淬硬45钢车削加工的研究

"以车代磨"切削加工淬硬材料,经济优势明显。使用涂层硬质合金刀具材料车削淬火45钢,合理的刀具几何参数,恰当的切削用量,是保证车削顺利实现的关键。实验证明,使用涂层硬质合金刀具,采用较高的切削速度,吃刀深度ap≤0.1mm、进给量f≤0.1mm时,车削淬火45钢可以达到表面粗糙度R≈0.2～0.5μm,刀具耐用度与车削非淬火钢时相当,可以代替磨削加工。     

切削用量对车削42CrMo钢切削力的影响

在单因素条件下通过改变切削用量车削42CrMo钢试验,得出了切削用量的改变对主切削力、进给力、背向力与总切削力的影响规律,分析了切削用量的改变导致切削力变化的原因,提供了车削42CrMo钢半精加工阶段的参考切削用量。结果表明:背吃刀量和进给量的改变对主切削力的影响较大,而切削速度的改变对主切削力影响较小;总切削力的变化规律与主切削力相似,背吃刀量对进给力的影响较大。     

Comparison of one-dimensional and multi-dimensional models in stability analysis of turning operations

Chatter is one of the main problems in machining resulting in poor surface quality and low productivity. Chatter can be avoided by applying stability diagrams which are generated using stability models. The stability analysis of turning has mostly been performed using single dimensional, so-called oriented transfer function approach whereas the actual turning processes usually involve multi-dimensional dynamics. In this paper, a comparative analysis between one dimensional (1D) and multi-dimensional stability models is given for turning operations. The multi dimensional model includes the inclination and side edge cutting angles and insert nose radius in order to demonstrate their effect on absolute stable depth of cut predictions. Chatter experiments are conducted in order to compare with both model predictions. It is demonstrated that for higher inclination angles and insert nose radii 1D models result in significant errors, and multi-dimensional solutions are required.     

Prediction of flank wear by using back propagation neural network modeling when cutting hardened H-13 steel with chamfered and honed CBN tools

Productivity and quality in the finish turning of hardened steels can be improved by utilizing predicted performance of the cutting tools. This paper combines predictive machining approach with neural network modeling of tool flank wear in order to estimate performance of chamfered and honed Cubic Boron Nitride (CBN) tools for a variety of cutting conditions. Experimental work has been performed in orthogonal cutting of hardened H-13 type tool steel using CBN tools. At the selected cutting conditions the forces have been measured using a piezoelectric dynamometer and data acquisition system. Simultaneously flank wear at the cutting edge has been monitored by using a tool makers microscope. The experimental force and wear data were utilized to train the developed simulation environment based on back propagation neural network modeling. A trained neural network system was used in predicting flank wear for various different cutting conditions. The developed prediction system was found to be capable of accurate tool wear classification for the range it had been trained.     

Progressive cutting tool wear detection from machined surface images using Voronoi tessellation method

Tool condition monitoring by machine vision approach has been gaining popularity day by day since it is a low cost and flexible method. In this paper, a tool condition monitoring technique by analysing turned surface images has been presented. The aim of this work is to apply an image texture analysis technique on turned surface images for quantitative assessment of cutting tool flank wear, progressively. A novel method by the concept of Voronoi tessellation has been applied in this study to analyse the surface texture of machined surface after the creation of Voronoi diagram. Two texture features, namely, number of polygons with zero cross moment and total void area of Voronoi diagram of machined surface images have been extracted. A correlation study between measured flank wear and extracted texture features has been done for depicting the tool flank wear. It has been found that number of polygons with zero cross moment has better linear relationship with tool flank wear than that of total void area.     

车削加工轴受弹性约束的变温应力计算

本文计算了车削加工中工件承受弹性(或部分)约束及主轴热伸长影响情况下轴的变温应力.文章将工艺系统刚度和热变形两个因素引入变温应力计算公式中,提高了轴受弹性(或部分)约束的变温应力计算精度,为提高零件加工精度提供了理论依据.     

Intelligent Programming of CNC Turning Operations using Genetic Algorithm

CAD/CAM systems are nowadays tightly connected to ensure that CAD data can be used for optimal tool path determination and generation of CNC programs for machine tools. The aim of our research is the design of a computer-aided, intelligent and genetic algorithm(GA) based programming system for CNC cutting tools selection, tool sequences planning and optimisation of cutting conditions. The first step is geometrical feature recognition and classification. On the basis of recognised features the module for GA-based determination of technological data determine cutting tools, cutting parameters (according to work piece material and cutting tool material) and detailed tool sequence planning. Material, which will be removed, is split into several cuts, each consisting of a number of basic tool movements. In the next step, GA operations such as reproduction, crossover and mutation are applied. The process of GA-based optimisation runs in cycles in which new generations of individuals are created with increased average fitness of a population. During the evaluation of calculated results (generated NC programmes) several rules and constraints like rapid and cutting tool movement, collision, clamping and minimum machining time, which represent the fitness function, were taken into account. A case study was made for the turning operation of a rotational part. The results show that the GA-based programming has a higher efficiency. The total machining time was reduced by 16%. The demand for a high skilled worker on CAD/CAM systems and CNC machine tools was also reduced. Received: September 2004 / Accepted: September 2005     

A knowledge-based system for the prediction of surface roughness in turning process

In the present work, a knowledge-based system is developed for the prediction of surface roughness in turning process. Neural networks and fuzzy set theory are used for this purpose. Knowledge acquired from the shop floor is used to train the neural network. The trained network provides a number of data sets, which are fed to a fuzzy-set-based rule generation module. A large number of IF–THEN rules are generated, which can be reduced to a smaller set of rules by using Boolean operations. The developed rule base may be used for predicting surface roughness for given process variables as well as for the prediction of process variables for a given surface roughness. The concise set of rules helps the user in understanding the behavior of the cutting process and to assess the effectiveness of the model. The performance of the developed knowledge-based system is studied with the experimental data of dry and wet turning of mild steel with HSS and carbide tools.     

转折物元辨析

本文探讨转折物元的概念、功能与特色．提出了两种类型的转折物元定义．     

Integrated Simulation of Machine Tool and Process Interaction for Turning

The interaction between process and machine tool behaviour can lead to process instabilities in terms of self‐excited vibrations where the energy of the machine tool oscillation is generated by process excitation. The regenerative chatter effects lead to wavy surfaces on the work‐piece. This effect has been simulated for turning processes with an integrated simulation approach, which couples a time domain simulation model for the machine tool and the workpiece with an analytical turning model. In this paper a procedure is illustrated for coupling an FEA‐based 3‐dimensional turning model with the time domain model for the machine tool under consideration of the resulting workpiece surface. In comparison to an analytical approach for calculating the mechanical tool load, the 3D‐FEA‐model has the potential to determine the resulting cutting forces for even complex‐shaped tool geometries, e.g. a complicated chip breaker or a varying cutting edge radius on the main or minor cutting edge. As a matter of the huge model size the calculation time in particular for 3‐dimensional problems is comparatively long to analytical cutting force models. Therefore, in this paper an approach to reduce the calculation time by using characteristic diagrams for the calculated process forces in the FEA‐model is presented. The research has also been focused on the current major problem in the FEA‐based modelling that the thrust and feed forces are generally underestimated in the simulation.