基于人工鱼群算法的混凝土锯切力预测模型  

Prediction Model of Concrete Sawing Force Based on Artificial Fish Swarm Algorithm

作　　者：陈波 熊飞翔[1,2] 王艳 CHEN Bo;XIONG Fei-xiang;WANG Yan(College of Mechanical Engineering,Guangxi University,Nanning Guangxi 530004,China;Guangxi Key Lab of Manufacturing System&Advanced Manufacturing Technology,Guangxi University,Nanning Guangxi 530004,China)

机构地区：[1]广西大学机械工程学院,广西南宁530004 [2]广西大学广西制造系统与先进制造技术重点实验室,广西南宁530004

出　　处：《装备制造技术》2018年第1期11-14,21,共5页Equipment Manufacturing Technology

基　　金：国家自然科学基金资助项目(编号:51565005);广西有色金属及特色材料加工重点实验室开放课题基金项目(No.GXKFJ16-16);广西制造系统与先进制造技术重点实验室资助项目(12-071-11S07)

摘　　要：利用人工鱼群算法的基本原理,并根据金刚石锯片锯切混凝土的实验数据,建立金刚石锯片干切混凝土锯切力的预测模型,对比实验实测数据与预测模型,验证基于人工鱼群算法的混凝土锯切力预测模型的可行性。结果表明:人工鱼群算法预测锯切力与实验锯切力相比,平均相对误差只有2.58%,证明了所建立预测模型的准确性;人工鱼群算法的预测精度比多元回归分析法更高;由锯切力公式可知,影响锯切力的最主要因素为锯切深度,其次为进给速度,锯片的转速对锯切力影响较小。Abstract:In this paper,a prediction model for sawing force of diamond saw blade dry cutting concrete is estab原lished based on the basic principle of artificial fish swarm algorithm and the experimental data of diamond saw blade sawing concrete.Compared with the experimental data and prediction model,the feasibility of the prediction model of the concrete sawing force based on artificial fish swarm algorithm is verified.The results show that the av原erage relative error is only 2.58%when the predicted sawing force compared with the experimental sawing force,which proves the accuracy of the predicted model.The prediction accuracy of artificial fish swarm algorithm is higher than that of multiple regression method.It is known from the sawing force formula that the most important factor affecting the sawing force is the sawing depth,and the second is the feed speed,and the speed of the saw blade has little influence on the sawing force.

关 键 词：人工鱼群算法 混凝土 锯切力 预测模型 

分 类 号：TU528[建筑科学—建筑技术科学]