The Detection of Surface Quality On-Line Based on Machine Vision in the Production of Bearings

Chang Wang; Jing Jing Gao

doi:10.4028/www.scientific.net/AMM.319.523

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Spectrophotometric Determination of Trace Hg²⁺ with hsDNA-Modified Nanosilver Probe
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A Method of RAM-Based Frequency Acquisition for Base Station Positioning Receiver
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The Detection of Surface Quality On-Line Based on Machine Vision in the Production of Bearings
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Weakened Support Detection Based on Road Slab Vibration Response
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Method for Estimating the Domino Effect in Quantitative Assessment
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Study on Detection of Structures Crack Based on Digital Image Technology
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 319The Detection of Surface Quality On-Line Based on...

The Detection of Surface Quality On-Line Based on Machine Vision in the Production of Bearings

Abstract:

The combining of digital image processing technique and pattern recognition technique, it can be wild used in the products of industry classification and recognition Line bearing assembly defects in this article for the detection and identification of needs, Automatic detection system based on machine vision, contrast measurement plane array camera on a different surfaceImage acquisition, binarization processing for subsequent pretreatment image pattern recognition, feature extraction and eigenvalue comparison, product line surface defect detection and identification.

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Periodical:

Applied Mechanics and Materials (Volume 319)

Pages:

523-527

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.319.523

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Online since:

May 2013

Authors:

Chang Wang, Jing Jing Gao

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Digital Image

, Calibration, Machine Vision, Pattern Recognition

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References

[1] Yiquan WU, Zhaoda JU . Image improcess the Threshold Selected Method 30years(1962-1992）improvement[J]. Data acquistion and processsing, 1993, 8(3):80～81. In Chinese

Google Scholar

[2] Marr D. , Visual calculation theory, Science Press, 1988.

Google Scholar

[3] Yuejin ZHANG , Iimage Engineer：Iimage understanding & computer image, Bei Jing：Tsinghua University Press, 2000. In Chinese

Google Scholar

[4] Xifa ZHANG . Cannon cauterization interior ballistics [M]. Bei Jing: National Defence Industry Press, 2001. In Chinese

Google Scholar

[5] Lawson G, Fowler S , Halsey H, etal. The inbore chronograph laserradar for interior ballistics measurements[J]. SPIE vo l. 1936 applied laserradar technology, 1993: 374-385.

Google Scholar

[6] Garner J. M. Marrs T. Off the shelf technology for gun barrel straightness measurement [C]. 10th U. S. Army Gun Dynamics symposium. 2001:462-489.

Google Scholar