基于响应面法的全尾砂浆絮凝沉降多因素交互影响及参数优化研究  

Study on multiple factor interaction and parameter optimization of flocculation sedimentation of unclassified tailings slurry based on response surface method

作　　者：李勇明 乔登攀[1] 杨天雨[1] 王俊[1] 施仁智 张希 廉柏栋 郑聪 LI Yongming;QIAO Dengpan;YANG Tianyu;WANG Jun;SHI Renzhi;ZHANG Xi;LIAN Baidong;ZHENG Cong(Faculty of Land Resource Engineering,Kunming University of Science and Technology,Kunming 650093,China;Baoshan Jinchanghe Mining Corporation Limited,Baoshan 678000,Yunnan,China;Liangshan Mining Corporation Limited,Liangshan 615141,Sichuan,China)

机构地区：[1]昆明理工大学国土资源工程学院,昆明650093 [2]保山金厂河矿业有限公司,云南保山678000 [3]凉山矿业股份有限公司,四川凉山615141

出　　处：《有色金属科学与工程》2024年第6期901-910,共10页Nonferrous Metals Science and Engineering

基　　金：云南省基础研究专项-青年项目(202301AU070185);云南省基础研究专项-青年项目(202101AU070022);昆明理工大学人培基金资助项目(KKZ3202021040)。

摘　　要：针对某矿山超细粒级全尾砂沉降速度慢,导致设备尾砂处理量低,不能满足充填要求的问题,通过对絮凝沉降参数进行优化来加快沉降速度、提高尾砂处理量。首先对影响沉降的因素和预测优化目标进行分析,在此基础上进行单因素絮凝沉降试验,确定了砂浆浓度、絮凝剂溶液浓度和絮凝剂添加量三因素的试验设计范围。随后,采用响应面法以优化目标固体通量和预测目标底流浓度为响应指标,设计了17组配比试验,根据试验结果构建多元非线性回归模型,研究多因素之间交互作用对固体通量的影响。最后,并对全尾砂浆絮凝沉降参数进行优化,以实现固体通量的最大化,以及对该参数下底流浓度进行预测。结果表明:固体通量不仅受单因素的影响,还受多因素交互作用的影响,且砂浆浓度与絮凝剂添加量之间的交互作用对固体通量的影响程度最大;优化目标固体通量最大为0.7559kg/(m^(2)·s)时的砂浆浓度为25.36%、絮凝剂溶液质量浓度为0.21%、絮凝剂添加量为31.37g/t、预测目标底流质量浓度为57.97%,以此参数进行验证试验,误差均小于2%,模型可靠性较高。本研究为矿山絮凝沉降参数的确定提供了重要依据。The equipment's low tailings treatment capacity,due to the slow sedimentation speed of the ultra-fine-grained unclassified tailings in a certain mine,prevents it from meeting the filing requirements.Therefore,the research optimized the flocculation sedimentation parameters to accelerate the sedimentation and improve the tailings treatment capacity.Firstly,the factors affecting the settlement and the prediction optimization target were analyzed.On this basis,carrying out the single-factor flocculation settlement test,the study determined the experimental design range of the three factors of slurry concentration,flocculant solution concentration and flocculant addition amount,using the response surface method to optimize the target solid flux and predict the target underflow concentration as the response index to design 17 sets of proportioning tests.According to these tests,a multivariate nonlinear regression model was constructed to study the influence of interaction between multiple factors on the solid flux,and the flocculation settlement parameters of unclassified tailings slurry were optimized to maximize the solid flux and predict the underflow concentration under this parameter.The results showed that the solid flux was not only affected by a single factor but also by the interaction of multiple factors,and the interaction between slurry concentration and flocculant addition amount had the greatest influence on it.When the maximum solid flux of the optimization target was 0.7559 kg/(m^(2)·s),the slurry concentration was 25.36%,the flocculant solution concentration was 0.21%,the flocculant addition amount was 31.37 g/t,and the predicted target underflow concentration was 57.97%.The verification test was carried out under these parameters,with less than 2%error.Thus,the reliability of the model is high,providing an important basis for the determination of mine flocculation sedimentation parameters.

关 键 词：超细尾砂 响应面法 絮凝沉降 参数优化 

分 类 号：TD853.34[矿业工程—金属矿开采]