基于小波变换的信号去噪在瑞利-泰勒不稳定性定标实验中的应用

De-noising based on wavelet transform in Rayleigh-Taylor instability analysis

  • 摘要: 采用Daubechies小波分析,对神光Ⅱ装置上流体力学不稳定性实验中样品扰动幅度和X光强度之间定标关系的数据进行了处理,获得了比较理想的去噪效果,并由此得到了平面调制靶波长及材料线性吸收系数等细节信息。该定标关系对准确测量瑞利-泰勒不稳定性的增长至关重要。作为对比,利用Wiener滤波方法对数据进行了处理,结果显示在处理这类信号时,Daubechies小波滤波在去除噪声和保留信号细节特征方面明显优于Wiener滤波。

     

    Abstract: In hydrodynamics instability experiment, the quantificational relation between amplitude fluctuation of sample and X-ray intensity is important to analysing Rayleigh-Taylor instability exactly. The signal-to-noise of the data is always low due to the complex image environment, thus improving the signal-to-noise of the image is inevitable. With the area backlighting, the X-ray intensity images were recorded by XSC in ShenguangⅡ facility. Daubechies wavelet filtering and Wiener filtering were used to de-noise the data separately. The results show that the Daubechies wavelet filtering is better than the Wiener filtering in de-noising and maintaining the detail of the signal.

     

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