摘要
目前振动筛运行状态主要依靠人工经验判断,现有在线监测方法因测量精度低,难以满足大型振动筛的智能化发展需求。为此,开发了振动筛运行状态在线监测系统,对该系统的构成与主要功能进行了概述;针对传统单轴或普通三轴单方向振动传感器准确性差的技术难题,建立了振动筛虚拟空间三维坐标系,利用运动矢量合成算法重构了筛机监测位点的实际振动方向角与振动强度,克服了传感器安装精度和现场工况条件对结果的影响,实现了筛机振动数据的精准测量;根据温度传感器实时数据获取轴承温升曲线,实现了温度数据的精准感知;通过对异常数据的分析,基于支持向量机建立了振动筛运行异常与预警模型。现场应用表明,在线监测系统实现了振动筛运行状态数字化判识与早期故障预警,显著降低了筛分装备故障率,保障设备高效稳定运行。
The operation status monitoring of vibrating screen is mainly based on manual experience currently,and the traditional online monitoring methods are difficult to meet the intelligent needs of large-scale vibrating screen due to the poor accuracy.On the basis,an running status online monitoring system for vibrating screen was developed,and the its composition and main functions were outlined.To overcome the technical problems of poor accuracy of traditional single-axis or three-axis single-direction vibration sensors,a virtual space three-dimensional coordinate system was established for the vibrating screen.The motion vector synthesis algorithm was used to reconstruct the actual vibration direction angle and vibration intensity of the monitoring sites of the screen,overcoming the influence of the sensor installation accuracy and on-site working conditions on the monitoring results,and achieving accurate measurement of screen machine vibration data.By using the temperature sensors,the temperature curve of the bearing was obtained,which realized the accurate perception of temperature data.Based on real-time data from temperature sensors,the bearing temperature rise curve was obtained,achieving precise perception of temperature data.By analyzing abnormal data,a vibration screen operation anomaly and early warning model was established based on support vector machine.The on-site application showed that the online monitoring system has achieved digital recognition and early fault warning of the running status of the vibrating screen,significantly reducing the failure rate of screening equipment and ensuring efficient and stable operation of the equipment.
作者
黄涛
于洋
徐文彬
赵静
侯运
赵环帅
段晨龙
HUANG Tao;YU Yang;XU Wenbin;ZHAO Jing;HOU Yun;ZHAO Huanshuai;DUAN Chenlong(School of Chemical Engineering and Technology,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China;Anshan Anzhong Mining Machinery Co.,Ltd.,Anshan,Liaoning 114042,China;Anshan Lishan District Civil Affairs Mine Spare Parts Factory,Anshan,Liaoning 114042,China;Ansteel Steelmaking Plant,Anshan,Liaoning 114042,China;School of Chemical and Environmental Engineering,China University of Mining and Technology-Beijing,Haidian,Beijing 100083,China)
出处
《中国煤炭》
北大核心
2024年第4期91-96,共6页
China Coal
关键词
选煤厂
大型振动筛
运行状态
在线监测
故障预警
coal preparation plants
large-scale vibrating screen
running status
online monitoring
fault early warning
