李永刚 马明晗 武玉才 董晨晨 李正文 刘淼

摘 要：为了精确识别转子匝间短路的故障程度，保障机组经济、安全运行，基于改进熵权理论与灰色关联理论，采用不同故障程度下机电信号为故障样本，建立了转子绕组匝间短路故障程度诊断模型，并采用SDF-9型故障模拟机组进行了实验验证。该方法解决了利用单一特征识别偏差较大的问题，能够精确、有效识别转子绕组匝间短路的故障程度，以便合理安排转子绕组匝间短路故障状态下汽轮发电机组的运行和检修，方法简单且无需加装新传感器，能够为现场发电机的经济可靠运行提供指导性建议。

关键词：汽轮发电机；转子绕组；匝间短路；故障程度；改进熵权；灰色关联

中图分类号：TM 311

文献标志码：A

文章编号：1007-449X（2018）06-0062-08

Abstract：In order to accurately identify the fault degree of rotor winding interturn short circuit and ensure the economic and safe operation of the generating unit， the fault degree diagnosis model of rotor winding interturn short circuit fault is established by using electromechanical signals under different fault degrees as fault samples based on the improved entropy weight theory. Grey relation theory and experimental verification was carried out by using the SDF9 type fault simulation unit. This method solves the problem of large deviation caused by single feature recognition， and can accurately and effectively identify the fault degree of rotor winding interturn short circuit so that reasonable arrangements for the operation and maintenance of turbine generator can be carried out under rotor winding interturn short circuit fault condition. This method is simple and does not need to install new sensors， which can provide guidance for the economic and reliable operation of the generator.

Keywords：turbo generator； rotor winding； interturn short circuit； fault degree； improved entropy weight； grey relation

0 引 言

转子绕组匝间短路故障是汽轮发电机最常见的故障之一。造成短路故障的原因有很多[1]，一方面由于电机制造过程中线圈绝缘、绕组固定等工艺问题；另一方面由于运行过程中长期振动、频繁调峰等运行原因；还有就是由于维护、检修过程中的一些不当操作破坏了绕组绝缘。随着越来越多的大型机组投入到电力系统，发电机发生转子匝间短路的故障的几率也会有所增加。

目前，国内转子绕组匝间短路故障检测方法的研究开展的较为深入，主要的方法有探测线圈法[2]、励磁电流法[3]以及定转子振动检测法[4-6]。另外，针对转子绕组匝间短路时不平衡磁拉力[7-9]、电磁转矩[10]、轴电压[11-12]以及端部漏磁[13]的研究也有开展。……