A Data-Based Nonlinear Modeling Method for Temperature Monitoring of Medical Equipment
It is of great significance to control the temperature of the infant incubators for making the babies stay at a comfortable and safety environment.The INCU incubator analyzer is widely used to verify the normal temperature of incubators.However,the traditional monitoring methods mainly rely on the mean of temperature value and the range of variation to judge if the temperature is normal or not.In this article,a data-based modelling method is proposed to monitor the variations of the temperature automatically and in advance.Considering the nonlinear correlations in the temperature data,a nonlinear model,kernel probabilistic principal component analysis is used,which is introduced in detail and is demonstrated by the real temperature data of the infant incubators.
temperature monitoring the INCU incubator analyzer data-based kernel probabilistic principal component analysis
Yun-yun Wu Kun Zheng Cai-xian Zheng Chang Su Tai-shi Zheng
Department of Clinical Engineering, The Childrens Hospital Zhejiang University School of Medicine, Hangzhou 310052, Zhejiang Province,China
国际会议
杭州
英文
36-40
2015-10-21（万方平台首次上网日期，不代表论文的发表时间）