摘要
Abstract
With the development of high-frequency switching technology,the application of a large number of power electronic equipment not only leads to low-frequency harmonic emission,but also causes supraharmonic emission in the range of 2～150 kHz,which brings more and more problems such as high-frequency electromagnetic interference.The supraharmonic signals have a wide distribution bandwidth and small amplitude.In actual engineering applications,the sampling frequency requirements for such signals are high,and the amount of data generated is large.Existing detection algorithms are difficult to simultaneously take into account the requirements of low data storage capacity and high-frequency domain resolution.In order to solve this contradiction,according to the outlier characteristics of supraharmonic signals,on the basis of the skewed distribution model,combined with the improved Density-based Spatial Clustering of Applications with Noise(DBSCAN)algorithm,a new supraharmonic accurate quantization algorithm,Skewed Distribution Density-Based Spatial Clustering of Applications with Noise(SD-DBSCAN),is proposed.The resolution of the detection results of the algorithm can reach 5 Hz,and the data volume is less than 0.05%of the original spectrum,which can meet the requirements of high resolution and low data volume at the same time.Finally,the effectiveness of the proposed algorithm is demonstrated through simulation and testing platforms.Based on the algorithm proposed,a new method and technology for monitoring and measuring the impact of supraharmonic emissions can be explored and developed,providing a theoretical basis and practical experience for research in the field of supraharmonic generation.关键词
高频电磁干扰/超高次谐波检测/离群点检测/DBSCAN算法Key words
high-frequency electromagnetic interference/supraharmonic detection/outlier detection/DBSCAN algorithm分类
信息技术与安全科学
