The problems of the bobbin capacity and the high speed unwinding yarn taking off the ring or not during the winding of the ring spinning machine were dealt with. The mathematical model of the ring winding machine moti...The problems of the bobbin capacity and the high speed unwinding yarn taking off the ring or not during the winding of the ring spinning machine were dealt with. The mathematical model of the ring winding machine motion law was analyzed and optimized.Through the analysis and study of the movement rule of bottom bobbins and the ring spinning frame spool forming, the mathematical model of active bottom bobbins forming movement was established. Also,the mathematical model of bobbins formation was simulated and optimized. The concept of "controlled nail"was put forward. On this basis,the mathematical model of the current tube forming motion was optimized. The experimental results demonstrated that the theory of"controlled nail"met the high-speed spinning winding theory. The theory of "controlled nail "not only did the capacity of the bobbin increase,but also the spinning speed and efficiency are both improved,reducing the high-speed winder winding off. This research could provide a theoretical basis for the development of a new ring spinning frame.展开更多
当前高速铁路接触网参数检测中,存在开口销体积小、分布分散、故障缺陷识别困难,过度依赖综合检测车等问题。本文提出一种采用无人机航拍,结合图像分割与识别技术的基于更快的区域卷积神经网络(Faster R-CNN)算法实现图像处理和优化,进...当前高速铁路接触网参数检测中,存在开口销体积小、分布分散、故障缺陷识别困难,过度依赖综合检测车等问题。本文提出一种采用无人机航拍,结合图像分割与识别技术的基于更快的区域卷积神经网络(Faster R-CNN)算法实现图像处理和优化,进而对开口销缺陷进行检测识别的方法,有效地提升开口销缺陷识别准确率和有效性。测试结果表明,采用基于Faster R-CNN算法的无人机高速铁路接触网开口销缺陷检测方法的开口销图像缺陷识别准确率可达到98%以上,平均精度约90%,接受者操作特征曲线下的面积(area under curve,AUC)大于0.98。该算法通过软件开发工具包(software development kit,SDK)嵌入到无人机,实现接触网开口销自动巡检、智能识别,为现场作业提供智能化检测设备,提升接触网的智能化检测手段,保障高速铁路安全运行。展开更多
基金National Basic Research Program of China(973 Program)(No.2010CB334711)
文摘The problems of the bobbin capacity and the high speed unwinding yarn taking off the ring or not during the winding of the ring spinning machine were dealt with. The mathematical model of the ring winding machine motion law was analyzed and optimized.Through the analysis and study of the movement rule of bottom bobbins and the ring spinning frame spool forming, the mathematical model of active bottom bobbins forming movement was established. Also,the mathematical model of bobbins formation was simulated and optimized. The concept of "controlled nail"was put forward. On this basis,the mathematical model of the current tube forming motion was optimized. The experimental results demonstrated that the theory of"controlled nail"met the high-speed spinning winding theory. The theory of "controlled nail "not only did the capacity of the bobbin increase,but also the spinning speed and efficiency are both improved,reducing the high-speed winder winding off. This research could provide a theoretical basis for the development of a new ring spinning frame.
文摘当前高速铁路接触网参数检测中,存在开口销体积小、分布分散、故障缺陷识别困难,过度依赖综合检测车等问题。本文提出一种采用无人机航拍,结合图像分割与识别技术的基于更快的区域卷积神经网络(Faster R-CNN)算法实现图像处理和优化,进而对开口销缺陷进行检测识别的方法,有效地提升开口销缺陷识别准确率和有效性。测试结果表明,采用基于Faster R-CNN算法的无人机高速铁路接触网开口销缺陷检测方法的开口销图像缺陷识别准确率可达到98%以上,平均精度约90%,接受者操作特征曲线下的面积(area under curve,AUC)大于0.98。该算法通过软件开发工具包(software development kit,SDK)嵌入到无人机,实现接触网开口销自动巡检、智能识别,为现场作业提供智能化检测设备,提升接触网的智能化检测手段,保障高速铁路安全运行。
