Crack classification of fiber-reinforced backfill based on Gaussian mixed moving average filtering method

Abstract

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.