊
LIU Hui;HUANG Hailin;TANG Shanshan(Department of Intelligent Manufacturing,Anhui Vocantional and Technical College,230011,Hefei,Anhui,China;China National Building Materials Group Anhui Resource Saving&Environmental Technology Co.,Ltd,230088,Hefei,Anhui,China)
出处
《淮北师范大学学报（自然科学版）》
CAS
2023年第2期50-57,共8页
Journal of Huaibei Normal University：Natural Sciences
基金
安徽省高校自然科学基金项目(KJ2020A1035)。
关键词
电能质量扰动
同态滤波
二维离散正交S变换
支持向量机
power quality
homomorphic filter
two-dimensional discrete orthonormal S transform
support vector machine
