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An Intelligent Self-Calibrating 4-DOF Parallel Robot for Precise Geometric Data Collection in Digital Manufacturing

机译:用于数字制造中精确几何数据收集的智能自校准四自由度并联机器人

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Accurate capture of digital data from a manufactured part is an essential source of information about the quality of the produced part and the health of the corresponding manufacturing processes. The commonly known precise instruments for digitizing work-pieces on Coordinate Metrology Machine (CMM) are contact probes. Although, contact techniques confront difficulties, they lead to higher precisions comparing to non-contact methods. Ball-tip-radius error is one of the significant faults of contact methods. Conventional error compensating approaches of ball-tip-radius error often demand complicated and time consuming post-processes. Furthermore, considering the limitations of typical serial structure in commercial CMMs, adaptive accurate path planning is a very complex task. This paper presents an intelligent combination of a novel 4-DOF parallel mechanism implementing, a linear cost-effective contact probe, and an adaptive path planning method to automatically correct the probing direction. The implemented parallel structure has three translational DOF in X, Y and Z directions and one rotational DOF around X axis. A precise turn-table provides rotation of work-piece around the Z axis. The developed algorithm utilizes a data clustering approach and intelligently generates an automated adaptive probe placement and motion path. Validation process using simulation and actual measurement of free-form surfaces demonstrate highly reliable feasibility for eliminating the ball-tip-radius error resulting in high precision 3D data capturing process.
机译:从制造零件中准确捕获数字数据是有关制造零件的质量和相应制造过程的运行状况的重要信息来源。用于在坐标测量机(CMM)上数字化工件的众所周知的精密仪器是接触探针。尽管接触技术面临困难,但与非接触方法相比,它们可导致更高的精度。球形尖端半径误差是接触方法的重大缺陷之一。球头半径误差的传统误差补偿方法通常需要复杂且耗时的后处理。此外,考虑到商用CMM中典型序列结构的局限性,自适应精确路径规划是一项非常复杂的任务。本文提出了一种新颖的4-DOF并联机构实现方案,一种具有成本效益的线性接触式探针以及一种可自动校正探测方向的自适应路径规划方法的智能组合。所实现的平行结构在X,Y和Z方向上具有三个平移自由度,并且绕X轴具有一个旋转自由度。精密的转台可使工件绕Z轴旋转。所开发的算法利用数据聚类方法,并智能地生成自动自适应探头放置和运动路径。使用仿真和对自由曲面的实际测量进行的验证过程证明了消除球形尖端半径误差(导致高精度3D数据捕获过程)的高度可靠的可行性。

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