CIESC Journal ›› 2016, Vol. 67 ›› Issue (S1): 312-317.doi: 10.11949/j.issn.0438-1157.20160525

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Retrieval of particle size distribution based on TSVD method with constraints

ZHANG Biao, XU Chuanlong, WANG Shimin   

  1. Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, Jiangsu, China
  • Received:2016-04-21 Revised:2016-04-28 Online:2016-08-31 Published:2016-08-31
  • Supported by:

    supported by the National Natural Science Foundation of China (51506030)and the Natural Science Foundation of Jiangsu Province (BK20150622).


Particle size distribution is one of the most important parameters and technical indicators. It not only directly affects the performance and quality of the products, but also helps to reduce energy consumption, improve the environment and safeguard human health. In this paper, several common particle size distributions were retrieved by measuring the extinction values of different visible spectrums using total light scattering methods under independent model. Wherein the estimation values were calculated by the Anomalous Diffraction Approximation (ADA), and the measurement values were obtained by applying Mie theory. A novel inversion algorithm was proposed by using Truncated Singular Value Decomposition (TSVD) regularization combined with two constraints, the particle size distribution is non-negative and the integral of the particle size distribution is equal to 1. To demonstrate the advantage performance of the proposed algorithm, several numerical test cases were investigated. The retrieval results show that the improved TSVD algorithm has higher retrieval accuracy than the traditional TSVD algorithm in the absence of measurement errors, and the improved TSVD algorithm has better anti-noise performance than the traditional TSVD algorithm under different measurement errors. Thus this improved TSVD algorithm can be used as an effective method for retrieval of particle size distribution.

Key words: TSVD regularization, total light scattering, parameter estimation, size distribution, numerical simulation

CLC Number: 

  • TK124
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