消失模工艺在矿车铸件生产中的实践

针对矿车铸件的生产工艺,大胆引进消失模工艺,通过实践及对生产过程的经验总结,为进一步完善提高生产技术和改进措施,扩大消失模工艺在其他产品的应用提出了意见。     

Tribology of nitriding layer, TiN coatings and their complex on AISI D2 steel

The sliding wear and impact wear resistances of D2 steel with nitriding layer, PVD titanium nitride coating and their duplex treatment were investigated. The experimental results suggest that the duplex treatment has the best sliding and impact wear resistances under experimental conditions. And the wear resistance of PVD titanium nitride is better than that of nitriding. The impact wear resistance and wear mechanism of all three surface layers remain unchanged under impact load of 0.2 J or 1 J. All samples end with the same symptom of flaking.     

异型材挤出口模内的流动模拟

本文根据挤出机理，对口模内的流动行为进行适当的简化和假定，建立了挤出口模内流动分析的数学模型，并采用横截面／假想区域法实现了复杂异型材挤出口模内的数值模拟，数值分析结果与三维有限元解和解析解的对比，取得了满意的效果。     

斜井提升钢丝绳磨损“失效树”分析

介绍了引起斜井提升钢丝绳失效的各种因素 ,并建立“失效树” ,为煤矿生产中判断其失效原因及预防提供可靠依据。     

铰接顶梁接头模具的热处理

叙述了热锻模的工作条件及材料分析 ,对铰接顶梁接头模具的热处理工艺作了探讨。     

新型模具钢012Al在深冷处理过程中的组织转变

本文利用x-射线衍射分析及复型和薄膜透射技术研究了012Al钢经淬火后在深冷处理过程中的组织转变。结果表明,淬火后的残余奥氏体在深冷处理过程中部分转变成马氏体;深冷处理使马氏体发生分解,析出超细碳化物;同时伴有形变晶孪产生。     

Study on Numerical Simulation of Mold Filling and Solidification Processes under Pressure Conditions

The mold filling and solidification simulation for the high pressure die casting (HPDC) and low pressure die casting (LPDC) processes were studied.A mathematical model considering the turbulent flow and heat transfer phenomenon during the HPDC process has been established and paralled computation technique was used for the mold filling simulation of the process.The laminar flow characteristics of the LPDC process were studied and a simplified model for the mold filling process of wheel castings has been developed.For the solidification simulation under pressure conditions,the cyclic characteristics and the complicated boundary conditions were considered and techniques to improve the computational efficiency are discussed.A new criterion for predicting shrinkage porosity of Al alloy under low pressure condition has been developed in the solidification simulation process.     

面向Internet的模具知识本体的构建研究

通过对Internet上模具知识特点的分析,提出通过修改模具论坛的发贴模板的方法来获取论坛贴子的标签,然后利用"七步法"构建Internet上模具知识本体,并初步提出语义搜索概念模型,为基于Internet模具知识的搜索引擎的实现提供理论和实践基础。     

Intelligent tool wear monitoring based on parallel residual and stacked bidirectional long short-term memory network

Effective tool wear monitoring (TWM) is essential for accurately assessing the degree of tool wear and for timely preventive maintenance. Existing data-driven monitoring methods mainly rely on complex feature engineering, which reduces the monitoring efficiency. This paper proposes a novel TWM model based on a parallel residual and stacked bidirectional long short-term memory (PRes–SBiLSTM) network. First, a parallel residual network (PResNet) is used to extract the multi-scale local features of sensor signals adaptively. Subsequently, a stacked bidirectional long short-term memory (SBiLSTM) network is used to obtain the time-series features related to the tool wear characteristics. Finally, the predicted tool wear value is outputted through a fully connected network. A smoothing correction method is applied to improve the prediction accuracy. The proposed model is experimentally verified to have a high prediction accuracy without sacrificing its generalization ability. A TWM system framework based on the PRes–SBiLSTM network is proposed, which has a certain reference value for TWM in actual industrial environments.     

The statistical modeling of surface roughness in high-speed flat end milling

Surface roughness is one of the most important requirements in machining process. The surface roughness value is a result of the tool wear. When tool wear increase, the surface roughness also increases. The determination of the sufficient cutting parameters is a very important process obtained by means of both minimum surface roughness values and long tool life. The statistical models were developed to predict the surface roughness.This paper presents the development of a statistical model for surface roughness estimation in a high-speed flat end milling process under wet cutting conditions, using machining variables such as spindle speed, feed rate, depth of cut, and step over. First- and second-order models were developed using experimental results of a rotatable central composite design, and assessed by means of various statistical tests. The highest coefficient of correlation (R_adj²) (88%) was obtained with a 10-parameter second-order model. Meanwhile, a time trend was observed in residual values between model predictions and experimental data, reflecting the probable effect of the tool wear on surface roughness. Thus, in order to enhance the estimation capability of the model, another independent variable was included into the model to account for the effect of the tool wear, and the total operating time of the tool was selected as the most suitable variable for this purpose. By inserting this new variable as a linear term into the model, R_adj² was increased to 94% and a good fit was observed between the model predictions and supplementary experimental data.In this study, it was observed that, the order of significance of the main variables is as X₅>X₃>X₄>X₁>X₂ (total machining time, depth of cut, step over, spindle speed and feed rate, respectively).