WEC fault modelling and condition monitoring: A graph‐theoretic approach
WEC fault modelling and condition monitoring: A graph‐theoretic approach
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DOI：
10.1049/iet-epa.2019.0763
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发表时间：
2020-02
影响因子：
1.7
通讯作者：
Yufei Tang;Yu Huang;Erica Lindbeck;Samuel Lizza;James H. VanZwieten;Nathan Tom;W. Yao
中科院分区：
文献类型：
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作者：
Yufei Tang;Yu Huang;Erica Lindbeck;Samuel Lizza;James H. VanZwieten;Nathan Tom;W. Yao
波浪资源的性质通常需要波能量转换器（WEC）组件来处理峰值负载（即扭矩，力和力量），这些峰值大于平均载荷，加速设备降解。此外，由于其孤立的性质和严酷的操作环境，WEC系统预计将拥有高运营和维护（O＆M）成本，即其能源级别的27％。因此，通过应用条件监测和容忍控制的技术来开发以减轻这些成本的技术，将显着影响网格连接的WEC功率的经济可行性。为了实现这一目标，在开源建模平台WEC-SIM中开发了故障组件的模型，以估计具有可能设备和传感器故障的WEC操作的性能和可测量状态。然后将两种类型的故障组件模型应用于具有基本控制器阻尼和弹簧力的点吸收器WEC模型。导致设备行为的变化记录为基准测试，并提出了使用多元时间序列的故障检测和识别的图理论方法。仿真结果表明，这些故障可以极大地影响WEC的性能，并且所提出的方法可以有效地检测和分类不同类型的故障。
The nature of wave resources usually requires wave energy converter (WEC) components to handle peak loads (i.e., torques, forces, and powers) that are many times greater than their average loads, accelerating equipment degradation. Moreover, due to their isolated nature and harsh operating environment, WEC systems are projected to possess high operations and maintenance (O&M) cost, i.e., around 27% of their leveled cost of energy. As such, developing techniques to mitigate these costs through the application of condition monitoring and fault tolerant control will significantly impact the economic feasibility of grid connected WEC power. Toward this goal, models of faulty components are developed in the open source modeling platform, WEC-Sim, to estimate the performance and measurable states of a WEC operating with likely device and sensor failures. Two types of faulty component models are then applied to a point absorber WEC model with basic controller damping and spring forces. Resulting changes in device behavior are recorded as a benchmark, and a graph-theoretic approach is proposed for fault detection and identification utilizing multivariate time series. Simulation results demonstrate that these faults can greatly affect the WEC performance, and that the proposed method can effectively detect and classify different types of faults.