Hospitals’ daily operations have become increasingly dependent on medical devices. However, the occurrence of faults is inevitable. Therefore, it is crucial for hospitals to make timely fault diagnoses and enact the corresponding measures and improvements. This paper proposes a novel concept lattice method for the intelligent diagnosis of medical device faults. To minimize the influence of uncertain factors, fuzzy sets are used to accurately express relationships between concepts. First, the occurrence frequency and severity of each fault type are extracted based on the collected information. Then, the fuzzy formal context of occurrent faults and known faults can be constructed. Next, the corresponding fuzzy concept lattice is established and visualized using a Hasse diagram. Finally, the similarity between the concept lattices is calculated and used for fault diagnosis. Here, the weight factors are determined using the decision-making trial and evaluation laboratory (DEMATEL) method. A comparative analysis is performed to show that the proposed method uses simple calculations and is highly accurate.

医院的日常运营越来越依赖于医疗设备。但是，故障的发生是不可避免的。因此，对医院进行及时的故障诊断并制定相应的措施和改进措施至关重要。本文提出了一种新的概念格方法，用于医疗设备故障的智能诊断。为了最大程度地减少不确定因素的影响，模糊集用于准确表达概念之间的关系。首先，根据收集的信息提取每种故障类型的发生频率和严重性。然后，可以构造发生断层和已知断层的模糊形式上下文。接下来，使用Hasse图建立相应的模糊概念晶格并使其可视化。最后，计算概念格之间的相似度并将其用于故障诊断。在这里，权重因子是使用决策试验和评估实验室（DEMATEL）方法确定的。进行了比较分析，结果表明该方法使用了简单的计算方法，并且具有很高的准确性。