Power systems have widely adopted the concept of health index to describe asset health statuses and choose proper asset management actions. The existing application and research works have been focused on determining the current or near-future asset health index based on the current condition data. For preventative asset management, it is highly desirable to estimate asset health indices, especially for asset classes in which the assets share similar electrical and/or mechanical characteristics. This important problem has not been sufficiently addressed. This paper proposes a sequence learning based method to estimate health indices for power asset classes. A comprehensive data-driven method based on sequence learning is presented and solid tests are conducted based on real utility data. The proposed method revealed superior performance with comparison to other Estimation methods.

中文翻译：

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估计电力系统中的资产类别健康指数

电力系统广泛采用健康指数的概念来描述资产健康状况并选择适当的资产管理行动。现有的应用和研究工作主要集中在根据当前状况数据确定当前或近期的资产健康指数。对于预防性资产管理，非常需要估计资产健康指数，特别是对于资产具有相似电气和/或机械特性的资产类别。这一重要问题尚未得到充分解决。本文提出了一种基于序列学习的方法来估计电力资产类别的健康指数。提出了一种基于序列学习的综合数据驱动方法，并根据实际效用数据进行了可靠的测试。