刮板输送机负载预测及变频调速研究

Research on Load Prediction and Variable Frequency Speed Regulation of Scraper Conveyor

本文以煤矿中经常使用的SGZ1250/2400型刮板输送机为研究对象,在分析减速器齿轮啮合频率信息与负载大小之间的关系的基础上,基于卷积神经网络技术预测刮板输送机的负载。经验证其具有良好的预测精度,可将误差控制在5%范围内。基于负载预测结果,利用模糊PID控制技术对刮板输送机的运行速度进行变频调速。经实践测试,系统达到了预期效果,设备故障率降低10%,能源消耗降低15%,经济效益和安全效益显著提高。

In this paper,the SGZ1250/2400 scraper conveyor,which is often used in coal mines,is taken as the research object.On the basis of analyzing the relationship between the gear meshing frequency information of the reducer and the load,the load of the scraper conveyor is predicted based on Convolutional neural network technology.After verification,it was found that it has good prediction accuracy,and the error can be controlled within the range of 5%.Based on the load prediction results,the fuzzy PID control technology is used to perform variable frequency speed regulation on the operating speed of the scraper conveyor.After practical testing,the system has achieved the expected results,reducing equipment failure rate by 10%,energy consumption by 15%,and significantly improving economic and safety benefits.