Prediction Research on Cutting Surface Roughness of PBX Based on RBF Neural Network

doi:10.3969/j.issn.1000-1093.2014.02.010

Abstract

Abstract: The surface quality of polymer-bonded-explosive（PBX）is a key factor to influence the explosive components and the weapons. An avalanche phenomenon, which is created by material, process and operating condition, on the cutting surface of PBX is observed by analyzing the cutting surface 3D-contour of PBX, which causes the difference between 2D arithmetical mean deviation of the profile and 3D arithmetical mean deviation of the profile to be 32%. Hence, a prediction model which consideres the multiple factors is established with the RBF neural network. The training and test of the prediction model illustrates that the model could reflect the regularity of cutting process, and the predicted error is within 2%.

Key words: manufacturing process and equipment, polymer-bonded-explosive, surface topography, roughness, neural network

CLC Number:

TP183

TANG Xian-jin, ZHANG Qiu, ZOU Gang, WU Song, LIU Wei, YIN Rui. Prediction Research on Cutting Surface Roughness of PBX Based on RBF Neural Network[J]. Acta Armamentarii, 2014, 35(2): 200-206.

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