Precision measurement for small size parts based on support vector regression
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Precision measurement for small size parts based on support vector regression
Optics and Precision EngineeringVol. 15, Issue 4, Pages: 557-563(2007)
作者机构:
1. 吉林大学 机械科学与工程学院, 吉林 长春 130022
2. 杭州电子工业大学,浙江 杭州 310018
作者简介:
基金信息:
DOI:
CLC:TP274.5;TG806
Received:22 December 2006,
Revised:18 February 2007,
Published Online:30 April 2007,
Published:30 April 2007
稿件说明:
移动端阅览
HE Qiu-wei, WANG Long-shan, LIU Qing-min, et al. Precision measurement for small size parts based on support vector regression[J]. Optics and precision engineering, 2007, 15(4): 557-563.
DOI:
HE Qiu-wei, WANG Long-shan, LIU Qing-min, et al. Precision measurement for small size parts based on support vector regression[J]. Optics and precision engineering, 2007, 15(4): 557-563.DOI:
Precision measurement for small size parts based on support vector regression
In order to improve measurement precision and measurement speed of small size parts
a new kind of precision measurement method based on Support Vector Regression(SVR) for micro size parts was put forward. Taking the tooth shape chain board as the study object
its main parameters were measured. Using a transillumination in this system
the digital image of tooth shape chain board was collected by A102FCCD device
and was input into computer by IEEE1394 digital card. Then
the original gray level image was processed by reducing noise with median filtering
creating a binary image with threshold method
extracting contour and rotating the image. The image rotation can be realized using Hough transform to detect the longest line. After the image processing
the original gray level image with noise was changed into edge information with single-pixel width. Based on the theory parameter calculation of the tooth shape chain and SVR principle
the detected regions were determined according to the proportions of the length and width oftooth shape chain board. By pixel points on edges in the detected regions
the training set of corresponding line section was madeup for the support vector regression to obtain the regression function of every detected line section
which is the expression of the sub-pixel
and then the main parameters of the tooth shape chain board were measured. Finally
the measurement error was analyzed. The measurement results meet tolerance requirement of the part. The measurement precision can reach 2 μm. Theory analysis and experimental results show that the proposed method significantly reduces the effect of the discreteness of CCD and the system noise on the measurement precision
and is characterized by high speed and high precision. At the same time
this method is very robust to image in plane rotation
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