|Table of Contents|

Intelligent fault diagnosis of ventilator based on fault tree and Bayesian network(PDF)

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

Issue:
2021年第9期
Page:
1129-1135
Research Field:
医学信号处理与医学仪器
Publishing date:

Info

Title:
Intelligent fault diagnosis of ventilator based on fault tree and Bayesian network
Author(s):
MA Jianchuan1 CHONG Yinbao1 LANG Lang1 XIAO Jingjing1 WANG Qing1 FAN Liping1 LIU Xiangjun2
1. Department of Medical Engineering, the Second Affiliated Hospital of Army Medical University, Chongqing 400000, China 2. Unit 32572 of the Chinese Peoples Liberation Army, Anshun 561000, China
Keywords:
ventilator fault tree analysis Bayesian network fault analysis
PACS:
R318.6
DOI:
10.3969/j.issn.1005-202X.2021.09.015
Abstract:
In order to find out the cause of the ventilator fault quickly and accurately, troubleshoot the fault and restore the normal operation of the equipment quickly, a method based on fault tree and Bayesian network is used for analyzing the common faults of the ventilator. Based on the comprehensive analysis on the structural principle of the ventilator, combined with literature cases, a fault tree of the ventilator is established for qualitative analysis and the ventilator faults are quantitatively analyzed by Bayesian network. Finally, the actual maintenance cases are used for validation. The results show that the reasoning results obtained by the proposed method are consistent with the actual results, with a consistency up to 84.54%, which provides a theoretical basis for the establishment of static database of ventilator faults and intelligent fault diagnosis, with certain value of promotion.

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Last Update: 2021-09-27