将具有保温功能的医疗设备的温度控制在设定值的合适范围内具有重要意义。传统的温度监测方法主要是人工判断，对主观经验依赖性较大，而且过于简单，遇到复杂情况将无法判断温度的可靠性。本文基于主成分分析（PCA）模型，提出了一种新的医疗设备温度监测模型，即基于PCA模型构造多个温度传感器监测数据之间的相关关系，进而构造了相关统计量来监测医疗设备的温度是否正常。将该模型应用于蓝光箱的箱温数据分析，结果表明，该模型可以有效地监测蓝光箱的箱温，当箱温出现异常时，能够及时地发出故障警报，使得异常状况在最短的时间内被发现和处理。该模型可运用到各类温度数据需要进行监测的医疗设备中，具有较强的实用性。%It was important to ensure the temperature control of medical equipment with the heat preservation function within an acceptable range of the setting value. The temperature monitoring was traditionally carried out by artiifcial judgment, which mainly depended on subjective experiences. Also, it was not easy to make an accurate decision in case of complex situations. In this paper, a PCA-based (Principal-Component-Analysis-Based) multivariate statistical model was proposed and applied for temperature monitoring of the medical equipment. In the new model, connections between the monitoring data of temperature sensors was constructed on the basis of PCA model so as to monitor the status of the temperature of medical equipment through use of corresponding statistical data. After application of the new model to analysis of the temperature of the blue light box, it demonstrated its effectiveness, quick responses and alert to the abnormal conditions, which could ensure the abnormalities are found and processed in the shortest time. In practice, the proposed model had strong practicality and could also be used in various medical equipment that needed to monitor the temperature data.
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