少数据样本下公路机电设施剩余使用寿命预测-工程学研究-CSCIED科技核心评价数据库-手机版

少数据样本下公路机电设施剩余使用寿命预测

Remaining useful life prediction for highway mechanical and electrical facilities using fuzzy similarity and evidence theory

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DOI	10.12208/j.jer.20250045
刊名	工程学研究 Journal of Engineering Research
年，卷(期)	2025, 4(2)
作者	胡永恺¹, 钱威¹, 王强¹, 王亚楠², 温林¹,
作者单位	1 江苏宁沪高速公路股份有限公司江苏南京 2 招商局重庆交通科研设计院有限公司重庆
摘要	针对基于少量且没有明显规律的数据样本，难以准确预测公路机电设施剩余使用寿命（RUL）的问题，提出一种联合模糊相似性方法与证据理论的RUL预测方法。采用模糊相似性方法根据机电设施退化过程之间的相似性对RUL进行直接估算，同时充分利用证据理论在处理不确定性信息方面的优势，通过基本概率分配来表示RUL预测结果的置信度，以处理退化过程的复杂性和不确定性问题。在公路机电设施的试验结果表明：所提方法相比于核密度估计（KDE）和均值方差估计（MVE）方法，在处理预测不确定性的有效性，以及得到预测区间的可靠性和精度具有优势。
Abstract	A remaining useful life (RUL) prediction method combining fuzzy similarity method and evidence theory is proposed to address the problem of accurately predicting the RUL of mechanical and electrical facilities in highway based on a small number of data samples without obvious patterns. Adopting the fuzzy similarity method to directly estimate RUL based on the similarity between the degradation processes of electromechanical facilities, while fully utilizing the advantages of evidence theory in handling uncertain information, the confidence level of RUL prediction results is represented through basic probability al-location to deal with the complexity and uncertainty of the degradation process. The ex-perimental results of mechanical and electrical facilities in highway show that the pro-posed method has advantages over kernel density estimation (KDE) and mean variance estimation (MVE) methods in dealing with prediction uncertainty, as well as reliability and accuracy in obtaining prediction intervals.
关键词	机电；剩余使用寿命预测；不确定性；模糊相似性；证据理论
KeyWord	Mechanical and electrical; Remaining useful life prediction; Uncertainty; Fuzzy similarity; Evidence theory
基金项目
页码	27-33

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引用本文

胡永恺, 钱威, 王强, 王亚楠, 温林. 少数据样本下公路机电设施剩余使用寿命预测 [J]. 工程学研究. 2025; 4; (2). 27 - 33.

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