Abstract：Objective To analyze the fault correlation of ventilator sensor system, provide solution for the problems including high
failure rate and potential hazard during the usage of ventilator, and provide reference for preventive maintenance of ventilator.
Methods The maintenance work orders related to the sensor system of a single type of ventilator provided by our hospital and the
original factory engineers from 2010 to 2022 were collected and sorted out as the research object. The establishment of the gamma
distribution model and the method of parameter estimation were used, and the model was verified and analyzed using goodness of
fit test, K-S test, evaluation index of goodness of fit including mean square error, root mean square error, and mean absolute error.
Results The K-S test statistic D values for the six types of ventilator failure points were 1.99×10-2, 2.98×10-2, 4.03×10-2, 4.06×10-2,
3.13×10-2, 6.22×10-2 respectively. The goodness of fit test statistic χ2 were 396.95, 601.01, 23.25, 13.94, 52.35, 5.55, respectively.
Except for gas mixture pressure sensor faults, the distribution of calculated values and actual values of each fault point model was
statistically significant (P<0.05). The mean time between failures, reliability mean time and extreme value time of the six
failure points were basically consistent with the actual results. Conclusion The fault distribution model based on the
gamma theory can effectively analyze the fault distribution, failure efficiency and reliability of the ventilator sensor system, and can
provide evidence-based basis for formulating targeted preventive maintenance programs, which has certain research significance.
徐慧，王士森. 基于呼吸机传感器系统故障关联的
失效率和可靠性研究[J]. 中国医疗设备, 2024, 39(1): 44-49.
XU Hui, WANG Shisen. Research on Failure Rate and Reliability Based on Fault Correlation of Ventilator Sensor System. China Medical Devices, 2024, 39(1): 44-49.
