为应对船用电力变压器在高盐雾、高湿度、强振动等恶劣海洋环境下绝缘老化加速及状态数据稀缺挑战，研究船用电气设备电力变压器剩余寿命预测的建模方法。构建包含初始健康指数与环境修正系数的多层级健康状态评估模型，引入基于二元非线性Wiener过程与Copula函数绝缘退化相关性建模，融合油中溶解物等多源退化指标，结合故障率模型与热点温度驱动老化系数动态更新机制，实现变压器健康状态综合修正与剩余寿命计算。实验表明，该方法预测最大绝对误差比均低于8%，预测区间覆盖率均高于89%，在高温高湿、频繁启停等典型船用场景中均保持较高精度与泛化能力，形成了环境自适应与非线性老化机理建模的剩余寿命预测体系，有助于船舶电力系统视情维修与健康管理。
To address the challenges of accelerated insulation aging and scarce state data of marine power transformers in harsh marine environments such as high salt spray, high humidity, and strong vibration, a modeling method for predicting the remaining life of marine electrical equipment power transformers is studied. This method constructs a multi-level health status assessment model that includes an initial health index and environmental correction coefficient. It introduces a modeling of insulation degradation correlation based on binary nonlinear Wiener process and Copula function, integrates multi-source degradation indicators such as dissolved substances in oil, and combines a failure rate model with a dynamic update mechanism of aging coefficient driven by hot spot temperature to achieve comprehensive correction of transformer health status and calculation of remaining life. The experiment shows that the maximum absolute error ratio of this method is less than 8%, and the coverage rate of the prediction interval is higher than 89%. It maintains high accuracy and generalization ability in typical marine scenarios such as high temperature, high humidity, and frequent start stop. It forms a residual life prediction system that adapts to the environment and models the nonlinear aging mechanism, which is helpful for the maintenance and health management of ship power systems as needed.
2025,47(19): 140-144 收稿日期：2025-5-8
DOI：10.3404/j.issn.1672-7649.2025.19.022
分类号：U664; TM285
作者简介：王一帆(2004-),男,研究方向为变压器的寿命预测
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