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提出了基于平移不变离散小波变换(Translation Invariant Discrete Wavelet Transform,TI-DWT)小波模极大值空间选择性滤波(Translation Invariant Discrete Wavelet Transform Wavelet Modulus Maxima Spatial Selectivity Filter,TI-DWT-MSSNF)的能谱平滑算法,并构建了光滑效果评价指标。分别使用α谱仪和γ谱仪获取了239Pu、241Am的α能谱和137Cs的γ能谱,将5点3次多项式最小二乘法、传统的小波模极大值法和TI-DWT-MSSNF分别用于α和γ谱平滑处理。结果表明:相比较5点3次多项式最小二乘法和传统的小波模极大值法,TI-DWT-MSSNF消除统计涨落更加彻底,特征信息保留更好,峰形畸变更小,是一种更优的方法。
In this paper, TI-DWT (Transform Invariant Discrete Wavelet Transform, Wave-Space Modulus Maxima Spatial Selectivity Filter, TI-DWT-MSSNF) Spectral smoothing algorithm, and build a smooth evaluation index. The 239Pu and 241Am alpha spectra and the 137Cs gamma spectrum were obtained using the alpha spectrometer and the gamma spectrometer, respectively. The polynomial least square 5-3 point method, the traditional wavelet modulus maxima method and TI-DWT-MSSNF For alpha and gamma spectral smoothing. The results show that compared with the 5: 3 polynomial least squares method and the traditional wavelet modulus maxima method, TI-DWT-MSSNF can eliminate more statistical fluctuations and retain better feature information with smaller peak distortion. A better way.