Development of an Algorithm to Detect Screw Threads in Planar Point Clouds

Kosarevsky, Sergey; Latypov, Viktor

doi:10.2478/v10048-010-0024-4

Cited by 10 publications

(9 citation statements)

References 13 publications

(20 reference statements)

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“…1 There are two measurement methods for detecting thread in mechanical manufacturing technology, single-parameter measurement and comprehensive measurement. 2 Using contact screw surface method with specialized gauge, a single parameter is obtained, and this method is a single-parameter measurement method. It often causes the wear of parts.…”

Section: Introductionmentioning

confidence: 99%

Measurement method of screw thread geometric error based on machine vision

Jing

2018

Measurement and Control

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In order to solve manual operation and low detection efficiency in the measurement of thread geometric error, machine vision and optical enlargement are adopted to measure the high-precision geometric error of thread. For screw thread edge image characteristics, a new method using 67.5° and 112.5° improved Sobel templates to obtain the edge of image was put forward, and we calibrated the system using self-calibration method. The geometric error measurement system of screw thread was designed. The geometric error of screw thread, such as pitch, angle and diameter of screw, were calculated by extracting the coordinates of image edge. The system can be concluded that the method of machine vision, whose linear precision is less than 10 μm, can be used to detect the comprehensive parameters of screw thread. The designed measurement system was intuitive, efficient and easy to operate. It can be used in modern manufacturing and has values in generalized application.

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Section: Introductionmentioning

confidence: 99%

Measurement method of screw thread geometric error based on machine vision

Jing

2018

Measurement and Control

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“…In the proceedings [6] a method is presented to perform an elementwise inspection of internal threads using laser sensor and CCD camera. Kosarevsky and Latypov [7] used Hough transformation to extract features from planar sections obtained via profile measuring machines. The mathematics behind these image recognition techniques can be found in [8].…”

Section: Related Workmentioning

confidence: 99%

“…Performing image recognition in each plane a numeric evaluation of thread parameters can be obrained. The planar evaluation algorithm was presented in [7]. Using the obtained results one can assess the quality of the measured thread.…”

Section: Analysis On 3d Density Fieldmentioning

confidence: 99%

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Detection of Screw Threads in Computed Tomography 3D Density Fields

Kosarevsky¹,

Latypov²

2013

Measurement Science Review

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Measurements and inspection in production must be rapid, robust and automated. In this paper a new method is proposed to automatically detect screw threads in 3D density fields obtained from computed tomography measurement devices. The described method can be used to automate many operations during screw thread inspection process and drastically reduce operator's influence on the measurement process resulting in lower measurement times and increased repeatability.

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“…Kosarevsky [3] utilized the general Hough transformation to deal with the thread profile data and obtained the intersections of each adjacent segment pair, which can identify the circles tangent with the profile segments. Then, the pitch diameter can be calculated based on the Berndt formula [4].…”

Section: Introductionmentioning

confidence: 99%

A New Compensation Method for Measurement of Thread Pitch Diameter by Profile Scanning

Chen

Zhao

Lü

2014

Measurement Science Review

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For measurement of existing thread parameters using profile scanning, system error increases as pitch diameter, difference between the calibrating thread and measuring thread increases with the single gauge calibration method. There are several alignment deviations affecting the measurement of pitch diameter. To reduce the system error, a compensation method using two standard thread gauges to calculate the alignment deviations is proposed here. Finally, the theoretical and experimental comparisons between the single gauge calibration method and the proposed method are presented. The results demonstrate that the two gauges calibration method can effectively reduce the system error.

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Development of an Algorithm to Detect Screw Threads in Planar Point Clouds

Cited by 10 publications

References 13 publications

Measurement method of screw thread geometric error based on machine vision

Measurement method of screw thread geometric error based on machine vision

Detection of Screw Threads in Computed Tomography 3D Density Fields

A New Compensation Method for Measurement of Thread Pitch Diameter by Profile Scanning

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