基于贝叶斯网络的精密医疗设备故障诊断研究  

Research on fault diagnosis of hospital precision medical equipment based on Bayesian network

作　　者：朱婷婷 叶真 金鑫 ZHU Tingting;YE Zhen;JIN Xin(Seventh People’s Hospital of Shanghai University of TCM,Shanghai 200137,China)

机构地区：[1]上海中医药大学附属第七人民医院,上海200137

出　　处：《电子设计工程》2025年第4期184-187,共4页Electronic Design Engineering

摘　　要：为提升精密医疗设备的运行可靠性,提出基于贝叶斯网络的精密医疗设备故障诊断方法。精密医疗设备故障主要包括机械故障、电路故障、操作不当故障、老化磨损故障以及软件故障五种类型。采集精密医疗设备运行信号,提取所采集设备运行信号的故障特征,依据所提取的设备故障特征,通过完成训练的贝叶斯网络实现医院精密医疗设备的故障诊断。贝叶斯网络通过确定节点数量以及节点状态、构建有向无环图、贝叶斯网络参数学习以及贝叶斯网络推理四部分实现故障诊断。将该方法应用于医院的全自动血液细胞分析仪中,验证该方法可以诊断医院精密医疗设备的机械故障、电路故障等不同类型故障,提升精密医疗设备的运行可靠性。Research the fault diagnosis method of hospital precision medical equipment based on Bayesian network,and improve the operation reliability of hospital precision medical equipment.The failures of precision medical equipment in hospitals mainly include five types:mechanical failures,circuit failures,improper operation failures,aging and wear failures,and software failures.The operation signal of precision medical equipment is collected,and the fault characteristics of the collected equipment operation signal are extracted.According to the extracted equipment fault characteristics,the fault diagnosis of hospital precision medical equipment is realized through the Bayesian network that completes the training.The Bayesian network realizes fault diagnosis through four parts:determining the number of nodes and node status,constructing a directed acyclic graph,learning Bayesian network parameters,and Bayesian network inference.The method was applied to the automatic blood cell analyzer in a hospital,and it was verified that the method can diagnose different types of faults such as mechanical faults and circuit faults of the hospital’s precision medical equipment,and improve the operation reliability of the hospital’s precision medical equipment.

关 键 词：贝叶斯网络 精密医疗设备 故障诊断 机械故障 电路故障 

分 类 号：TN929[电子电信—通信与信息系统]