基于K-means聚类算法的沥青烟电除尘器火花分析  

Discharge Analysis of Asphalt Fume ESP Based on K-means Cluster Algorithm

作　　者：赵艳平[1] 张艳华[1] 胡伟伟 

机构地区：[1]兰州交通大学电子与信息工程学院,兰州730070 [2]甘肃科近环保技术有限公司,兰州730000

出　　处：《工业安全与环保》2014年第4期31-33,共3页Industrial Safety and Environmental Protection

基　　金：甘肃省青年科技基金(1208RJYA071)

摘　　要：为了保证沥青烟电除尘器的除尘效率、降低除尘设备的火灾风险,采用了K-means聚类的方法分析ESP放电信号。首先将ESP伏安特性曲线的二维空间进行了分割,确定了不同运行状态与聚类中心的关系,然后使用K-means聚类算法计算其聚类中心,最后根据当前ESP输入参数与各个聚类中心欧氏距离的关系,从而判断出ESP是否处于火花放电状态。仿真结果表明该方法可以准确地判断出所有火花放电信号。In order to gumantee the cleaning eficieney of asphalt fume electrostatic precipitator and reduce fire risks of the equipment, the Kmeans duster algorithm is introduced to analyze the discharge signal of ESP. The 2 dimension space of ESP voltage-ampere characteristics is divided into four parts and each part has a cluster center. The center is mapped with the ESP operation status and it can be calculated by K- means algorithm. The ESP status can be detemained according to the Euclidean distances between input parameters and various clustering centers. The simulation result indicates that the method can accurately estimate ESP discharge signals.

关 键 词：电除尘器 沥青烟气 放电信号 K—means聚类算法 

分 类 号：X701.2[环境科学与工程—环境工程]