摘要
随着电力电子技术的高速发展,新的电力电子器件的不断涌现,电力电子技术的应用日益深入到工业生产和社会生活的各个方面。电力电子设备的广泛应用使得对设备的可维护性要求越来越突出。高电压、大电流的电力电子装置的功率器件较多,发生故障时用常规的检测方法费时费力,针对故障本身的特点,人工智能、神经网络、小波分析等新兴的学科已成功应用于电力电子设备的故障诊断。智能化的故障自动诊断方法,有利于快速分析确定故障的部位和性质,缩短电力电子电路的运行停机时间,提高效率,减少损失。
故障特征提取和识别方法的研究对发展和完善电力电子装置的智能故障诊断技术有着重要的作用。应用小波包能量法提取出电力电子装置在各种状态下电压及电流信号的能量特征向量,并将它们进行数据融合作为神经元网络故障分类器的输入向量,由神经元网络故障分类器对各种故障进行识别和诊断。以电力电子整流装置主电路故障为例进行了仿真实验,试验结果表明该方法无需数学模型就能快速准确的完成故障定位诊断。
利用小波及小波包分析﹑神经网络及系统辨识等理论实现了三电平逆变装置的故障诊断软件系统设计,诊断系统是直接利用MATLAB自身携带的GUIDE(图形用户界面开发环境)完成了可视化设计,实现了界面与功能的一体化设计。经试验验证该故障诊断系统故障诊断率高﹑诊断速度快﹑操作简单﹑实用性强。
With the rapid development of power electronics and continual emerging of novel power electronic devices, power electronic equipments have been increasingly applied to all aspects of industry and living. The requirement of its maintainability is also more and more important. Because there are many devices in these circuits of high voltage, strong current systems, one will take much time and make many efforts to deal with it using normal fault diagnosis methods. Aiming at the own characteristics of fault, new technologies such as artificial intelligence, neural network, wavelet analysis, etc have been successfully used to fault diagnosis of power electronics. Intellectualized automatic fault diagnosis method has the advantage of rapid analyzing and localizing the fault, cutting the stop time, increasing the efficiency and reducing the loss.
The research on failure feature extraction and failure to identify plays an important role in developing and improving the intelligent fault diagnostic. These signal feature vectors of various states about voltage and current of power electronic device, which are extracted by using the wavelet packet energy method, are integrated as the input vectors of the neural network failure classifier, identified and diagnosed various faults by the neural network classifier. The result of the simulate experiment with the main circuit of electronic power electronic rectifier device failure as an example, shows that the method can deal with the location of fault diagnosis rapidly and accurately without mathematical model.
The software system design of fault diagnosis of three-level inverter device are realized by using these theories of wavelet and wavelet packet analysis, neural network, system identification and so on. The Visual diagnostic system is designed by direct using the GUIDE (graphical user interface development environment) of MATLAB. It has realized one design of the Interface and function. The tests results show that the fault diagnosis system have many advantages of high rate of fault diagnosis, diagnosis rapidly, operate simply and strong practical.
引文
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