摘要
为避免商标纸堆叠输送装置偏移对识别结果的影响,提出了基于深度学习的商标纸堆叠输送装置异常识别方法。分析输送装置承受的最大拉力,结合定义的输送装置最大瞬时加速度得出其所受载荷值;结合商标纸堆叠变化提取输送装置点位特征,采用基于深度学习的异常状态识别方法识别异常点位。实验结果表明:所提方法识别精度较高,满足商标纸堆叠输送装置的运维需求。
In order to avoid the influence of the offset on the identification results of trademark paper stacking conveyor device,it analyzes the maximum bearing force of the conveying device.Combining the defined maximum instantaneous acceleration of the conveying device,it extracts the characteristics of the point location of the conveying device,and identifies the abnormal state of the abnormal state based on deep learning.The results show that the identification accuracy is high to meet the operation and maintenance requirements of trademark paper stacking conveying device.
作者
陈镕
章韦伟
张志彬
Chen Rong;Zhang Weiwei;Zhang Zhibin(Longyan Tobacco Industrial Co.,Ltd.,Fujian Longyan,364021,China)
出处
《机械设计与制造工程》
2024年第5期130-134,共5页
Machine Design and Manufacturing Engineering
关键词
商标纸堆叠
输送装置
深度学习
装置异常识别
stacking trademark paper
conveying device
deep learning
device anomaly identification
