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再生混凝土梁受弯破坏过程声发射的灰色模型 被引量:2

Grey Model of Acoustic Emission of Recycled Concrete Beam Subjected to Bending Failure
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摘要 为了分析采用传统灰色理论对声发射事件数建立声发射灰色模型GM(1,1)的预测值相较于试验值较大、预测精度不高等问题,根据再生粗骨料取代率为30%的再生混凝土梁在受弯破坏过程中的声发射现象,通过引入折减系数提高预测值的精度,并给出了折减系数在梁破坏全过程的表达式。通过和试验相验证,比较GM(1,1)灰色模型预测值与试验值,最终结果表明:折减系数与时间呈现较好的非线性关系,在起点处与终点处分别为折减系数的0. 5倍和3倍。根据上述特性得到修正后的灰色模型,其精度较传统模型有了很大的提高,利用该模型对材料受力过程中的声发射参数进行分析,进而实现对再生混凝土梁受弯破坏的判别及预测,对于今后预测材料损伤问题提供了参考。 In order to analyze the problem that the predicted value of the acoustic emission gray model GM( 1,1) established by the traditional gray theory for the number of acoustic emission events compared with the experimental value and the prediction accuracy is not high,the replacement rate of the recycled coarse aggregate is 30%,the acoustic emission phenomenon of recycled concrete beams during bending failure was improved by introducing the reduction factor,and the expression of the reduction factor in the whole process of beam failure was given. By comparing with the experimental results,the predicted and experimental values of the GM( 1,1) grey model were compared. The final results show that the reduction coefficient has a good nonlinear relationship with the time,which is 0. 5 times of the reduction factor at the starting point and the ending point respectively and 3 times of the reduction factor. According to the above characteristics,the corrected gray model has a higher precision than the traditional model. The model is used to analyze the acoustic emission parameters during the stress process of the material,and then the discrimination and prediction of the bending failure of recycled concrete beams. It provides a reference for predicting material damage in the future.
作者 吕旭滨 于江 秦拥军 姜思凡 Lu Xu-bin;YU Jiang;QIN Yong-jun;JIANG Si-fan(College of Civil Engineering and Architecture,Xinjiang University,Urumqi 830047,China)
出处 《科学技术与工程》 北大核心 2019年第28期270-275,共6页 Science Technology and Engineering
基金 国家自然科学基金(51668060,51668061)资助
关键词 再生 混凝土 声发射 灰色模型 折减系数 regeneration concrete acoustic emission grey model reduction factor
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