难加工材料可加工性分析方法的研究
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摘要
随着航空、航天、核能、兵器、化工、电子工业及现代机械工业的发展,难加工材料如不锈钢、钛合金、高温合金等得到了越来越广泛的应用。这些材料所具有的高温高强度、高硬度、高的硬质点含量及多相性等性能特征使其能很好地满足使用要求。然而,难加工材料的这些特殊特性又使得在切削加工过程中产生高温和高应力,导致加工条件恶化,刀具寿命短,产品表面质量差,加工效率低等问题。因此,研究难加工材料的可加工性,掌握其切削规律,寻求技术措施是切削加工领域的一个重要课题,也是直接关系到我国汽车、航空航天、能源等重要工业部门的发展速度和制造业整体水平。
材料的可加工性是指材料切削加工的难易程度,影响材料可加工性因素很多,如材料的物理机械性能、化学成分、微观组织等,而这些因素之间彼此又相互作用相互影响,同时评价材料可加工性的标准也随加工条件的不同而有所差异。正是由于加工条件的复杂性,影响材料可加工性因素的多样性使得如何科学地分析工件材料的可加工性成为一个机械制造领域的一个难点。
本论文旨在探索一种基于相位图对难加工材料的可加工性进行分析研究的新方法。论文通过分析难加工材料的化学成分、物理机械性能及加工特点,确定了影响难加工材料可加工性的五个关键物理机械性能指标,即硬度、延展性、加工硬化、导热性及磨蚀性；通过对这些性能指标与切削参数和切削刀具、切削结果等之间的关联关系的定性分析,建立关系模型,结合相位图示法,提出了难加工材料可加工性分析的相位图表达方法；在建立该相位图的过程中,完成了上述关键性能指标对可加工性影响的数学模型,进而建立了典型难加工材料如钛合金、不锈钢等的可加工性相位图,并从理论上进行了分析和论证；同时,以典型难加工材料Inconel 718镍基高温合金为例,完成了相关的试验研究,验证了材料可加工性图与切削参数选择及切削过程输出如刀具磨损之间的关系。在这些研究基础上,结合实例推理与专家系统,建立了基于材料可加工性图的难加工材料切削参数选择的专家系统。在该系统中,通过计算新实例和已有实例之间的相似度,从实例库中找到与新实例相符的已有实例的加工经验,充分运用已有的经验指导新材料的加工,帮助工程技术人员进行切削参数的选择和确定。
本文提出的用图示表达难加工材料可加工性的方法,能直观、综合地表达材料性能与材料可加工性之间的关系,同时将可加工性相位图应用到切削参数的选择,用于指导新材料或未知难加工材料试制条件的选择,可达到缩短试制周期和试制成本的目的。
Difficult-to-cut materials such as stainless steels, titanium alloys and super alloys, have been widely used in many industrial areas as aeronautics and astronautics, nuclear energy, chemical industry, weaponry, electronic industry and modern mechanical manufacturing. These materials always satisfy the actual application requirements due to their excellent properties like super strength at high temperatures, hardness, high contents of hard-inclusions and inhomogeneity. However, the high temperature and high stress occur in the cut machining processes, which could induce worse machining conditions and thus the short life of cutting tools, bad surface quality of products and low machining efficiency. Therefore, it is of great importance to investigate the machinability of difficult-to-cut materials, address the cutting performance and explore the related technical solutions. How to machine these super materials effectively is quite crucial to those key industries like automobile, energy, aeronautics and astronautics and also known as a challenge work in cutting fields.
Machinability is the property of a material which can be machined easily or difficultly by a cutting tool. The machinability of materials is always influenced by many factors like the physical properties, chemical contents and microstructures. Due to the diversity and the complex interactions among these factors and even the uncertain evaluation stands for the machinability under various cutting conditions, scientific description and evaluation of machinability is a challengeable work in the mechanical manufacture areas in recent years.
The present work aims to develop a novel method to evaluate and describe the machinability of difficult-to-cut materials using polar diagrams. Based on the analyzing of the chemical contents, the mechanical and physical properties and the machining characteristics of these materials, five key parameters, i.e., hardness, ductility, strain hardening, thermal conductivity and abrasiveness, have been employed to describe the machinability. The relationships between these properties and the cutting parameters, the cutting tools or cutting results, were investigated and the related formulas were obtained. The polar diagram method for the describing the machinability of difficult-to-cut materials has been developed and the models for the evaluation of the influence of those key proper parameters on the machinability have been proposed. By using this method, the polar diagrams of several typical stainless steels and titanium alloys, as examples, were obtained and the corresponding theoretical discussion and analysis were given. Furthermore, a nickel-based alloy, Inconel 718, was used as an example and industry experiments were conducted to demonstrate the relationships between the polar diagrams and the cutting parameters as well as the cutting results like the tool wear. By combining these related models and the case-based reasoning methodology, a novel intelligent expert system for the selection of proper cutting parameters according to machinability has been developed. By calculating the similarity degree between the machinability of a given material and those known materials, the expert system can help the engineers to determine the suitable cutting parameters for a given material by considering the machining experience of those known materials in the database.
