小波分析在强流直线感应加速器信号处理中的应用
Methods of signal processing in LIA based on wavelet transform
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摘要: 应用小波变换具有良好的时频局部特性，通过对强流直线感应加速器(LIA)脉冲信号的去噪声、信号突变点检测以及时间间隔测量等处理，表明小波变换在LIA信号处理中有广泛的应用前景；利用小波包分析的每个节点都代表了对应频带的信号特征的特点，对“神龙一号”快脉冲波形数据进行小波包变换，以各频带信号能量为元素构造特征向量，实现了高维波形数据的特征值提取，达到了数据压缩和降维的目的，为进一步实现LIA故障智能诊断、预测维护提供了一种可行的途径。Abstract: According to the time-frequency localization properties of wavelet transform, the application methods in pulse signal′s de-noising and singularity detection show good performance in signal processing of high current LIA. A method to extract characteristic parameters from energy on the coefficients of wavelet packet transform of Dragon-Ⅰ’s waveforms is presented. Parameters, which are extracted from the relevant frequency bands and are used as vector, represent jointly temporal position and frequency variation of waveform. Such characteristic vector can be applied to further signal processing and fault diagnosis of high current LIA.
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Key words:
- wavelet transform /
- signal de-noising /
- singularity detection /
- characteristic vector
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