Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction with Particle Filtering
Lubrication Oil Condition Monitoring and Remaining Useful Life Prediction with Particle Filtering
复制标题
通过颗粒过滤进行润滑油状态监测和剩余使用寿命预测
DOI：
10.36001/ijphm.2013.v4i3.2151
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Eric Bechhoefer
中科院分区：
文献类型：
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作者：
Junda Zhu;Jae Yoon;D. He;Yongzhi Qu;Eric Bechhoefer
为了降低风能的成本，有必要提高风力涡轮机的可用性并降低运营和维护成本。功能性的风力涡轮机的可靠性和可用性在很大程度上取决于其驱动火车子组件（例如变速箱）的润滑油保护性能，以及用于润滑油状况监测和降解检测的手段。风界目前使用润滑油分析来检测变速箱和轴承磨损，但无法检测到润滑油的功能故障。润滑油状况监测和降解检测的主要目的是确定这些油是否恶化的程度，以至于它们不再履行其功能。本文介绍了一项有关使用粒子过滤技术和市售在线传感器来开发在线润滑油状况监测和剩余使用寿命预测的研究。它首先引入了风力涡轮机的润滑油状况监测和降解检测。选择粘度和介电常数作为模拟润滑剂降解的性能参数。特别是，提出了使用粒子过滤的润滑性润滑性能评估和持续的使用粘度和介电常数数据的降解润滑油的使用寿命预测。提供了基于实验室验证模型的仿真研究，以证明已开发技术的有效性。
In order to reduce the costs of wind energy, it is necessary to improve the wind turbine availability and reduce the operational and maintenance costs. The reliability and availability of a functioning wind turbine depend largely on the protective properties of the lubrication oil for its drive train subassemblies such as the gearbox and means for lubrication oil condition monitoring and degradation detection. The wind industry currently uses lubrication oil analysis for detecting gearbox and bearing wear but cannot detect the functional failures of the lubrication oils. The main purpose of lubrication oil condition monitoring and degradation detection is to determine whether the oils have deteriorated to such a degree that they no longer fulfill their functions. This paper describes a research on developing online lubrication oil condition monitoring and remaining useful life prediction using particle filtering technique and commercially available online sensors. It first introduces the lubrication oil condition monitoring and degradation detection for wind turbines. Viscosity and dielectric constant are selected as the performance parameters to model the degradation of lubricants. In particular, the lubricant performance evaluation and remaining useful life prediction of degraded lubrication oil with viscosity and dielectric constant data using particle filtering are presented. A simulation study based on lab verified models is provided to demonstrate the effectiveness of the developed technique.