Optimization of regularization parameter of inversion in particle sizing using light extinction method

Mingxu Su , Feng Xu , Xiaoshu Cai , Kuanfang Ren , Jianqi Shen
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引用次数: 43

Abstract

In particle sizing by light extinction method, the regularization parameter plays an important role in applying regularization to find the solution to ill-posed inverse problems. We combine the generalized cross-validation (GCV) and L-curve criteria with the Twomey–NNLS algorithm in parameter optimization. Numerical simulation and experimental validation show that the resistance of the newly developed algorithms to measurement errors can be improved leading to stable inversion results for unimodal particle size distribution.

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用光消光法优化粒度反演正则化参数
在消光法粒度测量中,正则化参数在正则化求解不适定逆问题中起着重要作用。我们将广义交叉验证(GCV)和l曲线准则与Twomey-NNLS算法结合起来进行参数优化。数值模拟和实验验证表明,该算法可以提高对测量误差的抵抗能力,从而获得稳定的单峰粒度分布反演结果。
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