摘要
基于实验测试结果,设计了倍捻机关键工艺参数与锭子工作性能关系的BP神经网络预测模型,并对锭子功耗和滑差率进行了预测。结果表明:所建BP神经网络模型具有较高的预测精度,且解决了转速滑差率的估算问题,这对指导龙带锭子驱动系统的动力学研究有现实意义,同时为设备的设计和生产运行进一步奠定了理论基础。
This study designs BP neural network prediction model of the relationship between key process parameters of double twister and the working performance of spindle and predicts the power loss of spindle and slip ratio based on the test result of experiment. The result indicates that BP neural network model established has a high prediction accuracy and solves the estimation problem of rotation slip ratio, having practical significance for guiding the research on dynamics of tangential belt spindle driving system and meanwhile further laying a theoretical foundation for the design, production and operation of the equipment.
出处
《现代纺织技术》
2013年第1期13-16,共4页
Advanced Textile Technology
关键词
倍捻机
工艺参数
锭子功耗
转速滑差率
BP神经网络
double twister
process parameters
spindle power loss
rotation slip ratio
BP neural network
