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To address bottlenecks and challenges caused by scarce fault samples, unclear failure modes, and insufficient methods for analyzing the reliability performance of regenerative braking energy feedback devices in urban rail transit, this study analyzes equipment reliability by collecting and examining fault event data for these devices. The paper establishes a fault tree model for the regenerative braking energy feedback devices and explores Gaussian kernel density estimation (KDE) to obtain a fitted failure probability distribution function, thereby constructing a reliability modeling and analysis method for such devices. This approach transforms discrete monthly mean time between failures (MTBF) data into a smooth probability density function curve, effectively narrowing the fluctuation range of reliability estimates. Furthermore, it calculates the core MTBF value range with a 95% confidence interval, significantly enhancing both the intuitiveness and scientific understanding of fault data and its distribution for such equipment. This methodology assists in precisely determining the optimal timing for scheduled maintenance, enabling dynamic maintenance adjustments, and supports future equipment selection and lifecycle management decisions.

, authors=Muran ZHANG, Yuyang ZHANG, authorsList=Muran ZHANG, Yuyang ZHANG, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1308453984512008832, articleId=1308453983933194878, tenantId=1146029695717560320, journalId=1146123302524792850, language=CN, title=制动能量回馈装置故障树与可靠性建模方法研究, columnId=1152669334955536763, journalTitle=都市快轨交通, columnName=机电工程, runingTitle=null, highlight=null, articleAbstract=

针对城市轨道交通制动能量回馈装置故障样本少、失效模式不明确、可靠性表现手段不足带来的一系列瓶颈和挑战，为更加有效地分析设备可靠性，通过收集整理制动能量回馈装置故障事件相关数据，建立制动能量回馈装置故障树模型，并探索使用高斯核函数估计（KDE），得到拟合后的故障概率分布函数，创新性的构建一套针对制动能量回馈装置的可靠性建模与分析方法，将离散的总体平均无故障运行时间（MTBF）月度数据转化为平滑的概率密度函数曲线，有效缩小可靠性估计的波动范围，并计算出置信区间为95%的核心MTBF值域，显著提升对该类设备故障数据及其分布认知的直观性和科学性，用于辅助精确制定计划性维修的最佳时间节点，实现动态化维修，并辅助未来的设备选型与全生命周期管理决策。

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张目然，女，硕士，高级工程师，从事城市轨道交通供电技术管理工作，zhangmuran@gzmtr.com

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张目然，女，硕士，高级工程师，从事城市轨道交通供电技术管理工作，zhangmuran@gzmtr.com

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