The present polar diagram method can give a direct and integrated description of the relationship between the material properties and the machinability and therefore, can be applied to guide the selection of cutting conditions for new materials or unknown difficult-to-cut materials, which certainly could decrease the trial-machining time and process cost in machining these materials.
材料的可加工性是指材料切削加工的难易程度,影响材料可加工性因素很多,如材料的物理机械性能、化学成分、微观组织等,而这些因素之间彼此又相互作用相互影响,同时评价材料可加工性的标准也随加工条件的不同而有所差异。正是由于加工条件的复杂性,影响材料可加工性因素的多样性使得如何科学地分析工件材料的可加工性成为一个机械制造领域的一个难点。
本论文旨在探索一种基于相位图对难加工材料的可加工性进行分析研究的新方法。论文通过分析难加工材料的化学成分、物理机械性能及加工特点,确定了影响难加工材料可加工性的五个关键物理机械性能指标,即硬度、延展性、加工硬化、导热性及磨蚀性；通过对这些性能指标与切削参数和切削刀具、切削结果等之间的关联关系的定性分析,建立关系模型,结合相位图示法,提出了难加工材料可加工性分析的相位图表达方法；在建立该相位图的过程中,完成了上述关键性能指标对可加工性影响的数学模型,进而建立了典型难加工材料如钛合金、不锈钢等的可加工性相位图,并从理论上进行了分析和论证；同时,以典型难加工材料Inconel 718镍基高温合金为例,完成了相关的试验研究,验证了材料可加工性图与切削参数选择及切削过程输出如刀具磨损之间的关系。在这些研究基础上,结合实例推理与专家系统,建立了基于材料可加工性图的难加工材料切削参数选择的专家系统。在该系统中,通过计算新实例和已有实例之间的相似度,从实例库中找到与新实例相符的已有实例的加工经验,充分运用已有的经验指导新材料的加工,帮助工程技术人员进行切削参数的选择和确定。
本文提出的用图示表达难加工材料可加工性的方法,能直观、综合地表达材料性能与材料可加工性之间的关系,同时将可加工性相位图应用到切削参数的选择,用于指导新材料或未知难加工材料试制条件的选择,可达到缩短试制周期和试制成本的目的。
Difficult-to-cut materials such as stainless steels, titanium alloys and super alloys, have been widely used in many industrial areas as aeronautics and astronautics, nuclear energy, chemical industry, weaponry, electronic industry and modern mechanical manufacturing. These materials always satisfy the actual application requirements due to their excellent properties like super strength at high temperatures, hardness, high contents of hard-inclusions and inhomogeneity. However, the high temperature and high stress occur in the cut machining processes, which could induce worse machining conditions and thus the short life of cutting tools, bad surface quality of products and low machining efficiency. Therefore, it is of great importance to investigate the machinability of difficult-to-cut materials, address the cutting performance and explore the related technical solutions. How to machine these super materials effectively is quite crucial to those key industries like automobile, energy, aeronautics and astronautics and also known as a challenge work in cutting fields.
Machinability is the property of a material which can be machined easily or difficultly by a cutting tool. The machinability of materials is always influenced by many factors like the physical properties, chemical contents and microstructures. Due to the diversity and the complex interactions among these factors and even the uncertain evaluation stands for the machinability under various cutting conditions, scientific description and evaluation of machinability is a challengeable work in the mechanical manufacture areas in recent years.
The present work aims to develop a novel method to evaluate and describe the machinability of difficult-to-cut materials using polar diagrams. Based on the analyzing of the chemical contents, the mechanical and physical properties and the machining characteristics of these materials, five key parameters, i.e., hardness, ductility, strain hardening, thermal conductivity and abrasiveness, have been employed to describe the machinability. The relationships between these properties and the cutting parameters, the cutting tools or cutting results, were investigated and the related formulas were obtained. The polar diagram method for the describing the machinability of difficult-to-cut materials has been developed and the models for the evaluation of the influence of those key proper parameters on the machinability have been proposed. By using this method, the polar diagrams of several typical stainless steels and titanium alloys, as examples, were obtained and the corresponding theoretical discussion and analysis were given. Furthermore, a nickel-based alloy, Inconel 718, was used as an example and industry experiments were conducted to demonstrate the relationships between the polar diagrams and the cutting parameters as well as the cutting results like the tool wear. By combining these related models and the case-based reasoning methodology, a novel intelligent expert system for the selection of proper cutting parameters according to machinability has been developed. By calculating the similarity degree between the machinability of a given material and those known materials, the expert system can help the engineers to determine the suitable cutting parameters for a given material by considering the machining experience of those known materials in the database.
The present polar diagram method can give a direct and integrated description of the relationship between the material properties and the machinability and therefore, can be applied to guide the selection of cutting conditions for new materials or unknown difficult-to-cut materials, which certainly could decrease the trial-machining time and process cost in machining these materials.
引文
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