摘要：以-0.038mm煤系高岭土为原料,制备"双90"优质煅烧高岭土,通过试验确定φ25 mm~φ10 mm水力旋流器组超细分级及磁选除铁、煅烧增白的工艺参数。结果表明:当矿浆质量分数为12%,旋流器组两级入料压力为0.4 MPa、0.65 MPa时,产品D90为1.98μm;当磁感应强度为1.4 T,煅烧助剂Na Cl用量为2.5%,经950℃高温煅烧2 h后,白度为91.48%,产品达到"双90"标准要求。

摘要：The random distribution problem of dendrite preferred growth direction was settled by random grid *** method was used to study the influence of forced laminar flow effect on multiple grains during *** high pure succinonitrile （SCN） undercooled melt as an example,the forced laminar flow effect on multiple grains was studied by phase-field model of single grain which coupled with flow equations at non-isothermal *** simulation results show that the random grid method can reasonably settle the problem of random distribution and is more *** the solid fraction is relatively low,melt particles flow around the downstream side of dendrite,and the flow velocity between two dendrite arms becomes *** the stage of solidification time less than 1800Δt,every dendrite grows freely;the upstream dendrites are stronger than the downstream *** higher the melt flow rate,the higher the solid ***,when the solid fraction is relatively high,the dendrite arm intertwins and only a little residual melt which is not encapsulated can flow;the solid fraction will gradually tend to equal to solid fraction of melt without flow.

摘要：带式输送机早期机械故障诊断面临现场环境噪声干扰和工况多变等问题。提出了基于深度迁移学习的带式输送机早期机械故障诊断模型。首先利用集成经验模态分解(EEMD)对振动信号进行预处理,得到振动信号的时频特征组图和时频统计特征参数集;然后构建了一种ResNet与Transformer相结合的融合特征提取网络,提取振动信号的局部和全局时频特征;设计了基于域对抗神经网络的深度迁移方法对融合特征提取网络进行优化,以提升模型对变工况场景的适应能力;最后设计了基于物联网的带式输送机早期故障诊断和预测性维护系统,能够有效地提升带式输送机的生产效率和管理水平。