机械科学与技术2026，Vol.45Issue(2)：253-260,8.DOI:10.13433/j.cnki.1003-8728.20240016
数字孪生与神经网络融合驱动的烧成系统故障预警研究
Study on Failure Warning of Firing System Driven by Fusion of Digital Twin and Neural Network
罗昌亮 1毛娅 1陈作炳 1邓宇1
作者信息
- 1. 武汉理工大学 机电工程学院,武汉 430070
- 折叠
摘要
Abstract
Aiming at the difficulty of process fault diagnosis and prediction under the dynamic coupling relationship of the firing system,a digital twin and neural network fusion-driven fault diagnosis and warning method of firing system is proposed by integrating the digital twin with the powerful data analyzing capability of neural network,which is highly characterized by using the interaction between the reality.Based on Unity3D,a digital twin workshop that highly portrays the physical workshop of the firing system is constructed;a failure diagnosis model for firing system based on the extreme learning machine neural network is established,the failure prediction of the firing system equipment driven by real-time monitoring data is realized,and a warning of the failure in the form of a panel in the virtual workshop is made,which provides a new way in thinking for the failure diagnosis and prediction of the firing system,and has important significance for the digital transformation of the cement industry.关键词
数字孪生/神经网络/烧成系统/故障诊断Key words
digital twins/neural network/firing systems/fault diagnosis分类
信息技术与安全科学引用本文复制引用
罗昌亮,毛娅,陈作炳,邓宇..数字孪生与神经网络融合驱动的烧成系统故障预警研究[J].机械科学与技术,2026,45(2):253-260,8.
