优化机械产品质量的改进型雅各布-托索模型

Yazui Liu, Haodong Shen, Gang Zhao, Xishuang Jing, Xiaoxiao Du
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引用次数: 0

摘要

装配质量在很大程度上取决于选择性装配过程中装配偏差模型的预测精度。目前,三维偏差分析方法仅能提供显示零件特征整体偏差的公差。这种局限性无法准确反映装配过程中零件的配合情况,从而导致选择性装配模型的初始误差。为解决这一问题,我们提出了一种改进的雅各布-托索模型,将零件装配特征的测量数据纳入偏差分析模型。首先,通过测量平面配合和轴孔配合的接触面来确定装配的实际接触状态。接着,通过分析装配连接图,构建代表装配偏差传输路径的雅各布矩阵。随后,通过将以小位移转矩(SDT)为特征的实际接触状态整合到统一的雅各布-转矩模型中,提供了高可信度公差传播的优势。最后,利用双关节机械手验证了所提出的改进雅各布-托索模型的可行性。
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Improved Jacobian-Torsor model for optimizing mechanical product quality
The quality of an assembly largely depends on the predictive accuracy of the assembly deviation model in the selective assembly process. Presently, three-dimensional deviation analysis methods only offer tolerances that indicate the overall deviation of a part feature. This limitation fails to accurately represent the fit of the parts during the assembly process, resulting in initial inaccuracies in the selective assembly model. To address this issue, an improved Jacobian-Torsor model is proposed that incorporates measured data from part assembly features into the deviation analysis model. Initially, the actual contact state of the assembly is determined by measuring the contact surface of the plane fit and the shaft-hole fit. Next, the Jacobian matrix, representing the transmission path of assembly deviation, is constructed by analyzing the assembly connection diagram. Subsequently, by integrating the actual contact state characterized by small displacement torsor (SDT) into the unified Jacobian-Torsor model, the advantage of high credibility tolerance propagation is provided. Finally, the feasibility of the proposed improved Jacobian-Torsor model is verified using the double-joint manipulator.
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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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