基于遗传算法的SVM决策模型在选煤监控系统中的应用  

Application of SVM Decision Model Based on Genetic Algorithm in Coal Preparation Monitoring System

作　　者：阿伦[1] 齐虎春[1,2] 白艳姝 A Lun;QI Huchun;BAI Yanshu(Inner Mongolia Vocational College of Chemical Engineering,Hohhot 010070,China;National Engineering Laboratory for Cyberlearning and Intelligent Technology,Beijing Normal University,Beijing 100875,China)

机构地区：[1]内蒙古化工职业学院,呼和浩特010070 [2]北京师范大学互联网教育智能技术及应用国家工程实验室,北京100875

出　　处：《煤炭技术》2022年第9期243-245,共3页Coal Technology

基　　金：内蒙古自治区高等学校科学研究项目(NJZY19280)。

摘　　要：选煤设备工作任务重,强度大,采用信息化的技术对选煤设备进行监控有利于保障选煤设备的可靠运转。对选煤设备的结构层次进行分析,构建选煤监控系统整体结构,设计系统硬件以及通信方式,以跳汰过程的监控为例采用GA-SVM判断跳汰过程的状态。测试了不同个数用户下系统的性能以及GA-SVM的诊断准确率,测试结果显示系统的性能可满足使用要求。The work of the coal preparation equipment is heavy and intensive. The use of information technology to monitor the coal preparation equipment is conducive to ensuring the reliable operation of the coal preparation system. The structure level of coal preparation equipment is analyzed, the overall structure of coal preparation monitoring system is constructed, the system hardware and communication mode are designed, and GA-SVM is used to judge the state of the jigging process by taking the monitoring of the jigging process as an example. The performance of the system under different numbers of users and the diagnostic accuracy of GA-SVM are tested, and the test results show that the performance of the system can meet the requirements of use.

关 键 词：GA-SVM 选煤 跳汰 松散度 

分 类 号：TD94[矿业工程—选矿]