Dahiya Ratna
Department of Electrical Engineering National Institute of Technology Kurukshetra, India.
ISA Trans. 2016 Nov;65:537-546. doi: 10.1016/j.isatra.2016.08.013. Epub 2016 Sep 21.
In this paper, a contribution to the development of low-cost wind turbine (WT) test rig for stator fault diagnosis of wind turbine generator is proposed. The test rig is developed using a 2.5kW, 1750 RPM DC motor coupled to a 1.5kW, 1500 RPM self-excited induction generator interfaced with a WT mathematical model in LabVIEW. The performance of the test rig is benchmarked with already proven wind turbine test rigs. In order to detect the stator faults using non-stationary signals in self-excited induction generator, an online fault diagnostic technique of DWT-based multi-resolution analysis is proposed. It has been experimentally proven that for varying wind conditions wavelet decomposition allows good differentiation between faulty and healthy conditions leading to an effective diagnostic procedure for wind turbine condition monitoring.
本文提出了一种有助于开发用于风力发电机定子故障诊断的低成本风力涡轮机（WT）试验台的方法。该试验台是利用一台2.5kW、1750转/分钟的直流电动机与一台1.5kW、1500转/分钟的自励感应发电机耦合而成，并在LabVIEW中与风力涡轮机数学模型相连接。该试验台的性能以已被验证的风力涡轮机试验台为基准。为了利用自励感应发电机中的非平稳信号检测定子故障，提出了一种基于离散小波变换（DWT）的多分辨率分析的在线故障诊断技术。实验证明，对于变化的风况，小波分解能够很好地区分故障状态和健康状态，从而形成一种有效的风力涡轮机状态监测诊断程序。
