In response to the challenges of maintenance difficulty,high costs,and long cycles in pharmaceutical glassware production equipment,this paper introduces digital twin technology to construct a digital twin operation and maintenance system for fault diagnosis of pharmaceutical glassware inspection equipment.This system aims to achieve virtual monitoring of the pharmaceutical glassware production line,prediction of key component status,and coordinated decision-making.Digital twin models for pharmaceutical glassware inspection equipment are built based on the characteristics of the equipment.To address data perception anomalies resulting from inconsistent module protocols in physical devices,a standardized communication protocol for pharmaceutical glassware inspection equipment is established using OPC UA.Subsequently,employing an architecture pattern that combines virtual and real data fusion,heterogeneous data from multiple sources are fused using similarity mapping fusion rules,followed by subsequent data analysis and processing.Features are input into the HSMM prediction model,and combined with a fuzzy expert system for fault identification analysis of pharmaceutical glassware equipment,providing final equipment maintenance recommendations.Simulation experiments demonstrate that the designed system accurately reflects the operational status of physical equipment and evaluates equipment status using a large number of data samples.
关键词
数字孪生/故障诊断/OPC/UA/数据融合/专家系统
Key words
digital twin/fault diagnosis/OPC UA/data fusion/expert system
维普
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