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基于BP神经网络的聚酯玻璃钢加速老化寿命预测
引用本文:张小锋,郑冉,孟江燕,李超.基于BP神经网络的聚酯玻璃钢加速老化寿命预测[J].失效分析与预防,2011,6(2):75-79.
作者姓名:张小锋  郑冉  孟江燕  李超
作者单位:1. 无损检测技术教育部重点实验室(南昌航空大学),南昌,330063
2. 成都飞机工业集团公司,复合材料厂,成都,610092
基金项目:江西省自然科学基金,航空检测与评价航空科技重点实验室资助项目
摘    要:采用BP神经网络对聚酯玻璃钢氙弧灯加速老化的弯曲寿命进行了预测.通过对聚酯及其玻璃钢的人工氙弧灯加速老化,测试其不同老化时间的弯曲强度,对弯曲强度与老化时间进行BP神经网络的建模分析,借助MATLAB软件对壤酯玻璃钢的使用寿命分别进行分析与预测,并采用最小二乘法对所预测的结果进行了对比.结果表明:在以弯曲强度达到初始强...

关 键 词:BP神经网络  聚酯玻璃钢  氙弧灯加速老化  寿命预测

Accelerated Aging Life Prediction for GFRP Based on BP Neural Network
ZHANG Xiao-feng,ZHENG Ran,MENG Jiang-yan,LI Chao.Accelerated Aging Life Prediction for GFRP Based on BP Neural Network[J].Failure Analysis and Prevention,2011,6(2):75-79.
Authors:ZHANG Xiao-feng  ZHENG Ran  MENG Jiang-yan  LI Chao
Affiliation:1.Key Laboratory of Nondestructive Testing(Nanchang Hangkong University) Ministry of Education,Nanchang 330063,China;2.Composites Factory,Chengdu Aircraft Industry Corporation,Chengdu 610092,China)
Abstract:The bending life of polyester glass fiber reinforced polyester(GFRP) under xenon arc lamp accelerated aging was predicted by BP neural network.The relationship between aging time and bending strength was tested.And models on the relationship between aging time and bending strength were built by BP neural network.Based on MATLAB,the aging life of polyester FRP was analyzed and forecast.The simulation results were compared with those by least square method.The results show that if the decrease in the bending strength by 50% is considered as failure,then the aging life of polyester is 813 d,that of GFRP with filler is 1 031 d and the GFRP without filler is 1 065 d.It is shown that the BP neural network can predict the aging life of FRP.The error between the predicted results by the BP neural network and those by least square method is less than 8%,and the predicted results is in accordance with the practical change of the material property.
Keywords:BP neural network  glass fiber reinforced polyester  xenon arc lamp accelerated aging  life prediction
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