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Crack classification of fiber-reinforced backfill based on Gaussian mixed moving average filtering method
Cement and Concrete Composites ( IF 10.5 ) Pub Date : 2022-09-08 , DOI: 10.1016/j.cemconcomp.2022.104740
Jian Yang , Kang Zhao , Xiang Yu , Yajing Yan , Zhiwei He , Yanming Lai , Yun Zhou

The crack classification in the rupture process of filling materials is important for predicting rupture instability and identifying rupture precursor features. To investigate fiber-reinforced backfill crack classification, uniaxial compression tests were performed on different fiber-reinforced backfills using a microcomputer-controlled electronic universal testing machine and a Micro-II Express Digital acoustic emission (AE) system. The crack classification model based on the Gaussian mixed moving average filtering method was combined with AE technique under uniaxial compression test, and the crack classification results of the Japanese Construction Materials Standard (JCMS-III B5706) parametric analysis method and the Gaussian mixed model (GMM) were compared and analyzed by comparing changes in the distribution of RA (rise time/maximum amplitude) and AF (average frequency) values. The results revealed that the fiber-reinforced backfill is dominated by tensile cracks in the initial loading stage, tensile cracks transitioned to shear cracks in the intermediate loading stage, and shear cracks dominated in the final loading stage. The fiber-reinforced backfill exhibits an overall distribution of high RA values and low AF values, and the data points are generally close to the RA half-axis, increasing along the RA half-axis in a striped distribution. The percentages of tensile and shear cracks obtained based on the GMM are roughly the same as those obtained by the JCMS-III B5706 parametric analysis method, indicating that the model is feasible to be applied to the crack classification of fiber-reinforced backfills. The results of the study can provide a new method for the crack classification during the rupture of fiber-reinforced filling materials in mines.



中文翻译:

基于高斯混合移动平均滤波法的纤维增强回填裂缝分类

填充材料破裂过程中的裂纹分类对于预测破裂不稳定性和识别破裂前兆特征具有重要意义。为了研究纤维增强回填裂缝分类,使用微机控制的电子万能试验机和 Micro-II Express 数字声发射 (AE) 系统对不同的纤维增强回填材料进行单轴压缩试验。基于高斯混合移动平均滤波法的裂缝分类模型结合AE技术在单轴压缩试验下,日本建筑材料标准(JCMS-III B5706)的裂缝分类结果通过比较RA(上升时间/最大振幅)和AF(平均频率)值的分布变化,对参数分析法和高斯混合模型(GMM)进行了对比分析。结果表明,纤维增强回填土在初始加载阶段以拉伸裂缝为主,在中间加载阶段拉伸裂缝转变为剪切裂缝,在最终加载阶段以剪切裂缝为主。纤维增强回填材料呈现高RA值和低AF值的整体分布,数据点普遍接近RA半轴,沿RA半轴呈条纹状分布。基于 GMM 得到的拉伸和剪切裂纹的百分比与 JCMS-III B5706 参数分析方法得到的百分比大致相同,表明该模型适用于纤维增强回填土的裂缝分类是可行的。研究结果可为矿山纤维增强充填材料破裂过程中的裂缝分级提供新的方法。

更新日期:2022-09-08
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