Investigation on tool wear and tool life prediction in micro-milling of Ti-6Al-4V

Short tool life and rapid tool wear in micromachining of hard-to-machine materials remain a barrier to the process being economically viable. In this study, standard procedures and conditions set by the ISO for tool life testing in milling were used to analyze the wear of tungsten carbide micro-end-milling tools through slot milling conducted on titanium alloy Ti-6 Al-4 V. Tool wear was characterized by flank wear rate,cutting-edge radius change, and tool volumetric change. The effect of machining parameters, such as cutting speed and feedrate, on tool wear was investigated with reference to surface roughness and geometric accuracy of the finished workpiece. Experimental data indicate different modes of tool wear throughout machining, where nonuniform flank wear and abrasive wear are the dominant wear modes. High cutting speed and low feedrate can reduce the tool wear rate and improve the tool life during micromachining.However, the low feedrate enhances the plowing effect on the cutting zone, resulting in reduced surface quality and leading to burr formation and premature tool failure. This study concludes with a proposal of tool rejection criteria for micro-milling of Ti-6 Al-4 V.

WEAR AND LIFE OF PCBN TOOLS WHEN DRY-CUTTING BEARING STEEL GCr15

The wear forms and reasons of PCBN tools when dry-cutting bearing steel GCr15are studied systematically. The effect law of the workpiece hardness on PCBN tools is gained andtool wearing with the quickest speed at the workpiece critical hardness is proved. The life equationat two kinds of workpiece hardness demonstrates that the effect of the cutting speed on the PCBNtool life is less than that of carbide tools and ceramic tools.

Influences of Tool Wear on Residual Stress and Fatigue Life of Workpiece in Hard Cutting Process

Tool wear has an important influence on the residual stress distribution on the machined surface.Also,it will influence the fatigue life of finished workpiece. In this research,the hard turning process of hardened die steel Cr12 MoV was studied by using PCBN tool with considering tool wear. Based on the numerical treatment of residual stress,the dispersion and distribution curves of different tool wear were fitted,and the influence mechanism of tool wear on the residual stress distribution of machined surface was analyzed.Based on the theory of fatigue mechanics and mathematical statistics,the mathematical model for difference of stress dispersion and fatigue life was established. The rotating and bending tests were carried out on the standard parts after cutting process for the workpiece. The influence of tool wear on fatigue life was revealed by fracture surface morphology and fatigue life study. The results provide theoretical support for control of residual stress and the fatigue property of the machined surface under the actual working conditions.

Crystalline and amorphous metal sulfide composite electrode materials with long cycle life:Preparation and performance of hybrid capacitors

Crystalline@amorphous NiCo_(2)S_(4)@MoS_(2)(v-NCS@MS)nanostructures were designed and constructed via an ethylene glycol-induced strategy with hydrothermal synthesis and solvothermal method,which simultaneously realized the defect regulation of crystal NiCo_(2)S_(4) in the core.Taking advantage of the flexible protection of an amor-phous shell and the high capacity of a conductive core with defects,the v-NCS@MS electrode exhibited high specif-ic capacity(1034 mAh·g^(-1) at 1 A·g^(-1))and outstanding rate capability.Moreover,a hybrid supercapacitor was assembled with v-NCS@MS as cathode and activated carbon(AC)as anode,which can achieve remarkably high specific energy of 111 Wh·kg^(-1) at a specific power of 219 W·kg^(-1) and outstanding capacity retention of 80.5%after 15000 cycling at different current densities.

Influence of Machining Parameter on Tool Life While Machining Hybrid Metal Matrix Composites

A metal matrix composite constitutes a continuous metallic matrix and a discontinuous phase known as reinforcement. The hybrid metal matrix composites (Hmmcs) have been used to manufacture drive shafts, disc brake rotors, brake drums, connecting rods pistons, engine block cylinder liners for automotive and rail vehicle applications. The Hmmcs castings of diameter 120 mm and length 300 mm were prepared through sand mould technique following stir casting methodology. The cast components further subjected to evaluation of physical properties and machining tests using two grades of coated inserts and PCD inserts. The experiments were carried out following ISO 3685 standards. The coating thickness of the TiN coated and TiAlN coated inserts were measured using Kalo testing method; the results of the test show that the interface of the substrate and coating was free from the porosity, and the coating thickness of TiN coating was 4.84 microns and TiAlN coating was measured 4.6 microns. The results of the experiments show that performance of the PCD insert was better than coated inserts at 0.1 mm/rev feed; however at 0.2 mm/revolution feed PCD insert failed by micro chipping of cutting edge while machining Hmmcs. When TiAlN coated inserts were used to machine Hmmcs the coated inserts failed by gradual wear and BUE formation.

