Support vector regression for determining the minimum zone sphericity

Balakrishna, P.; Raman, S. Ganesh Sundara; Trafali̇s, Theodore B.; Santosa, Budi

doi:10.1007/s00170-006-0774-1

Cited by 12 publications

(5 citation statements)

References 24 publications

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“…However, the drawback is that several runs should be made to ensure a global optimum. In recent years intelligent evaluation has being focused on in many countries [6][7][8][9]. To some extent, the method has solved drawbacks of traditional evaluation.…”

Section: Introductionmentioning

confidence: 99%

A New Flatness Evaluation-Rotation Method Based on GA

Jiang

Liu

2010

AMR

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Flatness is one fundamental element of geometric forms, and the flatness evaluation is particularly important for ensuring the quality of industrial products. This paper presents a new flatness evaluation in the view of the minimum zone evaluation - rotation method based on genetic algorithm. This method determines the minimum zone through rotating measurement points in three dimensions coordinate. The points are firstly rotated about coordinate axes. Then they are projected in one axis, and the smallest projection length is the flatness value. The rotation angles are optimized by genetic algorithm to improve search efficiency. An exponential fitness function and the rotation angles range is designed on the basis of flatness characteristics. An adaptive mode of crossover and mutation probability is used to avoid local optimum. The results show this method can search the minimum zone and converge rapidly.

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Section: Introductionmentioning

confidence: 99%

A New Flatness Evaluation-Rotation Method Based on GA

Jiang

Liu

2010

AMR

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“…According to the Hilbert-Schmidt principle [29], the inner product operation in the original linear case can be replaced by φ i (x) • φ j (x). The decision function becomes as shown in equation ( 8):…”

Section: Twin Support Vector Machinesmentioning

confidence: 99%

A new method of roundness error evaluation based on twin support vector machines

Zheng

Cao

et al. 2021

Meas. Sci. Technol.

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The geometric error determines the product quality and function to a certain extent. Among them, the roundness error is one of the important indicators for evaluating the geometric error of shaft parts. With the increase of industrial requirements, there are higher requirements for the accuracy and efficiency of roundness error evaluation. However, most of the traditional roundness error evaluation models used in the industry can no longer meet the needs of current industrial processing in terms of efficiency and accuracy. This paper proposes a new roundness error evaluation method based on twin support vector machines (TWSVMs). First, according to the roundness error evaluation and the TWSVMs theory, the roundness error evaluation model with the TWSVMs is obtained. Then, experimental research and analysis are carried out, and the accuracy and efficiency of the traditional roundness evaluation method and the new method are compared. The research results show that the new roundness evaluation method based on the TWSVMs proposed in this paper can efficiently and accurately evaluate the roundness error, and can be applied to the online evaluation of the roundness error in industrial processing to improve the processing efficiency.

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“…The number of sampling points is a key factor in determining the accuracy of flatness evaluation, excessive sampling points are the guarantee of detection accuracy [14]. For a large number of detection data, experts have proposed a variety of optimization algorithms for flatness evaluation, such as a support vector regression method [15], vectorial method [16] and a hybrid method based on reduced constraint region and convex-hull edge [17].…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Reconstructing Flatness Error Contour of Long Surface Based on a Laser Displacement Sensor

Zhong-wu

Zhao

2019

IEEE Access

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In order to solve the problem that the flatness error contour curve of the guideway mounting surface on machine tools can not be intuitive description, a novel method is proposed in this paper. The principle is to divide the measured surface with a certain length into several short surfaces with overlapping region, and the segmented surfaces are measured respectively, then the flatness error contours of the segmented surfaces can be obtained, finally, the segmented flatness error contours are spliced together to reconstruct the flatness error contour of the entire surface. On this basis, the detection instrument is designed, the detection principle is given, the benchmark plate is customized to identify the starting position and ending position of measurement, the reference surface and the measured surface are measured respectively in combination with the detection instrument and the benchmark plate. Then, an algorithm is developed to convert the distance difference between the reference surface and the measured surface into the flatness error contours of segmented surfaces. Next, using the geometric relationship between overlapping region of segmented flatness error contours, an algorithm is studied which can splice these segmented flatness error contours and reconstruct the flatness error contour of the entire surface. Meanwhile, mathematical models of the algorithms are established, and the measurement experiment is carried out. The results demonstrate that this method can reconstruct the flatness error contour of long surface accurately. INDEX TERMS Flatness detection, machine tool, detection instrument, flatness error contour reconstruction, contour splicing.

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Support vector regression for determining the minimum zone sphericity

Cited by 12 publications

References 24 publications

A New Flatness Evaluation-Rotation Method Based on GA

A New Flatness Evaluation-Rotation Method Based on GA

A new method of roundness error evaluation based on twin support vector machines

A Novel Method for Reconstructing Flatness Error Contour of Long Surface Based on a Laser Displacement Sensor

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