考虑刀具磨损的机床能耗建模及多目标优化方法研究

发布时间：2018-05-01 01:04

本文选题：机床能耗建模 + 刀具磨损　；参考：《哈尔滨工业大学》2017年硕士论文

【摘要】：制造业是我国经济发展的重要力量,是国民经济的重要组成部分。但制造业发展的同时,也带来了大量的能源与资源消耗。同时各类废弃物的排放也对自然环境带来了巨大威胁与挑战。如何提高能源利用率,降低能源消耗是我们所要迎接的重大挑战。在制造加工过程中,利用刀具进行切削加工占据很大比重。刀具的磨损会使得机床加工精度降低,能耗及加工成本提高。因此在对机床能耗进行研究的过程中考虑刀具磨损对能耗的影响具有重要意义。本文将对机床的能源消耗组成进行分析,按机床不同加工状态对机床能耗情况进行分析研究。同时,以往的机床能耗建模多从切削力与加工参数两个角度进行研究,忽视了加工过程中刀具状态对机床能耗的影响。本文对机床加工过程中刀具的磨损情况随机床加工进行的变化规律进行分析,并对刀具磨损程度与机床能耗的影响关系进行研究,在进行试切削实验的基础上建立了考虑刀具磨损的机床能耗函数关系模型。通过切削实验对机床加工参数与刀具磨损状态对机床能耗影响关系进行研究。利用响应曲面法进行实验设计与分析,并设计实验验证了模型的准确性。通过对实验数据分析得出了机床加工参数与机床切削加工过程能耗之间的影响关系,分析了各影响因素之间的主次顺序及交互作用。之后设计空切削实验建立了机床空切削过程能耗模型,最终得到完整的考虑刀具磨损的机床能耗模型。工件表面粗糙度是衡量工件加工质量的重要指标,对机械产品的使用寿命和可靠性有重要影响。本文研究了机床加工条件对工件表面粗糙度的影响关系。通过实验方法建立了工件表面粗糙度与加工条件之间的函数模型。利用已建立的考虑刀具磨损程度的机床加工功率和加工工件表面粗糙度模型,确定一种刀具状态监测方法以实现对刀具加工状态的实时监测。在进行机械加工过程中,合理的选择切削用量可以减少机床加工时间、提高工件加工质量以及缩减能源消耗,最终实现节能减排节能减排。本文在机床能耗模型及加工工件表面粗糙度模型的研究基础上,将对考虑机床加工效率、工件表面质量以及机床加工能耗的加工参数多目标优化问题进行研究。通过粒子群算法进行优化,采用灰色关联度分析方法确定多目标权重,最终给出机床加工参数优化值。将优化结果与经验参数结果进行比较,验证了优化方法的先进性与合理性。最终给出不同条件下机床加工参数的推荐值。
[Abstract]:Manufacturing industry is an important force of economic development and an important part of national economy. However, the development of manufacturing industry has also brought a lot of energy and resource consumption. At the same time, the emission of all kinds of waste also brings great threats and challenges to the natural environment. How to improve energy efficiency and reduce energy consumption is a major challenge we have to meet. In the manufacturing process, cutting tools occupy a large proportion. Tool wear will reduce machining accuracy, increase energy consumption and machining cost. Therefore, it is of great significance to consider the influence of tool wear on the energy consumption in the process of studying the energy consumption of machine tools. In this paper, the energy consumption composition of machine tool is analyzed, and the energy consumption of machine tool is analyzed according to different machining state of machine tool. At the same time, the former modeling of machine tool energy consumption is mostly studied from two angles of cutting force and machining parameters, ignoring the influence of cutting tool state on machine tool energy consumption in the process of machining. In this paper, the variation law of tool wear with machine tool processing is analyzed, and the influence of tool wear degree on machine tool energy consumption is studied. On the basis of experimental cutting experiments, a functional model of machine tool energy consumption considering tool wear is established. The influence of machining parameters and tool wear state on the energy consumption of machine tools was studied by cutting experiments. The response surface method is used for experimental design and analysis, and the accuracy of the model is verified by designing experiments. Through the analysis of the experimental data, the relationship between the machining parameters and the energy consumption in the machining process is obtained, and the order and interaction among the factors are analyzed. Then, the energy consumption model of the machine tool is established by designing the empty cutting experiment, and finally, the complete energy consumption model of the machine tool considering tool wear is obtained. The surface roughness of workpiece is an important index to measure the machining quality of workpiece, which has an important influence on the service life and reliability of mechanical products. The influence of machining conditions on workpiece surface roughness is studied in this paper. The functional model between workpiece surface roughness and machining conditions is established by experimental method. Based on the established model of machining power and workpiece surface roughness which considers the degree of tool wear, a tool condition monitoring method is established to realize the real-time monitoring of cutting tool status. In the process of machining, reasonable selection of cutting parameters can reduce machine tool processing time, improve the quality of workpiece processing and reduce energy consumption, and finally achieve energy saving and emission reduction. Based on the research of machine tool energy consumption model and machining workpiece surface roughness model, the multi-objective optimization problem of machining parameters considering machine tool machining efficiency, workpiece surface quality and machine tool energy consumption is studied in this paper. Particle swarm optimization (PSO) algorithm is used to determine the weight of multi-objective. Finally, the optimization value of machining parameters is given. The results of optimization and empirical parameters are compared to verify the advantage and rationality of the optimization method. Finally, the recommended values of machining parameters under different conditions are given.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TG502

【相似文献】