基于PSO-BP神经网络的带式输送机能耗优化研究  

Research on Energy Consumption Optimization of Belt Conveyor Based on PSO-BP Neural Network

作　　者：蒋思中 郭宏涛 安轲[1] 卢丹萍[1] JIANG Sizhong;GUO Hongtao;AN Ke;LU Danping(Guangxi Vocational and Technical College,Nanning 530226,China)

机构地区：[1]广西职业技术学院,南宁530226

出　　处：《煤炭技术》2022年第11期234-236,共3页Coal Technology

基　　金：广西高校中青年教师科研基础能力提升项目(2021KY0985,2020KY29009)。

摘　　要：针对当前带式输送机恒速运行方式能耗较大的问题,设计了一种基于PSO-BP神经网络的带式输送机能耗优化方法。通过分析能耗与输送机运行参数之间的关系,将带速、煤流量作为BP网络的输入,并采用粒子群算法(PSO)对BP网络模型的参数进行优化,获取带速、煤流量与最小能耗三者之间的最佳匹配关系,并以此构建PSO-BP网络模型进行试验。结果表明:该优化方法预测精度较高,满足现实要求;带式输送机采用文中方法作业时,可节省13.85%的能耗,具备较好的稳定性与实践性。Aiming at the problem of large energy consumption of constant speed operation mode of belt conveyor,an energy consumption optimization method of belt conveyor based on PSO-BP neural network is designed.By analyzing the relationship between energy consumption and conveyor operation parameters,taking belt speed and coal flow as the input of BP network,and using PSO algorithm to optimize the parameters of BP network model,the best matching relationship between belt speed,coal flow and minimum energy consumption is obtained,and PSO-BP network model is constructed for test.The results show that the optimization method has high prediction accuracy and meets the practical requirements;when the belt conveyor adopts the method,it can save 13.85%energy consumption,and has good stability and practicality.

关 键 词：PSO-BP神经网络 带式输送机 能耗优化 

分 类 号：TD528[矿业工程—矿山机电]