中文摘要：

针对柔性材料在工作过程中受力情况难以直接并准确测量的问题，提出一种基于粒子群优化的BP神经网络应力测量与补偿模型。在模型的训练过程中，采用粒子群算法对模型中的初始权值和阈值进行优化，解决BP神经网络收敛速度慢的问题。通过与柔性材料标准曲线的对比实验，验证了该模型对柔性材料进行应力测量的有效性和准确性。

英文摘要：

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.