东华大学学报（英文版）2025，Vol.42Issue(3)：292-300,9.DOI:10.19884/j.1672-5220.202405013
基于机器视觉的浆纱机拥纱故障检测
Fault Detection of Yarn Congestion in Sizing Machine Based on Machine Vision
摘要
Abstract
During the sizing process,yarn congestion fault occurs at the reed teeth of a sizing machine.At present,the yarn congestion fault is generally handled by manual detection.The sizing production line operates on a large scale and runs continuously.Untimely handling of the yarn congestion fault causes a large amount of yarn waste.In this research,a machine vision-based algorithm for yarn congestion fault detection is developed.Through the analysis of the congestion fault and interference contour characteristics,the basic idea of image phase subtraction to identify the congestion fault is determined.To address the interference information appearing after image phase subtraction,the image pre-processing methods of Canny edge extraction and mean filtering are employed.According to the fault size and location characteristics,the fault contour detection algorithm based on inter-frame difference is designed.To mitigate the camera vibration interference,the anti-vibration interference algorithm based on affine transformation is studied,and the fault detection algorithm for the total yarn congestion fault is determined.The detection of 20 sets of field data is carried out,and the detection rate reaches 90％.This fault detection algorithm realizes the automatic detection of yarn congestion fault of sizing machine with certain real-time performance and accuracy.关键词
机器视觉/筘齿拥纱/故障检测/帧间差分/仿射变换Key words
machine vision/yarn congestion/fault detection/inter-frame difference/affine transformation分类
信息技术与安全科学引用本文复制引用
李经纬,邹鲲,赵晨..基于机器视觉的浆纱机拥纱故障检测[J].东华大学学报（英文版）,2025,42(3):292-300,9.基金项目
National Key Research and Development Program of China(No.2017YFB1304001) （No.2017YFB1304001）
