基于小波分析的气泡光散射空间谱强度分布的高斯拟合算法优化

Optimized Gaussian Fitting Algorithm for Scattered Light′s Spatial Spectrum Intensity Distribution of Wake Bubbles Based on Theory of Wavelets

将小波消噪方法应用在采用CCD器件作为光传感器的尾流气泡光散射空间谱强度分布检测技术中,发现CCD输出经过消噪后的高斯拟合曲线比其直接进行高斯拟合的结果更逼近实际的气泡光散射谱强度分布,可以有效减小测量误差,使高斯拟合算法得以优化,从而解决了CCD饱和与测量噪音对散射谱强度分布半值宽度和峰值的影响,提高了用气泡光散射谱强度分布判断水中气泡存在和气泡大小的准确度.

Denoising methods based on theory of wavelets were used to process CCD signal output by detecting system for scattered light＇s spatial spectrum intensity of wake bubbles. As the output signal of CCD is denoised, it can diminish the difference between real spectrum intensity distribution and the fitted curve, and consequently the Gaussian fitting algorithm is optimized. The denoising methods can also effectively reduce the influence caused by CCD saturation or its hardware noise on peak value and FWHM of spatial spectrum and results in the improvement of the precision of determining wake bubbles＇ characteristic.