基于元动作单元的数控机床精密剩余使用寿命预测分析

IF 1.9 3区 工程技术 Q3 ENGINEERING, MANUFACTURING
Junfa Li, Minghui Gu, Yulong Li, Shutao Wen, Genbao Zhang
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引用次数: 0

摘要

考虑到数控机床运动误差传播的动态特性,为了提高 PRUL(精度剩余使用寿命)预测分析的精度,本文提出了一种基于 MAU(元动作单元)的数控机床精度退化建模方法。首先,从运动的角度,通过 FMA(功能-运动-动作)分解将数控机床划分为最小单元。其次,利用 MBS(多体系统)理论拓扑描述 MAU 之间的运动关系,并利用旋量理论建立运动误差模型。再次,考虑到多个误差源对数控机床 MAU 的 PRUL 的影响,利用运动传递比合成多个误差源,并结合构建的误差模型,构建 MAU 的精度退化模型,准确预测其 PRUL。最后,选择数控转台作为实验对象,从合理性、适用性和简便性等方面将本文提出的方法与常用方法进行比较,结果验证了本文提出的方法的适用性和正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive analysis of the precision remaining useful life of CNC machine tools based on meta-action unit
Taking into consideration the dynamic characteristics of motion error propagation in CNC machine tools, in order to enhance the accuracy of PRUL (precision remaining useful life) prediction analysis, this paper presents a precision degradation modeling approach based on MAU (meta-action unit) for CNC machine tools. Firstly, from the perspective of motion, the CNC machine tool is divided into the smallest unit by the decomposition of FMA (Function-Motion-Action). Secondly, the MBS (multi-body systems) theory is used to topologically describe the motion relationship between the MAU, and the spinor theory is used to model the motion error. Thirdly, considering the influence of multiple error sources on the PRUL of the CNC machine tool MAU, the motion transmission ratio is used to synthesize multiple error sources, and combined with the constructed error model, the precision degradation model of MAU is constructed, and its PRUL is accurately predicted. Finally, the CNC turntable is selected as the experimental subject to compare the proposed method with commonly used methods in terms of rationality, applicability, and simplicity, and the results verify the applicability and correctness of the method proposed in this paper.
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来源期刊
CiteScore
5.10
自引率
30.80%
发文量
167
审稿时长
5.1 months
期刊介绍: Manufacturing industries throughout the world are changing very rapidly. New concepts and methods are being developed and exploited to enable efficient and effective manufacturing. Existing manufacturing processes are being improved to meet the requirements of lean and agile manufacturing. The aim of the Journal of Engineering Manufacture is to provide a focus for these developments in engineering manufacture by publishing original papers and review papers covering technological and scientific research, developments and management implementation in manufacturing. This journal is also peer reviewed. Contributions are welcomed in the broad areas of manufacturing processes, manufacturing technology and factory automation, digital manufacturing, design and manufacturing systems including management relevant to engineering manufacture. Of particular interest at the present time would be papers concerned with digital manufacturing, metrology enabled manufacturing, smart factory, additive manufacturing and composites as well as specialist manufacturing fields like nanotechnology, sustainable & clean manufacturing and bio-manufacturing. Articles may be Research Papers, Reviews, Technical Notes, or Short Communications.
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