摘要
针对电器设备维修存在的故障诊断精度低、维修决策效率差等问题,提出了一种基于5G-IoT和数字孪生技术的维修方法。该方法利用5G网络的高带宽特性,通过多模态传感器实时采集设备运行数据;构建了设备数字孪生模型,实现物理设备与虚拟模型的动态映射,并进行故障诊断与维修决策。实验结果表明,该方法有效提升了故障检测率,有助于推动电器维修的数字化转型。
To address low fault diagnosis accuracy and inefficient maintenance decisions in electrical equipment maintenance,this paper proposes a maintenance method based on 5G-IoT and digital twin technology.The method utilizes 5G′s high bandwidth for real-time data collection through multimodal sensors,constructs a digital twin model for dynamic mapping between physical and virtual equipment,and performs fault diagnosis and maintenance decisions.Experimental results demonstrate enhanced fault detection rates,facilitating the digital transformation of electrical maintenance.
作者
章盛江
ZHANG Shengjiang(Zhejiang Haining Rail Transit Operation Management Co.,Ltd.,Haining 314400,China)
出处
《电工技术》
2025年第22期122-124,共3页
Electric Engineering
