A Stress Measurement and Compensation Model Based on PSO-BP Neural Network

doi:10.3969/j.issn.1006-2475.2015.06.023

Abstract

Abstract: For the problem that the stress distribution of flexible material is difficult to directly and accurately measure in the working process, this paper proposes a stress measurement and compensation model based on BP neural network with particle swarm optimization. In order to avoid trapping in local optimum, we use particle swarm optimization algorithm to optimize the model’s initial weights and threshold in the process of the training of the model. Through the contrast experiment with flexible material’s standard curve, effectiveness and accuracy of the model is verified when it is applied in stress measurement on the flexible fabric.

Key words: flexible material, particle swarm optimization, BP neural network, measure, compensation

CLC Number:

TP206.1

HAO Gang， ZHUANG Yi. A Stress Measurement and Compensation Model Based on PSO-BP Neural Network[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2015.06.023.

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