中国医疗设备2017，Vol.32Issue(12)：48-51,56,5.DOI:10.3969/j.issn.1674-1633.2017.12.011
基于关联挖掘的复杂医疗设备故障的检测技术研究
Research on Fault Detection of Complex Medical Equipment Based on Association Mining
李平 1邸玮 1熊光星1
作者信息
- 1. 解放军第169医院 医学工程科,湖南 衡阳 421002
- 折叠
摘要
Abstract
It is known that the detection precision of traditional medical equipment fault detection method is low, while the rate of leak detection and false drop rate are high. In the present study, a complex medical equipment fault detection method was put forward based on association mining. The failure data dependence of complex medical devices could be calculated by fuzzy decision method via obtaining the fault data space coordinates to determine the failure data cluster center. In addition, the failure data of medical equipment was clustered based on the K-Means clustering algorithm to determine the bayesian score function, and the fault data of complex equipment was tested via introduction of association mining method by using data OFWSC algorithm. The experimental comparison results showed that the detection accuracy, efficiency and time were superior to the traditional methods after applying the improved method of fault detection, which indicates that it has a certain practicality and superiority.关键词
复杂医疗设备/故障/检测技术/关联挖掘Key words
complex medical equipment/fault/detection technology/association mining分类
机械制造引用本文复制引用
李平,邸玮,熊光星..基于关联挖掘的复杂医疗设备故障的检测技术研究[J].中国医疗设备,2017,32(12):48-51,56,5.
