呼吸机故障智能诊断系统研究与开发  

Research and development of an intelligent diagnosis system for respirator faults

作　　者：宗华 宇应涛 褚代芳 贺骁伟 张柯 徐翔 ZONG Hua;YU Yingtao;CHU Daifang;HE Xiaowei;ZHANG Ke;XU Xiang(Information Department of the Second Affiliated.Hospital of Air Force Medical University,Xi'an 710038,Shannx Province,China.)

机构地区：[1]空军军医大学第二附属医院信息科,西安710038

出　　处：《中国数字医学》2025年第5期66-70,109,共6页China Digital Medicine

摘　　要：目的:提升医院呼吸机的故障智能诊断能力,实现故障原因快速准确定位并恢复正常运行。方法:采用故障树分析法和贝叶斯网络构建呼吸机运行可靠性模型,基于Access数据库和Foxtable软件开发具有可靠性和误报警监测抑制功能的系统模块,构建呼吸机故障智能诊断系统,实现运行参数实时监测、故障诊断与预测、误报警抑制等功能。结果:呼吸机故障智能诊断系统已上线运行1年多,故障报警结果与实际结果相符性达到87.2%。结论:该系统显著优化了呼吸机运维管理流程,有效提升了院内医疗设备的数字化与信息化管理水平。Objective Enhance the intelligent diagnosis capability of hospital respirators to quickly and accurately locate the cause of faults and restore normal operation.Methods Fault tree analysis and Bayesian network were used to construct a reliability model for respirator operation.A system module with reliability and false alarm monitoring and suppression functions was developed based on Access database and Foxtable software.An intelligent diagnosis system for respirator faults was constructed to achieve real-time monitoring of operating parameters,fault diagnosis and prediction,false alarm suppression,and other functions.Results The intelligent diagnosis system for respirator faults has been in operation for more than a year,and the consistency between the fault alarm results and the actual results has reached 87.2%.Conclusion The system significantly optimizes the operation and maintenance management process of respirators,effectively improving the digital and information management level of medical equipment in the hospital.

关 键 词：呼吸机 故障智能诊断 系统设计 

分 类 号：R197.3[医药卫生—卫生事业管理] R319[医药卫生—公共卫生与预防医学]