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作 者:施耀华 冯延晖[1] 任铭 邱颖宁[1] SHI Yaohua;FENG Yanhui;REN Ming;QIU Yingning(School of Energy and Power Engineering,Nanjing University of Science and Technology,Nanjing 210094,Jiangsu Province,China)
机构地区:[1]南京理工大学能源与动力工程学院,江苏省南京市210094
出 处:《中国电机工程学报》2020年第23期7750-7759,共10页Proceedings of the CSEE
基 金:国家重点研发计划项目(2019YFE0104800)。
摘 要:全功率变流器是永磁同步风电系统的核心部件和薄弱环节,发展变流器的状态监测和故障诊断方法是提高系统可靠性的关键。现有的变流器开关管故障诊断方法多基于单一的电流或电压信号,在实际诊断过程中存在因信号缺失和信号干扰而导致故障漏检和误检的问题。近年来风电系统大量安装以高灵敏度振动传感器为主的状态监测系统,这为变流器故障诊断提供了新的诊断途径。文章提出振动信号用于变流器故障诊断的可行性,通过理论分析,论证电流与发电机结构动态响应之间的关联机制和基于振动信号的故障诊断定位规律。在此基础上,进一步研究融合电流和振动信号的变流器故障诊断方法,通过建模仿真和实验结果,验证其有效性和可行性。实验结果表明,该方法能有效降低故障漏检率和误检率,提高诊断的完备性和可靠性。Full-power converter is the core assembly and weak link of permanent magnet synchronous wind power system. The Development of condition monitoring and fault diagnosis for converter is the key to improve the system reliability. Existing fault diagnosis approaches for converter switch are mostly based on a single current or voltage signal. During the actual diagnosis process, problem of missed detection or false detection may arise due to signal missing or signal interference. In recent years, a large number of condition monitoring systems mainly based on high-sensitivity vibration sensors have been installed on wind power systems, providing a new way of diagnosis for converter fault. This paper presented the feasibility of using vibration signals for fault diagnosis of converters. Through theoretical analysis, it demonstrat the correlated mechanism between the current and dynamic response of generator structure and the law of fault diagnosis and position based on vibration signals. On this basis, a converter fault diagnosis method based on fusion of current and vibration signals was further studied and its validity and feasibility were verified by simulation and experimental results. The experimental results show the approach could effectively reduce the missed detection and false detections rates for converter open-circuit faults, thus the completeness and reliability of diagnosis were improved.
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