关键词: 尾砂粒径, 数字图像相关法, 小波包能谱分析, 微损伤识别指标, 尖点突变理论

Abstract:

To explore the influence of tailings particle size distribution on strength and damage characteristics of filling body, uniaxial compression, scanning electron microscopy, and digital image correlation (DIC) tests were carried out on the filling body composed of ultrafine tailings (median particle size D₅₀=10.1 μ m), fine tailings (D₅₀=37.1 μ m), and coarse tailings (D₅₀= 121.31 μ m), and the strength and microstructure characteristics were analyzed. Based on the cusp mutation theory, the damage identification index of the filling body was established using wavelet packet technology, and the damage characteristics of the filling body were quantitatively analyzed. The results reveal that the strength and elastic modulus of the filling body first increase and then decrease with the increase of D₅₀, but the influence of tailings particle diameter on the strength and elastic modulus of the filling body is reduced with the increase of slurry concentration. Compared with the ultrafine and coarse tailings filling body, the coarse and fine particles of the fine tailings backfill are more closely combined, and its porosity is the lowest and microstructure compactness is the best. The energy change rate (ECR) mutation point is defined as the threshold of the backfill specimen damage mutation, which is used to distinguish the stable damage stage and the accelerated damage stage of the specimen, and the damage mutations of the ultrafine, fine, and coarse tailings filling body occur when their stresses reach 92.83%, 92.31%, and 72.93% of the corresponding peak stresses. With the increase of D₅₀, the failure mode of the backfill changes from shear failure to tensile failure, with the ECR increasing from 20.65% to 28.25%, and the damage degree is gradually aggravated. The research results lay the foundation for improving the particle gradation of mine tailings and enhancing the strength of filling body.

Key words: particle size of tailings, digital image correlation (DIC), wavelet packet energy spectrum analysis, micro damage identification index, cusp mutation theory