Labview在BP神经网络谐波监测中的实现

Realixation of labview in the harmonics of BP neural network

为了减少电力系统中谐波的危害,本文将神经网络理论应用于谐波监测,使用界面设计方便美观的Labview编程语言制作了一种谐波监测仪。文中构造了一个目前应用最为广泛的BP网络,给出了网络算法,形成了训练样本。并用基于Labview工作平台的G语言,编写了训练程序,将所形成的样本对网络进行了训练,然后对训练好的网络进行仿真实验。结果表明:所设计的神经网络可很好的监测谐波,并对谐波参数的显示设计了很好的人机界面。

To soften the negative effect from the harmonic waves in power system, this article applies the neural network theory into the measuring of harmonics, designs an apparatus for Measuring of Harmonics by the programming language of Labview which is more convenient and beautiful for interface design. This article designs the most widely-adopted BP network, demonstrates the network algorithm, and forms a training sample. By the employment of G language based on the platform of Labview, the author compiles a training program, puts into training the network by the designed sample, conducts a emulation experiment on the well-trained network. The result shows that the well-designed neural network can measure harmonics well. At the same time, an excellent human-computer interface is designed according to the display of the harmonics parameter.