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.
Last Update: 2021-09-27