关键词: 单视二维图像, 特征参数, 主元分析, 神经网络, 体积估算

Abstract: In granule processing industries，acquisition of particle size and shape parameters is a common procedure，and volumetric measurement is of great importance in dealing with particle sizing.To eradicate the major drawbacks with manual gauge，this paper proposes an optical approach using BP neural network to estimate the particle volume based on the 2-D image information.To achieve the better network efficiency and structure simplicity，Principal Component Analysis（PCA） is adopted to reduce the dimensions of network inputs.To improve the network convergence，momentum is incorporated in gradient descent algorithm.The real particle data are applied in training and testing the presented network.The experiment results suggest that the proposed neural network is capable of estimating particle volume with satisfactory precision and superior to the conventional BP network in terms of performance capacity.

Key words: particle image, particle parameters, Principal Component Analysis（PCA）, neural network, volume estimation