Life Prediction Model of Machine Tool based on Deep Learning

In view of the shortage of traditional life prediction methods for machine tools,such as low accuracy of life prediction and few samples basis attributes,a life prediction model of machine tools combined with machine tool attributes is proposed.The life prediction model of machine tool adopts KL dispersion distribution theory,uses modal superposition method to carry out machine tool life analysis,calculates the theoretical life of machine tool,and then carries on the simulation,obtains the machine tool life prediction value.Compared with the traditional method of machine tool life prediction,the model is based on the application life fatigue damage model,which superimposes the service times and maintenance cycle of the machine tool,derives the influence factor of machine tool life,and obtains the linear relationship between the influence factor of machine tool life and the life of machine tool.The influence factor of machine tool life is introduced as the life prediction parameter of machine tool.The data transformation relationship of HT300 parts is constructed.The original part data is enhanced.The effective training set is obtained.The life prediction model of machine tool based on deep learning is completed.The quantitative analysis of machine tool life is carried out.The experiment of machine tool life prediction using training data set proves the validity of the model.Regression test was carried out on the training data set to reflect the robustness of the model.The prediction accuracy of the model is further verified by Weibull test.

Tool life modeling for evaluating the effects of cutting speed and reinforcements on the machining of particle reinforced metal matrix composites

The wear of cutting tools in the machining of 2024Al alloy composites reinforced with Al2O3 particles using varying sizes and volume fractions of particles up to 23.3vol% was investigated by a turning process using coated carbide tools K10 and TP30 at different cut- ting speeds. Machining tests were performed with a plan of experiments based on the Taguchi method. The tool life model was developed in terms of cutting speed, size, and volume fraction of particles by multiple linear regressions. The analysis of variance （ANOVA） was also employed to carry out the effects of these parameters on the cutting tool life. The test results show that the tool life decreases with the increase of cutting speed for both cutting tools K10 and TP30, and the tool life of the K10 tool is significantly longer than that of the TP30 tool. For the tool life, cutting speed is found to be the most effective factor followed by particle content and particle size, respectively. The predicted tool life of cutting tools is found to be in very good agreement with the experimentally observed ones.

Research on the Seebeck effect in efficient turning process and improving tool life

In this paper, for the tool wear problem of the cutting process, the study on improving tool life has been done through the analysis of the Seebeck effect in the efficient turning process. The generation principle of the self-excited electric current in the cutting process is studied, and also its effect on the life of the turning cutter is studied, so as to reveal the mechanism of the self-excited electric current accelerating the wear of cutting tools. The study results show that the self-excited electric current which is generated during the cutting process is one of the main reasons that cause both the accelerated hardening and the low life of cutting tools to happen. Thus, if the generation of self-excited current is avoided and reduced, the cutting performance of cutting tools can be effectively improved, so to improve the tool life. The study can provide the anti-friction and anti-wear theory basis for the design of the efficient cutting tools.

Influence of Machining Parameter on Surface Roughness and Tool Life While Machining EN24 Grade Alloy Steel

The requirements of high quality machined surface as well as demand of enhanced contact time of cutting tools drive towards adopting multilayer coated carbide inserts. The industry requires higher productivity, hence higher machining parameters need to be used in order to meet the industry requirements. The alloy steel material used to fabricate machine parts consists of alloying elements like nickel, chromium and molybdenum difficult to machine, since the cutting tool fails by high tool wear, if we use uncoated carbide inserts to machine alloy steels. Hence in the present research work it is intended to use tungsten carbide inserts coated with different coatings for the experiments. The turning experiments were carried out using different grades of uncoated and coated carbide inserts of identical tool signature. The cutting speed selected for the experiments was 100 to 500 m/min in steps of 100 m/min, and the feed per revolution was 0.1 mm to 0.4 mm in step of 0.1 mm. The experimentation was carried out following ISO3685 standards. The results of the experiments revealed that the surface roughness measured was the least at cutting speed 500 m/min and feed per revolution of 0.1 mm, however the chip breaking found better when the feed used was greater than 0.2 mm/revolution.

A multi-source information fusion method for tool life prediction based on CNN-SVM

For milling tool life prediction and health management,accurate extraction and dimensionality reduction of its tool wear features are the key to reduce prediction errors.In this paper,we adopt multi-source information fusion technology to extract and fuse the features of cutting vibration signal,cutting force signal and acoustic emission signal in time domain,frequency domain and time-frequency domain,and downscale the sample features by Pearson correlation coefficient to construct a sample data set;then we propose a tool life prediction model based on CNN-SVM optimized by genetic algorithm(GA),which uses CNN convolutional neural network as the feature learner and SVM support vector machine as the trainer for regression prediction.The results show that the improved model in this paper can effectively predict the tool life with better generalization ability,faster network fitting,and 99.85%prediction accuracy.And compared with the BP model,CNN model,SVM model and CNN-SVM model,the performance of the coefficient of determination R2 metric improved by 4.88%,2.96%,2.53%and 1.34%,respectively.

