摘要现代高技术的发展过程中,神经网络和故障诊断逐渐被人们认知。随着科技的进步,电路结构变得复杂,诊断难度也不断变大。模拟电路故障诊断一直以来是学术界极其关注和重视的一个问题。
现在神经网络的应用越来越广泛,已成为控制领域、计算工程等领域必不可少的工具,它以其出色的自组织,自学习能力,为模拟电路故障诊断开启了一片新天地。
本文主要通过在模拟电路中设置状态,以BP神经网络为例,讲述了神经网络诊断模拟电路的过程,证明此算法能够精确的辨识故障。本文中例举的RLC测量电路,通过在软件中仿真得到实际的数据,将这些数据训练成样本,进行数据预处理后,将其他测量数据输入网络,再把输出与原始数据进行一个比较,结果故障诊断完全吻合,说明该算法有效果。49292
该论文有图13幅,表4个,参考文献20篇。
毕业论文关键词:神经网络 故障诊断 模拟电路
Neural Network Applications in Analog Circuit Fault Diagnosis
Abstract In the process of the development of modern high technology, neural network and fault diagnosis are recognized by people gradually. With the progress of science and technology, circuit structure becomes more and more complex and the diagnostic difficulty also grows. Analog circuit fault diagnosis has been a extremely important question in academic circles now.
Now the application of neural network become more and more widely.Due to its excellent self-organizing and self-learning ability, it has been a indispensable tool in control field and calculating engineering areas. It has opened up a new land for analog circuit fault diagnosis.
This paper mainly through the Settings in the analog circuit fault, cites the example of BP neural network, tells the process of neural network fault diagnosis of analog circuits. This algorithm can accurately identify the fault. The RLC measuring circuit examples in this article, through the simulation to get the actual data in the software, the data training samples, and other network measurement data input, the output again after diagnosis and original data are compared, and a tested correct diagnosis, shows that the algorithm is effective.
The paper has 13 figures ,4 tables and 20 references.
Key words: Neural network Fault diagnosis Analog circuits
目 录
摘要 I
Abstract II
目录 III
1 绪论 1
1.1 诊断工程概述 1
1.2 故障种类及原因 1
1.3 模拟电路故障诊断意义 2
1.4 模拟电路故障诊断方法概述 3
1.5 神经网络故障诊断方法 4
1.6 本文章节安排和主要内容 6
2 人工神经网络概述 7
2.1 神经网络基本原理 7
2.2 BP神经网络 9
2.3 BP神经网络故障诊断基本思想 12
2.4 本章小结 13
3 MATLAB简介及网络实现 14
3.1 MATLAB介绍 14
3.2 神经网络工具箱及相关函数介绍 15
3.3 BP神经网络MATLAB实现步骤 15
3.4 本章小结