The invention discloses an intelligent
quality control image analysis system for
textile bobbins, particularly relates to the field of
textile bobbin monitoring, is used for solving the problems of uneven winding and
yarn breakage caused by static accumulation, and is characterized in that a
fusion image is generated through a multispectral
imaging technology; after the
convolutional neural network analyzes the image, an electrostatic accumulation area is automatically identified, the intensity, the rate and the
spatial distribution characteristics are quantized,
time sequence data are fused through an
optical flow algorithm, and the electrostatic intensity level is dynamically updated; when the electrostatic strength reaches a set value, capturing a dynamic track and tension change in the
yarn winding and releasing process by using a corresponding sensor, extracting
yarn offset data, and evaluating the influence of electrostatic interference on winding uniformity and releasing smoothness in combination with tension anomaly analysis; and finally, after the electrostatic strength and the interference analysis result are integrated, a
random forest algorithm is adopted to generate a risk
score, and an early warning mechanism is triggered, so that the
spinning process is optimized, yarn breakage is reduced, the stability and the product quality are improved, and the production efficiency is improved.