基于FTA的磁共振成像设备可靠性研究
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摘要
目的探索故障树分析法评价磁共振成像设备可靠性研究中的效果,为预防和控制故障的发生,提高设备可靠性提供依据。方法通过专家咨询以及对MRI设备原理和构造的分析建立MRI设备故障树,并利用布尔代数运算法则求MRI设备故障树的全部最小割集和最小路集,最后利用调研收集的国内外不同场强MRI设备的故障数据计算故障事件发生概率,并采用非参数检验分析不同MRI设备故障事件发生率的差别。结果 (1)建立起MRI设备故障树,分析出MRI设备故障树共有32个最小割集,1个最小路集。(2)国产与进口MRI设备之间进行比较,底事件中有6种故障事件发生概率的比较差异有统计学意义(P<0.05);中间事件中有2种故障发生概率比较差异有统计学意义(P<0.05)。(3)场强为3.0T和1.5T的MRI设备的比较,底事件中6种故障事件发生概率的差异有统计学意义(P<0.05)。结论通过故障树分析方法确定引起MRI设备出现故障的最小割集为32个,最小路集为1个,发现了国产与进口MRI设备以及不同场强的MRI设备之间故障事件发生概率的差异,为进一步探究原因、完善改进措施,提高设备可靠性提供依据。
Objective To explore the effectiveness of fault tree analysis in evaluating the reliability of magnetic resonance imaging equipment, and to provide a basis for preventing and controlling the reliability of fault preparedness. Methods Structure of MRI equipment was built by expert consultation and the analysis of the MRI equipment principle, and all minimum cut set and minimum path set of MRI equipment fault tree was obtained by using Boolean algebra algorithm. Finally, the probability of the occurrence of failure events was calculated by using the failure data collected from different MRI devices at home and abroad, and the difference in the incidence of failure events of different MRI devices was analyzed by non-parametric test. Results(1) The fault tree of MRI equipment was established, and 32 minimum cut sets and 1 minimum path set were analyzed.(2) Domestic MRI equipment was compared with imported MRI equipment, there were statistically significant differences in the probability of 6 failure events in the baseline event(P<0.05). The difference in the probability of two kinds of failure in the intermediate events was statistically significant(P<0.05).(3) MRI equipment with a field intensity of 3.0 T compared with MRI equipment with a field intensity of 1.5 T, the probability of occurrence of 6 failure events in the baseline event was statistically significant(P<0.05). Conclusion The fault tree analysis method was used to determine the minimum cut set of 32 and the minimum path set of 1 that caused the failure of MRI equipment. The difference in the probability of occurrence of failure events between domestic and imported MRI equipment and MRI equipment with different field intensities was found, providing a basis for further exploration of the causes, improvement measures and improvement of equipment reliability.
Objective To explore the effectiveness of fault tree analysis in evaluating the reliability of magnetic resonance imaging equipment, and to provide a basis for preventing and controlling the reliability of fault preparedness. Methods Structure of MRI equipment was built by expert consultation and the analysis of the MRI equipment principle, and all minimum cut set and minimum path set of MRI equipment fault tree was obtained by using Boolean algebra algorithm. Finally, the probability of the occurrence of failure events was calculated by using the failure data collected from different MRI devices at home and abroad, and the difference in the incidence of failure events of different MRI devices was analyzed by non-parametric test. Results(1) The fault tree of MRI equipment was established, and 32 minimum cut sets and 1 minimum path set were analyzed.(2) Domestic MRI equipment was compared with imported MRI equipment, there were statistically significant differences in the probability of 6 failure events in the baseline event(P<0.05). The difference in the probability of two kinds of failure in the intermediate events was statistically significant(P<0.05).(3) MRI equipment with a field intensity of 3.0 T compared with MRI equipment with a field intensity of 1.5 T, the probability of occurrence of 6 failure events in the baseline event was statistically significant(P<0.05). Conclusion The fault tree analysis method was used to determine the minimum cut set of 32 and the minimum path set of 1 that caused the failure of MRI equipment. The difference in the probability of occurrence of failure events between domestic and imported MRI equipment and MRI equipment with different field intensities was found, providing a basis for further exploration of the causes, improvement measures and improvement of equipment reliability.
引文
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[10] 李垚,朱才朝,宋朝省,等.风电机组液压系统动态故障树的可靠性建模与评估[J].太阳能学报,2018,39(12):3584-3593.
[11] YANG J P, HUANG H Z, LIU Y, et al. Evidential networks for fault tree analysis with imprecise knowledge[J]. Int J Turbo Jet Eng,2012,29(2):111-122.
[12] 石向阳.基于FTA的B737-300空调系统故障诊断研究[J].大众科技,2017,19(2):41-43.
[13] 高国庆, 周璐春. 基于故障树的自适应光学电控系统可靠性分析[J]. 激光与光电子学进展, 2016(1):40-46.
[2] XIAO L, OUYANG S M, LI Y W, et al. Fault detection method for magnetic resonance imaging spectrometer based on the acquisition and analysis of its output waveforms[J]. Concept Magn Reson B,2017,47B(1):e21353.
[3] 陈凯,田堂振,胡陈强,等.基于FTA的制造工艺故障分析系统[J].机械设计与研究,2018,34(5):200-203,207.
[4] JICHUAN K, LIPING S, GUEDES S C. Fault tree analysis of floating offshore wind turbines[J]. Renew Energ, 2018:S0960148118310474.
[5] OLIVA J D R, LLANES J S, OJEDA M P. Advanced combinatorial method for solving complex fault trees[J]. Ann Nucl Energy,2018,120:666-681.
[6] 张帆,黄世泽,郭其一,等.基于故障树分析法的道岔故障诊断与可靠性评估方法[J].城市轨道交通研究,2018,21(10):52-56.
[7] 刘英,肖杨亮,张根保,等.基于梯形模糊数的数控磨床砂轮架系统故障树分析[J].工程设计学报,2018,25(4):394-401.
[8] 刘宇飞,魏加兴,王衍学.故障树模型分析法在灯体加工机械人机工程设计中的应用[J].机床与液压,2018,46(17):169-172.
[9] 胡顺威,周晖,从黎,等.基于故障树的含电力电子变电站配电网可靠性分析[J].电力系统保护与控制,2018,46(21):25-31.
[10] 李垚,朱才朝,宋朝省,等.风电机组液压系统动态故障树的可靠性建模与评估[J].太阳能学报,2018,39(12):3584-3593.
[11] YANG J P, HUANG H Z, LIU Y, et al. Evidential networks for fault tree analysis with imprecise knowledge[J]. Int J Turbo Jet Eng,2012,29(2):111-122.
[12] 石向阳.基于FTA的B737-300空调系统故障诊断研究[J].大众科技,2017,19(2):41-43.
[13] 高国庆, 周璐春. 基于故障树的自适应光学电控系统可靠性分析[J]. 激光与光电子学进展, 2016(1):40-46.