高压旋转电机的状态监测和故障诊断研究

【作者】 王旭红；

【导师】 彭建春；

【作者基本信息】 湖南大学 ， 电力系统及其自动化， 2002， 硕士

【摘要】 电机是当今生产活动和日常生活中最主要的原动力和驱动装置，它广泛地应用于现代工业生产中，它们数量之多，地位之重要，几乎没有其他设备所能与之相比。电机在运行过程中，难免会出现这样那样的故障，假如一条生产线上的主要电机故障，必将造成生产线停工，甚至会影响整个大生产系统的工艺流程。电机的故障现象比较复杂，要求维修人员具有较高技术水平与经验，才能发现和判断。电机的故障诊断和维护与电机本身一样由来已久。厂商及电机的用户仅依靠诸如过电流、过电压、接地等简单技术保证其运行的安全性和可靠性。然而，不定时的停机会扰乱生产并造成经济损失，人们开始寻找该领域的故障诊断方法。70年代兴起的设备故障诊断技术是一门新技术，它能实现设备在带负载运行、不停机的情况下，通过使用先进的技术手段对设备状态参数监测和分析，判断设备是否存在异常或故障，故障的部位和原因以及故障的劣化趋势，以确定合理的检修时间和方案。这门技术已在一些产业部门和技术领域得到迅速发展并取得了很大成效，促进了设备维修体制的一次变革，使设备维修体制由传统的事后维修和预防维修方式，逐步变为预知维修(或状态维修)。由此减少了事故停机损失，提高了设备运行的可靠性，降低了维修费用。目前这项技术正迅速崛起，应用领域不断拓宽。 本文从绝缘结构的故障机理入手，以绝缘结构故障的典型特征——局部放电为研究对象，重点讨论局部放电的在线监测方法、适用场合并比较它们的优缺点；在分析笼型异步电机转子断条在线监测的定子电流监测方法后，根据其缺陷，本文探讨了温升不平衡法、希尔伯特变换数字滤波、小波包分析法的原理及优点；以电机轴承、气隙偏心等故障为研究对象，通过对电机振动和转速频率的检测，诊断电机的故障类型；本文的重点工作是将人工智能技术中的模糊技术应用于电机的状态监测和故障诊断中，力求使电机故障诊断更接近人工智能化；最后，本文对电机状态监测和故障诊断系统进行了硬件和软件初步设计，为实现预测维修提供了有效的技术手段。更多还原

【Abstract】 Electrical machines are the most important and main drive devices in manufactures and our daily life.No other kinds of machines can replace them.They are widely used in the modem world.Without electrical machines,the world would not be what it is today.When operating, they might have a lot of faults.If a main electrical machine is wrong in a work line ,the whole line will stop,even the whole productive system.The phenomenon of the faults are so complicated and various that the maintance worker should be skillful and very experienced.The history of fault diagnosis and protection is as archaic as the machines themselves. The manufacturers and users of electrical machines initially relied on simple proctections such as over-current, over-voltage,earth-fault,etc. to ensure safe and reliable operation.However,as unscheduled machine downtime can upset deadline and cause heavy fmacial losses, improvements were sought in the field of fault diagnosis. In 1970’s a new technology of electrical machines’ fault diagnosis-condition monitoring has arisen. The technology could judge and diagnose the faults by advanced technology and analysis instrument when the machine is on-line. It can also determine the fault spot and reason.This technology has been used in some technological fields and proved efficient .It has promoted the revolution of maintance system and the historial protection is replaced by preventive maintenance.With this technology,we can improve the reliability of machine and decrease the maintance fee.Recently,reserch has pick up a fervent pace in the area of fault diagnosis of electrical machines.The paper simply analyzes the fault reason of electrical machines,stressly describes and explores the methods of condition monitoring and fault diagnosis such as partial discharge, stator current ,rotating speed, vibration etc.Fault prognosis is now include diagnostic feature,reason ,spot.Prodigious improvement in signal processing hardware and software has made this possible.Primarily,these techniques depend on locating specific harmonic components of the fault .These harmonic components are usually diffirent for diffirent types of faults.Automated tools such as fuzzy logic based system is also simply presented in the paper.更多还原