Due to multiple factors such as external environmental pollution,improper operation,and equipment fouling,quality issues such as performance and appearance may occur during paper production,which can affect the effectiveness of paper use and reduce economic benefits. It can be seen that paper production quality inspection is a crucial link in the papermaking process. However,the real-time effect of traditional manual paper production quality inspection methods is not ideal and the efficiency is relatively low. Therefore,it is urgent to introduce automated inspection methods to improve inspection efficiency,stabilize inspection levels,and reduce manual consumption. This article collects preprocessed data through near-infrared spectroscopy,builds a model based on SVM algorithm,and selects appropriate penalty coefficients and function parameters to achieve automated detection of paper production quality. This algorithm not only reduces the number of model parameters and training sample requirements,but is also suitable for quality inspection in small batch paper production. Moreover,it has high detection efficiency and accuracy,and excellent comprehensive performance.
关键词
SVM算法/纸张生产质量/表观质量/性能缺陷/自动化检测
Key words
SVM algorithm/paper production quality/apparent quality/performance defects/automated detection
维普
万方数据