通讯机构：
[Wang, Rongji] C;Cent South Univ Forestry & Technol, Coll Mech & Elect Engn, Changsha 410004, Hunan, Peoples R China.
关键词：
back propagation artificial neural network;injection molding process;process parameters;warpage
摘要：
A back propagation artificial neural network (BPANN) prediction model for warpage of injection-molded polypropylene was developed based on an orthogonal design method. The BPANN model was trained by the input and output data obtained from the moldflow software platform simulations. It is proved that the BPANN model can predict the warpage with reasonable accuracy. Utilizing the BPANN model, the effects of the process parameters, packing pressure (Pp), melt temperature (Tme), mold temperature (Tmo), packing time (tp), cooling time (tc), and fill pressure (pf), on the warpage were investigated. The most important process parameter affecting the warpage was Pp, and the second most important was Tme. The rest of the process parameters, Tmo, tp, tc, and pf, were found to be relatively less influential. Warpage increased with elevating Tmo. In contrast, an increase in Pp and Tme caused the warpage to decrease.
作者机构：
[高自成; 李立君; 闵淑辉; 阳涵疆; 周鹰; 祝强] Mechanical and Electrical Engineering Institute, Central South University of Forestry and Technology, Changsha, China
通讯机构：
Mechanical and Electrical Engineering Institute, Central South University of Forestry and Technology, Changsha, China
作者机构：
[李立君; 赵兵; 文韬; 张仟仟; 刘付] School of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha, China;[郭鑫] School of Science, Central South University of Forestry and Technology, Changsha, China;[洪添胜] Division of Citrus Machinery, China Agriculture Research System, Guangzhou, China;[洪添胜; 文韬] Key Laboratory of Key Technology for South Agricultural Machinery and Equipment, Ministry of Education, Engineering College of South China Agricultural University, Guangzhou, China
通讯机构：
Key Laboratory of Key Technology for South Agricultural Machinery and Equipment, Ministry of Education, Engineering College of South China Agricultural University, Guangzhou, China
期刊：
Advance Journal of Food Science and Technology,2014年6(1):130-134 ISSN：2042-4868
通讯作者：
Li, L.
作者机构：
[Lijun Li; Ye Xue; Jian Zhou] Machinery and Electrical Engineering College, Centre South University of Forestry Science and Technology, Changsha, 410004, China
通讯机构：
[Li, L.] M;Machinery and Electrical Engineering College, Centre South University of Forestry Science and Technology, China
作者机构：
[文韬; 李立君] College of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha, China;[郭鑫] College of Science, Central South University of Forestry and Technology, Changsha, China;[张南峰] Guangzhou Entry-exit Inspection and Quarantine, Guangzhou, China;[洪添胜; 李震] Division of Citrus Machinery, China Agriculture Research System, Guangzhou, China;[李震; 洪添胜; 文韬] Key Laboratory of Key Technology for South Agricultural Machinery and Equipment, College of engineering, South China agricultural University, Guangzhou, China
通讯机构：
Key Laboratory of Key Technology for South Agricultural Machinery and Equipment, College of engineering, South China agricultural University, Guangzhou, China
作者机构：
[文韬; 李立君] College of Mechanical and Electrical Engineering, Central South University of Forestry and Technology, Changsha 410004, China;[叶智杰; 张彦晖] College of Engineering, Hong Kong University of Science and Technology, Hong Kong;[洪添胜; 李震] Division of Citrus Machinery, China Agriculture Research System, Guangzhou 510642, China;[叶智杰; 李震; 洪添胜; 文韬] Key Laboratory of Key Technology on Agricultural Machinery and Equipment, Ministry of Education, Engineering College of South China Agricultural University, Guangzhou 510642, China
通讯机构：
Key Laboratory of Key Technology on Agricultural Machinery and Equipment, Ministry of Education, Engineering College of South China Agricultural University, China
关键词：
监测;害虫防治;试验;植保;橘小实蝇;光电监测
摘要：
为了解决现有的害虫机器监测技术与传统的监测手段结合存在的实时监测难度高、信息处理困难、成本高等问题,该文设计研发一种适用于果园环境的橘小实蝇成虫诱捕监测装置用于监测橘小实蝇成虫虫口密度。该装置外观由遮光罩、进虫口、虫口监测区和储虫瓶构成,信号检测模块包括红外光电耦合传感器匹配电路、电压跟随器电路、差分放大电路和迟滞比较器电路4部分。性能测试结果表明:该诱捕监测装置底部储虫瓶有、无遮光处理时,相应的感应电压均值分别为3.923和3.883 V,差异显著(P<0.05),且上述2种方式均能使检测探头输出工作在线性区域;虫口监测通道管壁设计成黑、白、蓝3色,在自然光照条件下,管壁颜色对监测探头感应性能无显著差异性(P=0.606);监测区域不同区域位置感应输出响应也无显著差异性(P=0.797),区域位置对监测输出误差影响可以忽略。应用该诱捕监测装置和人工计数方式在橘小实蝇成虫发生高峰期连续5 d 24 h监测成虫虫口密度,结果表明该装置监测相对误差为3%~8%,相比传统的人工计数方式,具有实时、自动化监测的优点,能够满足现有的橘小实蝇成虫长时期数据动态监测的需求,适用于果园橘小实蝇成虫动态监测推广使用。
