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电网二次设备自主芯片失效率预计方法及其验证

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电网二次设备的核心芯片严重依赖进口,存在断供风险,威胁电网安全.同时,现有二次设备中自主芯片部署数量少,退化机理复杂,可靠性未知,如何评估其可靠性有待研究.有鉴于此,该文提出了适用于二次设备芯片的失效率预计方法,并通过现有进口芯片验证其有效性.具体的,首先,分析介绍了现有新研产品的失效率预计方法;其次,结合二次设备自主芯片特点,提出了加速寿命试验与环境因子修正相结合的芯片失效率预计方法;再次,结合二次设备芯片-模块-整机结构和设备失效统计数据,提出了基于装置缺陷统计数据的芯片失效率估计方法,进一步,分析对比利用试验方法和统计数据的方法得到进口芯片失效率,验证了该文方法的有效性;最后,基于所提加速寿命试验与环境因子修正相结合的方法,预计了自主芯片的失效率,并与对标进口芯片进行了对比.
Method and Verification for Predicting the Failure Rate of Autonomous Chips in Secondary Equipment of Power Grid
The core chips of state grid secondary electric equipment heavily rely on imports,posing a risk of power outage and threatening the power grid's security.At the same time,the number of autonomous chips deployed in existing secondary equipment is small,the degradation mechanism is complex,and the reliability is still being determined.How to evaluate its reliability needs to be studied.Because of this,this article proposes a failure rate prediction method suitable for secondary equipment chips and verifies its effectiveness through existing imported chips.Firstly,the failure rate prediction methods for newly developed products are analyzed and introduced.Secondly,according to the characteristics of the secondary equipment chip,a method of chip failure rate prediction combining accelerated life test and environmental factor correction is proposed.Thirdly,a failure rate estimation method based on equipment defect statistical data is proposed by combining the secondary equipment chip-module-system structure and equipment failure statistics data.The failure rate of imported chips is obtained using experimental methods and statistical data.Through analysis and comparison,the effectiveness of this method is verified in this article.Finally,based on the proposed method of accelerated life test and environmental factor correction,the failure rate of a certain autonomous chip is estimated and compared with imported chips.

chipsecondary equipmentArrhenius modelaccelerated life testenvironmental factorfailure rate

舒治淮、李仲青、王雨茜、喇军、景子洋、刘宇、薛安成

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国家电网有限公司国家电力调度控制中心,北京市西城区 100031

中国电力科学研究院有限公司,北京市海淀区 100192

新能源电力系统全国重点实验室(华北电力大学),北京市 昌平区 102206

芯片 二次设备 Arrhenius模型 加速寿命试验 环境因子 失效率

国家重点研发计划项目

2021YFB2401000

2024

电网技术
国家电网公司

电网技术

CSTPCD北大核心
影响因子:2.821
ISSN:1000-3673
年,卷(期):2024.48(9)