GB/T 18487.2-2017 adds new specific requirements for low-frequency electromagnetic radiation emission of charging pile equipment,but a large amount of test data is only recorded and presented in the form of"frequency-amplitude"two-dimensional data table.To visually obtain the distribution characteristics and trends of low-frequency radiation nuisance of direct current charging piles in large samples,the analysis method of data pivot is used to analyze the large sample data.The direct current charging pile keywords are used as information tags,and the test data are filtered and sorted,categorized and summarized,and interactively queried for the information tags.The statistical characteristics of the large-sample data are presented through data visualization methods such as plane projection,histogram,and internalized magnitude probability distribution,etc.The data pivot approach is used to analyze the low-frequency radiation characteristics of direct current charging piles,and the statistical law of the sample data can be obtained intuitively.The law can provide intuitive reference basis for the statistics of product characteristics and improve product performance.The data pivot analysis approach is also applicable to the statistical characterization analysis of other test data.
关键词
直流充电桩/低频辐射发射/电磁兼容/数据透视/区间化/幅度概率分布/数据统计特性
Key words
Direct current charging pile/Low-frequency radiated emissions/Electromagnetic compatibility/Data pivoting/Internalization/Amplitude probability distribution/Statistical properties of data
维普
万方数据