基于机器视觉的整经机断纱检测系统

针对目前纺织行业整经机断纱检测可靠性低、灵敏度差等问题,开发了一款智能相机,实现了基于机器视觉的断纱自动检测系统.系统硬件结构以智能相机为核心,结合可编程逻辑控制器和触摸屏等设备实现机电一体化检测,提高了系统检测的灵敏度.视觉算法将复杂的二维信号转换为一维信号,从一维信号中自适应提取信号的极值,根据极值信号统计纱线根数,得到检测结果.针对现场图片存在噪声干扰的问题,提出基于局部信号相关性判断和极值点修正等信号极值选择方法,提高了系统检测的可靠性.实际应用表明,该断纱检测系统具有较好的检测灵敏度和可靠性,能够有效提高整经机的整经效率.

Broken Yarn Detection System on Warping Machine Based on Machine Vision

For the warping machine broken yarn detection’s reliability is low,and sensitivity is poor in the textile industry,a smart camera is developed,and the broken yarn automated inspection system is realized based on machine vision.Smart camera which is the core of the system,could implement the mechanical and electrical integration testing with the PLC and touch screen,and it could improve the system detection sensitivity.The visual algorithm converted complex two-dimensional signal to one-dimensional signal,and extracted the extreme signals from the one-dimensional signal adaptively.Then the number of the yarn is counted based on extreme signals to get test results.For there is noise disturbance in the pictures,the solutions are proposed to improve the system detection’s reliability,such as relevance judgments based on local signal and extreme point of correction.The practical application shows that the broken yarn detection system has good detection sensitivity and reliability,and can effectively increase the warping machine’s efficiency.