摘要
针对工业现场环境复杂干扰导致工控机对运输设备监测精度不足的问题,本文以工控机中破碎机、转载机、输送机为研究对象,提出一种基于麻雀搜索算法优化支持向量机(Support Vector Machine,SVM)的工控机监测系统。首先,基于系统需求分析,将系统整体框架设计为数据采集、数据传输与处理、故障诊断、可视化展示4个模块;其次,完成了工控机、传感器及电源等关键硬件的选型,并采用MDTP通讯协议,设计了以麻雀搜索算法改进的SVM为核心算法的故障诊断软件模块;最后,通过仿真实验与系统测试对方案进行了验证。实验结果表明,改进后的SVM算法对工控机中破碎机、转载机及输送机的故障诊断准确率达到98.33%,相较于其他故障诊断算法提升了约7%;系统测试证实了硬件选型的合理性、软件运行的稳定性以及MDTP协议在数据传输方面的高效性。综上所述,该系统有效解决了复杂环境下的监测难题,显著提升了工控机对运输设备的监测精度与可靠性。
In response to the problem of insufficient monitoring accuracy of transportation equipment by industrial personal computers caused by complex environmental interference on industrial sites,this paper takes crushers,transfer machines,and conveyors in industrial control computers as research objects,and proposes an industrial personal computer monitoring system based on a support vector machine(SVM)optimized by the sparrow search algorithm(SSA).Firstly,based on system requirements analysis,the overall framework of the system is designed into four modules:data acquisition,data transmission and processing,fault diagnosis,and visualization display.Secondly,the selection of key hardware such as industrial personal computers,sensors,and power supplies was completed,and the MDTP communication protocol was adopted to design a fault diagnosis software module with the SSA-improved SVM serving as the core algorithm.Finally,the scheme was validated through simulation experiments and system testing.The experimental results show that the improved SVM algorithm achieves a fault diagnosis accuracy of 98.33%for crushers,transfer machines,and conveyors,which is about 7%higher than other fault diagnosis algorithms;system testing has confirmed the rationality of hardware selection,the stability of software operation,and the efficiency of MDTP protocol in data transmission.In summary,the system effectively solves the monitoring problem in complex environments and significantly improves the monitoring accuracy and reliability of industrial personal computers for transportation equipment.
作者
王宏伟
崔军军
段军军
常圣强
WANG Hongwei;CUI Junjun;DUAN Junjun;CHANG Shengqiang(Shanxi Yamei Daning Energy Co.,Ltd.,Jincheng 048000,China;China National Coal Group Corp.,Beijing 100120,China;China National Coal Mining Equipment Co.,Ltd.,Beijing 100011,China)
出处
《国外电子测量技术》
2026年第2期265-270,共6页
Foreign Electronic Measurement Technology
基金
中国中煤重大科技专项(20221BY003)。
关键词
工控机
MDTP协议
运输设备
SVM算法
麻雀搜索算法
industrial personal computer
MDTP protocol
transportation equipment
SVM algorithm
sparrow search algorithm
