基于贝叶斯网络医学检验仪器故障诊断模型构建方法的研究

曲靖师范学院学报 ›› 2021, Vol. 40 ›› Issue (3): 61-66.

基于贝叶斯网络医学检验仪器故障诊断模型构建方法的研究

张喜红, 王玉香

亳州职业技术学院智能工程系,安徽亳州 236800

收稿日期:2021-04-15 出版日期:2021-05-26 发布日期:2021-07-13
作者简介:张喜红,亳州职业技术学院智能工程系副教授,山东大学访问学者,主要从事计算机技术研究.
基金资助:
安徽省高等学校自然科学研究重大项目“基于微信小程序和人工智能专家系统医学检验仪器故障诊断的应用研究”（KJ2019A1179）; 安徽省高等学校省级质量工程项目“《临床检验仪器》大规模在线开放课程（MOOC）示范项目”（2019mooc442）.

Research on the Method of Medical Instrument Fault Diagnosis Based on Bayesian Network

ZHANG Xihong, WANG Yuxiang

Department of Intelligent Engineering, Bozhou Vocational and Technical College,Bozhou Anhui 236800, China

Received:2021-04-15 Published:2021-05-26 Online:2021-07-13

摘要/Abstract

摘要： 为了解决医学检验仪器因结构复杂、维修资料较少等原因,导致医院设备科工作人员故障排查较难的问题,提出了一种基于维修日志数据分析,构建贝叶斯网络诊断模型的方法.以优利特500B尿液分析仪的故障诊断模型构建为例,详细介绍了运用工具包,基于维修日志数据分析,进行网络结构构建,及网络参数学习的具体实现过程.经实际推理测试实验证明,通过此方法构建的诊断系统,推理结果与实际相符可靠.

关键词: 贝叶斯网络, 尿液分析仪, 故障诊断

Abstract: A Bayesian network fault diagnosis model is established based on analysis of maintenance data in order to solve the problem of testing trouble in medical laboratory equipments resulted from the complicated structure of medical instruments and inadequate maintenance data. The Pgmpy toolkit is introduced based on the analysis of maintanace data, and the process of establishment of network and learning of the network parameters through a case study of the construction of diagnostic model of urinograph ulyt 500B. The experimental results show that the reasoning results of the diagnosis system constructed by this method are consistent with the reality.

Key words: Bayesian network, urine analyzer, fault diagnosis, Pgmpy

中图分类号:

TP399

张喜红, 王玉香. 基于贝叶斯网络医学检验仪器故障诊断模型构建方法的研究[J]. 曲靖师范学院学报, 2021, 40(3): 61-66.

ZHANG Xihong, WANG Yuxiang. Research on the Method of Medical Instrument Fault Diagnosis Based on Bayesian Network[J]. Journal of Qujing Normal University, 2021, 40(3): 61-66.