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Probabilistic failure rate model of a tidal turbine pitch system

机译:潮汐涡轮沥青系统的概率故障率模型

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Accurate reliability prediction for tidal turbines is challenging due to scarce reliability data. To achieve commercialization, it is widely acknowledged that reductions in maintenance costs are vital and robust component reliability assessments can help drive this. For established technologies, reliability prediction either involves a statistical assessment of historical failure data, or a physics of failure approach based on dedicated accelerated testing. However, for low/mid Technology Readiness Level tidal developers these common approaches are difficult. Thus, developers require a method of making reliability predictions for components in the absence of tidal turbine specific failure data and physical testing results. This paper presents a failure rate model for a tidal turbine pitch system using empirical Physics of Failure equations, with associated uncertainties. Critical component design parameters are determined and their effects on the failure rate investigated via a sensitivity analysis. The modelled failure rate is then compared with wind turbine failure data from a series of turbines. The tidal turbine failure rate is approximately 50% lower, however high reliability requirements mean this is unlikely to be acceptable. The developed model can assist turbine developers in estimating failure rates and determining reliability critical design parameters for the failure critical pitch system. (C) 2020 The Authors. Published by Elsevier Ltd.
机译:由于稀缺可靠性数据,对潮汐轮机的精确可靠性预测是具有挑战性的。为了实现商业化,广泛承认维护成本的减少是至关重要的,强大的组件可靠性评估可以帮助推动这一点。对于已建立的技术,可靠性预测涉及历史失败数据的统计评估,或基于专用加速测试的失效方法的物理学。但是,对于低/中型技术准备水平潮汐开发商这些常见方法很困难。因此,开发人员需要一种在不存在潮汐涡轮机特定故障数据和物理测试结果的情况下为组件进行可靠性预测的方法。本文介绍了使用失效方程经验物理的潮汐涡轮间距系统的故障率模型,具有相关的不确定因素。确定关键组件设计参数,并通过灵敏度分析研究了对对失败率的影响。然后将建模的故障率与来自一系列涡轮机的风力涡轮机故障数据进行比较。潮汐涡轮机破坏率降低约50%,但高可靠性要求意味着这不太可能是可接受的。开发的模型可以帮助涡轮机开发人员估算故障率和确定故障关键俯仰系统的可靠性关键设计参数。 (c)2020作者。 elsevier有限公司出版

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