This article presents an integrated risk assessment methodology for maintenance prediction of oil wetted gearbox and bearing in marine and offshore machinery with emphasis on ship cranes. Predictive maintenance uses important parameters measured in the equipment to ‘feel’ when breakdown is eminent. This type of maintenance intends to make interventions on machinery before harmful events may occur. This article assesses the risk levels of bearing and gearbox, which are the most sensitive components of the ship crane using fuzzy rule–based judgement for common elements and their sources. This will provide the ship crane operators with a means to predict possible impending failure without having to dismantle the crane. Furthermore, to monitor the rate of wear in gearbox and bearing of a ship crane, the ship crane reliability, and a trend to provide an operational baseline of data that will help the engineers to detect abnormal wear rates as they develop, is established. Within the scope of this research, a risk assessment model is developed for determining the risk levels of a crane’s components and recommending solutions using all the diagnostic capability obtainable for effective condition monitoring of the gearbox and bearing in ship cranes.

中文翻译：

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使用模糊规则库方法对船舶和海洋工业中的油湿齿轮箱和轴承进行维护预测的综合风险评估

本文提出了一种综合风险评估方法，用于船舶和海上机械中油浸变速箱和轴承的维护预测，重点是船舶起重机。预测性维护使用在设备中测量的重要参数来“感觉”故障很严重。这种类型的维护旨在在有害事件可能发生之前对机器进行干预。本文使用基于模糊规则的常见元素及其来源的判断来评估轴承和齿轮箱的风险级别，它们是船舶起重机最敏感的部件。这将为船舶起重机操作员提供一种无需拆卸起重机即可预测可能即将发生的故障的方法。此外，为了监测船舶起重机齿轮箱和轴承的磨损率，船舶起重机的可靠性，并且确立了提供数据操作基线的趋势，这将有助于工程师在开发过程中检测异常磨损率。在本研究的范围内，开发了风险评估模型，用于确定起重机部件的风险级别，并使用所有可获得的诊断功能推荐解决方案，以有效监控船舶起重机中的齿轮箱和轴承。