A best-fitting algorithm for optimal location of large-scale blanks with free-form surfaces

Shen, Bin; Huang, Gege; Wang, X.C.

doi:10.1016/s0924-0136(03)00241-3

Cited by 16 publications

(5 citation statements)

References 1 publication

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“…The registration effect between the measured data and the theoretical model is better. Otherwise, it may fall into the local trap, 17 occurring a positioning error.…”

Section: Blade Partition Registrationmentioning

confidence: 99%

Research on blade statistics measurement registration planning technology

Zhang

Liu

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part B:

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Blade has the characteristics of high machining quality of complex curved surface. If there is no benchmark before machining, it is impossible to judge whether the blades before machining are qualified. Therefore, it is necessary to analyze the blade measurement data. Due to the large measurement point error and disordered distribution, it is necessary to optimize the blade registration. Therefore, blade model registration and positioning is particularly important in blade shape detection and analysis. First, preregistration is carried out based on the six point optimization selection of the blade. After preregistration, the selection method of registration control point set based on theoretical model and statistical error is proposed, planning the registration datum point set on the blade model. The registration control point set is obtained through the registration operation between the measurement data and the registration reference point set. Finally, based on the stability and reliability of important sampling sensitivity and statistical error, obtain the probability density function of error normal distribution statistics samples and important samples. The selection of statistical control points and the rationality of the objective function were verified. The stability/reliability of the statistical alignment point selection is proved to be feasible. The statistical registration deviation is [0.015,0.026] mm, and the ICP registration deviation is [0.031,0.035] mm. The average deviation of statistics registration is about 0.013 mm smaller than the average deviation of ICP registration. The deviation of statistical sampling points is about 0.0214 mm, and that of traditional sampling points is about 0.0275 mm. The deviation of statistical sampling points is about 0.0061 mm smaller than that of traditional sampling points. It meets the requirements of rapid, high efficiency and high precision measurement for aeroengine blades.

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“…The registration effect between the measured data and the theoretical model is better. Otherwise, it may fall into the local trap, 17 occurring a positioning error.…”

Section: Blade Partition Registrationmentioning

confidence: 99%

Research on blade statistics measurement registration planning technology

Zhang

Liu

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

show abstract

“…Sun et al [9] effectively solved free-form surface localization by using the Lagrange multipliers method and the oriented Euclidean distance. Shen et al [10] proposed a hierarchical algorithm for localization of large blanks with freeformed surfaces. In rough fitting, the distance between the gravity center of the blank and the measured points at the surface corners is minimized, and in fine fitting, the oriented distances from the measured points to the design surface are assigned with different weights and then are summed up.…”

Section: Literature Reviewmentioning

confidence: 99%

Part localization theory and its application on near-net-shape machining

Chang

Wan

Chen

et al. 2018

Int J Adv Manuf Technol

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As an emerging technique, near-net-shape machining implies that billets of a part are near to its net shape (or its design), and thus, little machining of the billets is required to produce qualified pieces. This technique has been employed in production of critical parts, repair of important but worn out parts, and machining of three-dimensional (3-D) printed parts. To cut a near-net-shape billet, its part localization should be conducted by transforming (or localizing) its part design model geometrically such that the transformed model is inside the billet and within the part tolerances. This transformed model is called machining model. After that, the machining model is used to generate tool paths and the billet is cut with the tool along the paths. Unfortunately, the current problem of this technique is that the conventional part localization methods cannot ensure that the transformed model is within the tolerance and tool paths generated with this model cannot be used to cut the billet for a qualified piece. To address this problem, an innovative and practical approach is proposed to transform part features individually, making sure that the transformed model is inside the billet model and satisfies the part tolerance. In this work, three practical examples are rendered to verify this approach. This approach lays a theoretical foundation of part localization and is an effective solution to near-net-shape machining in industry.

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“…Xiong [4] introduced a CAD model based computer aided setup system based on certain workpiece localization algorithms. Shen [5] proposed an algorithm for the optimal localization of large-scale blanks with free-form surfaces by means of rotation, translational motion of a freeform surface and a projection method, the pre-location and adjustment and the final spatial posture control are realized to assure that the blanks coincide with their theoretical counterparts. While locating the workpiece, the basic issue is to match the measured points with the CAD model and the model-matching algorithm is the key to adaptive location of the workpiece.…”

Section: Introductionmentioning

confidence: 99%