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某医药企业生产制造产线上有诸多设备，对设备进行故障诊断对于药品生产有着重要意义，对此提出一种基于数字孪生的设备故障诊断及应用方法。构建了基于数字孪生的设备管理故障诊断及图谱构建系统框架，利用深度学习算法建立了设备故障诊断模型并验证了模型的有效性。构建了设备管理数据的知识图谱并进行问答应用，验证了框架的有效性和可行性，为企业设备的故障诊断和管理提供了重要支撑。
Abstract：A pharmaceutical company has many devices on its manufacturing line, and fault diagnosis of the devices is of great importance for drug production. This paper proposes a digital twin equipment fault diagnosis and application method. A framework of equipment management fault diagnosis and mapping system based on digital twin is constructed, and a equipment fault diagnosis model is established and its validity is proved. A knowledge graph of equipment management data is constructed and a question-and-answer application is conducted to verify the effectiveness and feasibility of the framework.
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基本信息:
中图分类号:TP277;TQ460.5
引用信息:
[1]陈雪军,梁川,李志博.数字孪生驱动的企业设备故障诊断及应用研究[J].微型电脑应用,2025,41(04):45-49.
基金信息:
江西省科技厅2022年重大研发专项03及5G项目(20224ABC03A15)
2025-04-20
2025-04-20