基于多因素的全尾砂胶结充填材料力学性能研究

胶结充填材料及配合比既是决定充填材料力学性能的关键指标,又是影响充填成本的主要因素。灰砂比、充填浓度、养护龄期等多因素对充填材料力学性能的影响程度不同,同时不同因素在对充填材料力学性能的影响方面彼此又有潜在的联系。为全面考察不同因素对全尾砂胶结充填材料力学性能的影响,本文以厂坝铅锌矿为依托,基于产能、技术和经济指标要求,以不同灰砂比、充填浓度、养护龄期下充填试块的强度参数为依据,展开了多因素下全尾砂胶结充填材料的力学性能试验研究。为准确获得试验信息,对多因素、多水平的系统问题进行了正交试验设计。通过对试验结果的多因素极差、方差分析,分析了不同因素影响全尾砂胶结充填材料力学性能的显著性程度,找出了最优化的配比条件,同时利用CIA800-3D超景深三维显微镜从微观角度对多因素下全尾砂胶结充填材料的力学性能进行了研究,最后在综合分析了多因素对全尾砂胶结充填材料力学性能影响的基础上,利用SOM神经网络技术,建立了不同养护龄期下全尾砂胶结充填材料的预测模型。研究结果表明,多因素下的全尾砂胶结充填材料力学性能的试验研究及预测模型的建立,对开展全尾砂胶结充填材料力学性能的研究探索了一种新的途径,为充填系统的设计和运行提供了可靠的技术保证。

BASED ON MULTIPLE FACTORS OF The BACKFILLING CEMENTED FILLING MATERIAL MECHANICS PERFORMANCE RESEARCH

Cemented filling material and mixing ratio is not only the key indexes of the filling material mechanical properties, and the main factors that affect the cost of filling. Contrast, weight, concentration, curing age and so on the influence of many factors on the filling material mechanics performance, at the same time, the influence of different factors on the filling material mechanics performance has the potential to contact each other again. For comprehensive study the influence of different factors on the filling material mechanics performance, this paper, which is based on the changba lead-zinc mine, based on the requirement of production capacity, technical and economic indexes, in different contrast ratio, weight, concentration, curing ages under filling on the basis of the strength parameters of the block, launched multiple factors of filling material mechanical performance test research. To obtain the comprehensive test information, system problem of multiple factors and levels, making a comprehensive combination design, implemented a comprehensive test. Based on the results of many factors, analysis of variance, finding out the optimal matching conditions, at the same time using VHX - 1000 super depth more than 3 d microscopic system from the Angle of the micro factors of filling material mechanical properties are studied, the last on the comprehensive analysis of many factors on the filling material mechanics performance impact, on the basis of using SOM neural network technology, set up the forecast model of the filling material under different curing ages. Research results show that under the multiple factors of filling material mechanical performance test research and build up the forecast model of filling material mechanics performance of the study to explore a new way, for the filling system design and production provides a reliable technical basis.