【作者】 张彤；

【导师】 宋国乡；

【作者基本信息】 西安电子科技大学 ， 应用数学， 2005， 硕士

【摘要】 小波分析是一门新兴理论，它克服了传统Fourier分析的不足，在时域和频域都具有良好的局部化特性，在信号处理、图像处理、语音分析等领域有重要的应用价值。 本文详细阐述了小波分析的基本理论，研究了小波包分析在模拟电路故障诊断中的应用，提出了一种基于小波包变换的特征提取的能量故障检测新方法。它克服了模拟系统中的故障模型比较复杂，难以进行简单的量化、元器件之间具有容差和广泛存在的非线性问题的缺陷；提出了一种基于不完全小波包变换和能量归一化作为预处理的模拟电路故障诊断的BP网络算法。样本信号经过预处理后，在送给BP网络进行训练时，有效减少了BP网络的输入节点和隐层节点的个数，从而减小了神经网络的规模，降低计算的复杂度，加快网络的训练速度，准确的进行故障定位等优点；最后研究了用神经网络和模糊规则的模糊神经网络的故障诊断方法。利用小波包变换在信号处理中的优势，提出了一种基于小波包变换的模糊神经网络故障诊断算法。仿真实验的结果表明此算法构造简单，便于进行模拟电路的自动测试，而且提高了模拟电路故障诊断的正确率。更多还原

【Abstract】 Wavelet analysis is a newly developed theory, which overcomes the disadvantages of traditional Fourier analysis. It has superior localized features in both the times and the frequencies domain and can be applied to signal processing, image processing and speech analysisThe paper gives a description of the basic theory of wavelet analysis, makes a research on the wavelet packet’s applications to fault diagnosis for analog circuit and proposes the energy fault diagnosis algorithm based on the wavelet packet transform as extraction optimal features. It overcomes the complexity of the fault model in the analog system, which makes it difficult to quantify simply and eliminates the defects of components tolerances and nonlinear effects. Thus it proposes the BP neural network fault diagnosis algorithm based on the incompletion wavelet packet transform and energy normalization as preprocessors. After preprocessed, the sample signal will be sent to BP neural network to be trained which effectively reduces the numbers of the inputs and the hidden layer nodes, thereby reducing the size of the neural network, degrading its complexity and minimizing its training time. It identifies fault location with accuracy. Finally the paper studies the method for the fuzzy neural networks fault diagnosis combined by the neural networks and fuzzy rules. Employing the wavelet packet transform, a fuzzy neural networks fault diagnosis algorithm based on wavelet packet transform is presented. Simulation results show that this algorithm structure is simple and easy for auto test and improve the accurate rate of fault diagnosis for analog circuit.更多还原