Life′s Simple 7干预减轻Her⁃2阳性乳腺癌患者化疗相关心血管系统损害的研究

目的探讨Life′s Simple 7(LS7)干预减轻Her⁃2阳性乳腺癌患者根治术后化疗相关心血管系统损害的作用。方法将120例Her⁃2阳性并接受标准化乳腺癌化疗的患者随机等量分为对照组及LS7组,对照组为标准化疗方案,LS7组为对照组基础上给予LS7干预12个月,后续通过比较两组治疗前后心血管系统损伤程度、焦虑、抑郁及生活质量等指标评价其对心血管系统损害的改善作用。结果相较于对照组,LS7组LS7总评分及7项心血管健康指标均优于对照组(P<0.05),LS7组LVEF较高(P<0.05)、NT⁃proBNP较低(P<0.05),焦虑和抑郁评分较低(P<0.05)、生活质量评分较高(P<0.05)。结论LS7干预可显著减轻Her⁃2阳性乳腺癌化疗相关心血管系统损害并改善乳腺癌患者的心理状况和生活质量,值得在临床推广。

基于nCode Design-Life的某车架疲劳可靠性分析

针对某型半挂牵引车车架局部出现裂纹或者断裂现象,通过有限元理论和疲劳分析理论相结合进行了车架的有限元分析和疲劳可靠性分析。首先对该车架进行了建模和有限元静态特性分析,然后定义了特定的时间载荷序列数据和材料参数,选用了S-N疲劳设计和静态疲劳分析方法,利用疲劳分析软件nCode Design-Life对该车架进行疲劳可靠性分析,得出该车架的疲劳结果云图和各节点的疲劳寿命,并从相关云图中确定出车架容易破坏的位置和其寿命之后再进行样车实验验证。

小学英语绘本教学中提问设计的研究——基于Good Thinker’s Tool Kit框架

基于“有效的问题设计可以促进学生自主思考”这一理论假设，该课题组教师在瑞士一所小学进行英文绘本教学时开展了实证研究。通过对比实验组与对照组的教学效果及问卷调查，证明以GoodThinker’s ToolKit为指导的问题设计框架可以有效促进学生的心智发展，培养他们自主思考的能力。

A Model of the Fatigue Life Distribution of Composite Laminates Based on Their Static Strength Distribution

The reasons of the static strength dispersion and the fatigue life dispersion of composite laminates are analyzed in this article. It is concluded that the inner original defects, which derived from the manufacturing process of composite laminates, are the common and major reason of causing the random distributions of the static strength and the fatigue life. And there is a correlative relation between the two distributions. With the study of statistical relationship between the fatigue loading and the fatigue life in the uniform confidence level and the same survival rate S-N curves of material, the relationship between the static strength distribution and the fatigue life distribution through a material S-N curve model has been obtained. And then the model which is used to describe the distributions of fatigue life of composites, based on their distributions of static strength, is set up. This model reasonably reflects the effects of the inner original defects on the static strength dispersion and on the fatigue life dispersion of composite laminates. The experimental data of three kinds of composite laminates are employed to verify this model, and the results show that this model can predict the random distributions of fatigue life for composites under any fatigue loads fairly well.

基于断裂力学的腐蚀钢丝疲劳S-N曲线研究

高强冷拔钢丝因其优异的力学性能被广泛应用于缆索承重结构,服役过程中钢丝腐蚀与断裂威胁着结构安全。钢丝腐蚀后表面的蚀坑因应力集中效应易产生疲劳裂纹,因此腐蚀钢丝剩余疲劳寿命主要取决于裂纹的扩展阶段,且裂纹扩展受到腐蚀程度(初始损伤)的显著影响。精确表征腐蚀程度并准确评估服役期钢丝腐蚀后的剩余寿命,仍是亟待解决的维修难题。首先采用蚀坑最大深度表征钢丝腐蚀程度,以应力强度因子幅作为裂纹扩展驱动力指标,基于断裂力学的Paris公式建立受拉钢丝裂纹扩展理论模型,进而推导腐蚀钢丝的疲劳S-N曲线。大量既有的腐蚀钢丝疲劳试验结果与理论预测值的比较验证了所提理论模型及疲劳S-N曲线的合理性和有效性。含多个蚀坑的钢丝裂纹扩展有限元模拟表明,等效单裂纹适用于多腐蚀坑钢丝疲劳寿命的简化分析。参数分析表明,蚀坑深度和腐蚀环境是腐蚀钢丝疲劳强度的关键影响因素,而应力比和疲劳加载频率影响较小,所提出的S-N曲线在钢丝常规服役条件下适用于评估其剩余寿命,可得到合理的预测结果。基于断裂力学所提的理论方法和疲劳S-N曲线可为腐蚀钢丝的疲劳强度和寿命评估提供参考。

