基于BP神经网络的灌孔砌块砌体抗压强度预测  

Estimation of Compressive Strength of Grouted Block Masonry Based on BP Neural Network

作　　者：王凤来[1] 朱飞[2] 周强[2] 

机构地区：[1]哈尔滨工业大学结构工程灾变与控制教育部重点实验室,黑龙江哈尔滨150090 [2]哈尔滨工业大学土木工程学院,黑龙江哈尔滨150090

出　　处：《建筑材料学报》2015年第6期1010-1016,1023,共8页Journal of Building Materials

基　　金："十二五"国家科技支撑计划项目(2013BAJ12B03)

摘　　要：完成了36件灌孔砌块砌体的抗压强度试验,统计了既有研究530件灌孔砌块砌体的抗压强度试验数据,建立了输入层为4个参数(砌块抗压强度、砂浆抗压强度、灌孔混凝土抗压强度和灌孔混凝土面积与砌体毛截面面积比值)的BP神经网络,推导出简化的灌孔砌块砌体抗压强度计算公式,分析了灌孔砌块砌体抗压强度试验值与计算值的比值(平均值).结果表明:在统计样本空间内,简化的灌孔砌块砌体抗压强度计算公式预测结果良好.BP神经网络方法可以作为灌孔砌块砌体抗压强度计算的一种新方法使用.36grouted block masonry specimens were applied to test their compressive strength,and compressive strength test results of 530 specimens in existing researches were counted.A BP neural networks model with four parameters（block compressive strength,mortar compressive strength,grouted concrete compressive strength and the ratio of grouted concrete area to gross section area of masonry）in input layer was established to predict the compressive strength of grouted block masonry.Then,based on the BP model,a simplified formula for compressive strength of grouted block masonry was deduced.In addition,the ratio（average value）of test data and calculated data of compressive strength of grouted block masonry was also analyzed.The results show that,in the statistical sample space,the compressive strength of grouted block masonry predicted by the simplified formula is suitable.The BP neural networks method is feasible in calculating the compressive strength of grouted block masonry.

关 键 词：灌孔砌块砌体 抗压强度 BP神经网络 公式对比 

分 类 号：TU364[建筑科学—结构工程]