For effective integrity management of marine renewable energy systems in the dynamic and uncertain ocean environments, understanding the failure dynamics is crucial. The cost of investment in marine/offshore renewable energy infrastructures and the associated cost due to failure and loss of energy production necessitate a predictive monitoring methodology that is dynamic and adaptive. This paper presents an integrated multi‐state pure‐birth‐pure‐death Markovian‐net profit value model for the offshore turbine subsystem failure analysis and its cost‐based consequences. The integrated model captures the offshore turbine subsystem's dynamic failure states and its economic implications due to the cost of energy loss and downtime for the period under consideration. The model applies a phase‐type exponential distribution to describe the monotonic state of failure. The methodology is demonstrated with an offshore wind turbine gearbox, and it captures the dynamic state of the system and its failure mechanisms. The cumulative effect of the subelements deterioration decreases the gearbox performance by over 35% within the first 2 years of operation.

中文翻译：

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远程离岸环境中可再生能源系统的动态故障分析

为了在动荡不定的海洋环境中对海洋可再生能源系统进行有效的完整性管理，了解故障动态至关重要。海洋/近海可再生能源基础设施的投资成本以及由于能源生产的失败和损失而产生的相关成本，需要一种动态且自适应的预测性监测方法。本文提出了一个综合的多状态纯净出生死亡马尔可夫净利润价值模型，用于海上涡轮机子系统故障分析及其基于成本的后果。集成模型捕获了海上涡轮机子系统的动态故障状态及其由于所考虑的时间段内的能源损失成本和停机时间而产生的经济影响。该模型应用相型指数分布来描述故障的单调状态。海上风力涡轮机变速箱演示了该方法，它捕获了系统的动态状态及其故障机理。在运行的前两年内，子元素劣化的累积影响使变速箱性能降低了35％以上。