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.     

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).     

Novel methods for rapid assessment of tool performance in milling

The paper examines the effectiveness of two innovative techniques designed to rapidly optimize a milling application. One of them relates to quantifying the relative wear of different insert grades concurrently in a single cutting test, by mounting the inserts in the same cutter, for a quick comparative performance evaluation. Experimental results that illustrate the validity and limitation of this concept, and a scheme for enhancing the reliability of the test method are presented. The other technique refers to rapid identification of the optimum feed/tooth that corresponds to maximum tool life. This entails a test wherein individual inserts in the cutter are subject to feed/tooth that are multiples of a base value, by selectively leaving appropriate number of consecutive insert pockets unoccupied. These novel techniques complement known accelerated tool life tests, and are expedient for industries that engage short production runs, in terms of selecting a suitable insert grade for an application, and determining optimal cutting conditions for the selected grade.     

基于机器视觉的加工刀具磨损监测方法

为了对加工过程中刀具的磨损状态进行监测,针对麻花钻的磨损形式,提出基于机器视觉的加工刀具磨损监测方法. 根据磨损刀具图像的灰度分布特点,提出基于积分图加速和Turky bi-weight核函数的非局部均值去噪方法;采用单、双阈值大津法获取磨损区域的灰度区间,实现对图像的自适应对比度增强;提出基于形态学重构方法的磨损区域局部极值点提取方法,有效完成对磨损区域的检测和边界提取. 该刀具磨损检测方法成功应用于麻花钻头磨损状态的监测过程,实验结果表明,相较于目前已有的机器视觉监测方法,所提出的方法具有更高的检测精度和效率,准确地提取磨损轮廓,从而有效实现对刀具磨损状态的监测和自动化监控加工过程,达到降低人工成本和产品不合格率的目的.     

碳化物在高铬铸铁高应力磨料磨损中的影响

对不同载荷作用下的高铬铸铁在耐磨实验机上进行了磨料磨损试验;对在不同的碳化物对基体的保护作用与碳化物的剥离进行了相关的分析.结果表明载荷在一定值以下磨损较为缓慢,当载荷超过一定值时,磨损急剧加剧,随着载荷的增加"尺寸较小"的碳化物首先剥离基体,当载荷继续增大时,"尺寸较大"的碳化物也剥离基体并有碎裂现象.这要求高铬铸铁中的碳化物不仅要分布均匀,碳化物的尺寸也要合适.     

Dynamic “Molecular Portraits” of Biomembranes Drawn by Their Lateral Nanoscale Inhomogeneities

To date, it has been reliably shown that the lipid bilayer/water interface can be thoroughly characterized by a sophisticated so-called “dynamic molecular portrait”. The latter reflects a combination of time-dependent surface distributions of various physicochemical properties, inherent in both model lipid bilayers and natural multi-component cell membranes. One of the most important features of biomembranes is their mosaicity, which is expressed in the constant presence of lateral inhomogeneities, the sizes and lifetimes of which vary in a wide range—from 1 to 10³ nm and from 0.1 ns to milliseconds. In addition to the relatively well-studied macroscopic domains (so-called “rafts”), the analysis of micro- and nanoclusters (or domains) that form an instantaneous picture of the distribution of structural, dynamic, hydrophobic, electrical, etc., properties at the membrane-water interface is attracting increasing interest. This is because such nanodomains (NDs) have been proven to be crucial for the proper membrane functioning in cells. Therefore, an understanding with atomistic details the phenomena associated with NDs is required. The present mini-review describes the recent results of experimental and in silico studies of spontaneously formed NDs in lipid membranes. The main attention is paid to the methods of ND detection, characterization of their spatiotemporal parameters, the elucidation of the molecular mechanisms of their formation. Biological role of NDs in cell membranes is briefly discussed. Understanding such effects creates the basis for rational design of new prospective drugs, therapeutic approaches, and artificial membrane materials with specified properties.     

纳米TiN改性金属陶瓷刀片的铣削性能

制备了两种纳米TiN改性金属陶瓷可转位铣刀片ToolA和ToolB。研究了这两种新型面铣刀在切削正火态45#钢时的铣削性能及其失效机理。试验结果表明,两种试验铣刀片在Vc=294m/min,fz=0.16mm/z,ap=0.5mm条件下铣削45#钢时,均未发现“崩刃”现象,并全都以“磨损”的形式失效,刀具寿命较长。此外,在同样切削条件下,ToolA具有良好的抗氧化磨损性能,而ToolB有更高的耐机械冲击能力;高温扩散和氧化磨损成为导致纳米TiN改性铣刀片磨损失效的主要原因。     

Influence of alloy ingredients on mechanical properties of ternary boride hard alloy clad materials

Using Mo, B-Fe alloy and Fe powders as raw materials, and adding C, Cr and Ni ingredients, respectively, or C, Cr and Ni mixed powders, ternary boride hard alloy clad materials was prepared on Q235 steel substrate by means of in-situ reaction and vacuum liquid phase sintering technology. The influence of alloy ingredients on the mechanical properties of ternary boride hard alloy clad materials was investigated. The results indicate that a mixture of 0.8% C, 5% Cr and 2% Ni ingredients gives a ternary boride hard alloy clad material with optimal mechanical properties, such as high transverse rupture strength, high hardness and good wear resistance.