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作 者:王雅静[1] 申晋[1] 郑刚[2] 刘伟[1] 孙贤明[1]
机构地区:[1]山东理工大学电气与电子工程学院,山东淄博255091 [2]上海理工大学光学与电子信息工程学院,上海200093
出 处:《光学精密工程》2012年第5期963-971,共9页Optics and Precision Engineering
基 金:山东省自然科学基金资助项目(No.ZR2010FM005;No.ZR2009AQ013);上海市重点学科建设资助项目(No.S0502);山东理工大学博士点学科建设资助项目(No.103123)
摘 要:针对单尺度反演方法中存在的精度偏低问题,结合Tikhonov正则化与瀑布型多重网格技术,提出了一种多尺度Tikhonov正则化(ML-TIK)动态光散射反演方法。该方法利用多重网格技术将原反演问题分解到多尺度的网格空间,按着网格从粗到细的顺序,采用单尺度Tikhonov正则化(TIK)对每个子反演问题进行求解,获取颗粒的粒度分布。分别采用TIK和ML-TIK法对噪声水平为0、0.005、0.01的200~650nm模拟双峰分布颗粒数据进行了反演,结果表明:ML-TIK法的反演结果与理论分布吻合,平滑性更好;相对于TIK法,ML-TIK法最多可减少粒径峰值误差8.19%,粒径反演误差0.448 2;而TIK法在噪声水平为0.005、0.01时,反演结果双峰特征不明显。因此,ML-TIK方法的反演精度更高、抗干扰能力更强。最后,用60nm与200nm实测数据的反演结果验证了该结论。For the low accuracy of single-level inversion methods to dynamic light scattering,a novel Multi-level Tikhonov regularization inversion(ML-TIK) method combining the Tikhonov regularization method with cascadic multi-grid technique was developed.Firstly,this method divided the original problem into several sub-inversion problems with different grid spaces by a multi-grid technique.Then,from the coarsest scale to the finest scale,each sub-inversion problem was inverted by single-level Tikhonov regularization(TIK) method.Finally,the Particle Size Distribution(PSD) was successively obtained by solving several sub-inversion problems.This method effectively reduces the ill-condition of the original equations.At noise levels 0,0.005 and 0.01,the simulation data of 200~650 nm bimodal distribution particles were respectively inverted by the TIK and ML-TIK.The results indicate that the inversion PSD of ML-TIK is more consistent with that of the theoretical one and it has better smoothness.Comparing to TIK,the ML-TIK can reduce the peak value error by 8.19% and relative error by 0.448 2.However,when the noise level is 0.005 and 0.01,the PSD of TIK has not obvious bimodal features.Therefore,the ML-TIK has improved the inversion accuracy and noise immunity.Inversion results of 60 and 200 nm experimental data verify above conclusions.
关 键 词:动态光散射 多重网格 TIKHONOV正则化 反演 粒度分布
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