爆破器材2025，Vol.54Issue(1)：36-40,5.DOI:10.3969/j.issn.1001-8352.2025.01.006
基于深度学习算法的硝酸铵溶液析晶点检测系统
A Detection System for Crystallization Points of Ammonium Nitrate Solution Based on Deep Learning Algorithm
魏周华 1王清华 1何锋军 1党创刚 1田璐 2孙伟博2
作者信息
- 1. 陕西北方民爆集团有限公司(陕西 西安,715600)
- 2. 西安科技大学能源学院(陕西 西安,710054)
- 折叠
摘要
Abstract
An automatic quality detection system for expanded ammonium nitrate aqueous solution was designed based on the on-site conditions of the production line.The accuracy of different deep learning algorithms in determining the crystallization state of ammonium nitrate solution was studied.EfficiencyNet algorithm exhibited the highest accuracy.Effi-ciencyNet algorithm was improved by increasing the number of feature channels in each layer and removing multiple MB-Conv layers in depth.The numbers of parameters were reduced,FLOPs were lowered,and the detection were accelerated.The average error between the automatically measured crystallization point temperature by the system and the manually measured temperature is less than 0.3℃.The results demonstrate that the system can accurately measure the crystalliza-tion temperature and density of ammonium nitrate solution,and automatically generate detection reports for ammonium nitrate solution.At the same time,it can trace and query data,and mark abnormal data,thereby meeting production requirements.关键词
硝酸铵水相溶液/深度学习/析晶点/EfficientNet算法Key words
aqueous solution of ammonium nitrate/deep learning/crystallization point/EfficientNet algorithm分类
化学工程引用本文复制引用
魏周华,王清华,何锋军,党创刚,田璐,孙伟博..基于深度学习算法的硝酸铵溶液析晶点检测系统[J].爆破器材,2025,54(1):36-40,5.
