医疗卫生装备2025，Vol.46Issue(5)：73-77,5.DOI:10.19745/j.1003-8868.2025090
基于核岭回归的呼吸机故障概率预测方法研究
Kernel ridge regression-based failure probability prediction method for ventilators
摘要
Abstract
Objective To propose a ventilator failure probability prediction method based on kernel ridge regression(KRR).Methods Firstly,the failure interval data of ventilators was collected and preprocessed to remove outliers.Secondly,the median rank method was used to estimate the failure probability.Finally,using the time data as the feature variable and the failure probability value as the target variable,a KRR model was established and trained by selecting the optimal kernel function and hyperparameter combination from radial basis kernel function,linear kernel function,polynomial kernel function,and S-type kernel function through grid search and cross-validation methods to predict ventilator failures.To verify the performance of the KRR model in predicting ventilator failure probability,it was compared with Weibull and its extended models.Results KRR achieved a coefficient of determination of 0.993 5,a mean squared error of 5.399 5×10-4,a root mean squared error of 0.023 2 and a mean absolute error of 0.018 3,outperforming Weibull and its extended models in prediction accuracy and error control.Conclusion The failure probability prediction method for ventilators based on KRR demonstrates exceptional performance in prediction accuracy and error control,and thus holds great potential for application.[Chinese Medical Equipment Journal,2025,46(5):73-77]关键词
核岭回归/呼吸机/故障概率预测/可靠性分析/剩余使用寿命Key words
kernel ridge regression/ventilator/failure probability prediction/reliability analysis/remaining useful life分类
医药卫生引用本文复制引用
樊立天,陈柱,谢思源,李豪杰,刘麒麟..基于核岭回归的呼吸机故障概率预测方法研究[J].医疗卫生装备,2025,46(5):73-77,5.基金项目
国家重点研发计划项目(2022YFC2407601) （2022YFC2407601）
