[Intelligent fault diagnosis expert system for multi-parameter monitor based on fault tree]

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2022 Jun 25;39(3):586-595. doi: 10.7507/1001-5515.202110009.
[Article in Chinese]

Abstract

Aiming at the dilemma of expensive and difficult maintenance, lack of technical data and insufficient maintenance force for modern medical equipment, an intelligent fault diagnosis expert system of multi-parameter monitor based on fault tree was proposed in this study. Firstly, the fault tree of multi-parameter monitor was established and analyzed qualitatively and quantitatively, then based on the analysis results of fault tree, the expert system knowledge base and inference engine were constructed and the overall framework of the system was determined, finally the intelligent fault diagnosis expert system for multi-parameter monitor was developed by using the page hypertext preprocessor (PHP) language, with an accuracy rate of 80% in fault diagnosis. The results showed that technology fusion on the basis of fault tree and expert system can effectively realize intelligent fault diagnosis of multi-parameter monitors and provide troubleshooting suggestions, which can not only provide experience accumulation for fault diagnosis of multi-parameter monitors, but also provide a new idea and technical support for fault diagnosis of medical equipment.

针对现代医疗设备维修贵、维修难、技术资料缺乏及维修力量不足的困境,本文提出了一种基于故障树的多参数监护仪故障智能诊断专家系统。首先建立了多参数监护仪故障树并进行了定性定量分析,然后基于故障树分析结果构建了专家系统知识库和推理机并确定了系统整体框架,最后采用页面超文本预处理器(PHP)语言开发实现了多参数监护仪故障智能诊断专家系统,故障诊断准确率达80%。结果表明:基于故障树和专家系统的两种故障诊断技术融合可有效实现多参数监护仪故障智能诊断并提供排故建议,既能为多参数监护仪故障诊断提供经验积累,又能为医疗设备故障诊断提供一种新的思路和技术支持。.

Keywords: Expert system; Fault tree; Intelligent fault diagnosis; Technology fusion.

MeSH terms

  • Expert Systems*
  • Monitoring, Physiologic

Grants and funding

国家重点研发计划项目(2016YFC0103100);军队卫勤专项资助项目(20WQ005)