Damage evolution of coal gasification slag based backfill by acoustic emission and Gaussian mixed moving average filtering method

The identification and study of the damage evolution process in coal gasification slag-based solid waste cemented paste backfill (CG-CPB) are crucial for understanding the damage patterns of the backfill under the influence of overburden. This study conducts uniaxial compression tests on CG-CPB specimens using acoustic emission (AE) technology. It analyzes the AE signals, stress curves, b-values, and RA-AF (rise time/maximum amplitude and average frequency) temporal characteristics during the damage process. The findings indicate a four-stage progression of damage in CG-CPB: pore closure, microcrack initiation, crack coalescence, and eventual instability. The results demonstrated that the AE amplitude is closely linked to these stages, with the temporal evolution of the b-value showing a correlation with crack propagation. A notable decrease in the b-value during Stage III is a precursor to instability. Furthermore, RA-AF analysis underscores tensile damage as the primary mode, with shear damage playing a secondary role in the backfill material. In addition, the Gaussian mixed moving (GMM) is employed to identify the backfill's instability mode, and cluster analysis is conducted on the mixed damage events that cannot be identified by the RA-AF method alone. The damage to the backfill is classified into three modes: tensile (60 %), shear (20 %), and mixed damage (20 %). It is proposed that the sudden drop in mixed damage should be used as a precursor of instability, providing sufficient redundancy for the safe operation of CG-CPB. This study's results offer a theoretical basis and guidance for predicting damage in CG-CPB. [Display omitted] •Coal gasification slag based backfill (CG-CPB) was prepared from low cost solid waste.•The effects of cement-sand ratio, activator content, and solid content on the AE signals were investigated.•The damage of the CG-CPB primarily involved tensile damage (80 %), and shear damage made a small contribution of 20 %.•GMM can effectively identify the damage patterns of CG-CPB.