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基于性能退化的智能脱扣器电源模块健康状态预测

Health state prediction of electronic trip unit power supply module based on performance degradation
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摘要 一般情况下电子产品在失效前性能已经发生退化,而传统的寿命预测方法没有利用退化信息。以智能脱扣器电源模块为研究对象,分析MOSFET开关周期和电路薄弱环节储能电容退化之间的关联关系,提出将MOSFET开关周期作为电源模块性能退化的特征量,建立以MOSFET开关周期为特征参量的智能脱扣器电源模块性能退化模型;将电源模块划分为健康、注意和危险3种健康状态,确定健康状态转移图和转移时间的计算方法,建立其健康状态评估模型;对电源模块进行温度应力下的加速退化实验,验证性能退化模型和健康状态评估模型,并预测电源模块在40℃工作环境下由健康状态转移至注意状态的平均转移时间为3906天,转移至危险状态的平均转移时间为9296天。 In general,the performance of electronic products deteriorates before failure.But,the traditional life prediction method does not use the degradation information.The power supply module of electronic trip unit is taken as the research object,the correlation between the MOSFET switching period and the circuit weak link electrolytic capacitor degradation is analyzed,the MOSFET switching period is taken as the characteristic quantity of performance degradation of power supply module,and the performance degradation model of the power supply module of electronic trip unit is formulated with the MOSFET switching period as the characteristic parameter.The power supply module is divided into health state,attention state and danger state,and the health state transition graph.The calculation method of transition time is determined,and the health state evaluation model is formulated.The accelerated degradation experiment of the power module under temperature stress is implemented to evaluate the performance degradation model and health state evaluation model.It predicts that the average transfer time of the power supply module from the health state to the attention state is 3906 days under 40℃environment,and the average transfer time of the power supply module from the danger state is 9296 days.
作者 李奎 赵伟焯 戴逸华 王尧 王阳 Li Kui;Zhao Weizhuo;Dai Yihua;Wang Yao;Wang Yang(Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province,Hebei University of Technology,Tianjin 300401,China;State Key Laboratory of Reliability and Intelligence of Electrical Equipment,Hebei University of Technology,Tianjin 300401,China;Beijing Runpower Technology Co.,Ltd.,Beijing 100096,China)
出处 《仪器仪表学报》 EI CAS CSCD 北大核心 2023年第8期209-217,共9页 Chinese Journal of Scientific Instrument
基金 国家自然科学基金(51937004,51977059)项目资助
关键词 电源模块 性能退化 加速实验 WIENER过程 健康状态预测 power supply module performance degradation accelerated test,Wiener process health state prediction
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