基于nCode Design-Life的电动客车车架疲劳寿命分析

针对某型电动客车车架疲劳及寿命问题,本文以有限元理论和疲劳分析理论相结合的方法,对电动客车车架进行静强度分析和疲劳寿命校核,建立有限元模型并进行受力分析,定义特定的载荷谱和材料疲劳数据;同时利用S-N静态疲劳设计方法,选用疲劳分析软件nCode Design-Life对该车架进行疲劳可靠性分析。分析结果表明,该车架的疲劳寿命为1.558×106次,许用行驶里程为650 000km,与公交客运车行驶里程参考值约为400 000km相比,结果满足要求。该研究实现了电动车减重节能,增加了续驶里程,为车架优化设计及寿命模型的建立提供了理论依据。

Impact of body mass index and gender on quality of life in patients with gastroesophageal reflux disease

AIM： To investigate the symptom presentation and quality of life in obese Chinese patients with gastro- esophageal reflux disease （GERD）. MKTHODS： Data from patients diagnosed with GERD according to the Montreal definition, were collected between January 2009 to March 2010. The enrolled patients were assigned to the normal [body mass in- dex （BMI） 〈 25 kg/m2], overweight （25-30 kg/m2）, and obese （BMI 〉 30 kg/m2） groups. General demographic data, endoscopic findings, and quality of life of the three groups of patients were analyzed and compared.and 15 patients were classified in the normal, over- weight, and obese, respectively. There was significantly more erosive esophagitis （73.3% vs 64.3% vs 39.2%, P = 0.002）, hiatal hernia （60% vs 33.9% vs 16.7%, P = 0.001）, and males （73.3% vs 73.2% vs 32.4%, P = 0.001） in the obese cases. The severity and frequency of heartburn, not acid regurgitation, was positively cor- related with BMI, with a significant association in men, but not in women. Obese patients were prone to have low quality of life scores, with obese women having the lowest scores for mental health. CONCLUSION： In patients with GERD, obese men had the most severe endoscopic and clinical presenta- tion. Obese women had the poorest mental health.

Higher vitamin D serum concentration increases health related quality of life in patients with inflammatory bowel diseases

AIM: To investigate the effect of vitamin D (VD) concentrations and VD supplementation on health related quality of life in inflammatory bowel disease (IBD) patients.

基于nCode Design-Life的重型起重设备疲劳寿命预测研究

为研究重型起重设备的疲劳损伤和寿命,以门式起重机为算例建立有限元模型,通过有限元静力学分析,最大等效应力位于跨中受拉区,得出门式起重机强度和刚度满足要求。采用nCode Design-Life疲劳仿真软件利用S-N疲劳设计方法对有限元静力学特性和疲劳损伤进行分析,得到门式起重机疲劳寿命分布云图和疲劳损伤云图,其最小寿命满足工程要求。为了研究载荷变化对起重机寿命的影响,通过改变载荷缩放因子来改变时间载荷序列的大小,对比分析载荷变化后的寿命情况,得出随机载荷减小门式起重机寿命大大增加,过载对门式起重机的疲劳寿命有显著的影响。

Fatigue life evaluation on key components of high-speed railway catenary system

The fatigue load spectrum and operation life evaluation of key components in the catenary system under the high speed train running condition were investigated.Firstly,based on the catenary model and pantograph model,the couple dynamic equations of pantograph–catenary were built with the Lagrange’s method;then the dynamic contact force was obtained by the Newmark method at the train speeds of 250,280 and 300 km/h,respectively.Secondly,the finite element model(FEM)of one anchor section’s catenary was built to analyze its transient response under the contact force as train running;then the loading time history of messenger wire base,steady arm,registration tube,oblique cantilever,and straight cantilever were extracted.Finally,the key components’fatigue spectrum was carried out by the rain-flow counting method,and operation life was estimated in consideration of such coefficients,such as stress concentration,shape and dimension,surface treatment.The results show that the fatigue life of the catenary system reduces with the increasing of train speed;specifically,the evaluated fatigue life of the steady arm is shorter than other components.