A parameterized automatic programming solution for composite grinding based on digital image processing

Shen, Nanyan; Zhao, Chen; Li, Jing; Xu, Yingjie; Yang, Wu; Deng, Zongqian

doi:10.1007/s00170-020-05984-6

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…The corner detection method mentioned in [ 13 ] is used to separate the straight-line boundary and bottom arc of the thread teeth. The DP algorithm in [ 30 ] is used to approximate the thread profile, but not single thread teeth are positioned in the thread image, which makes automatic measurement of sucker rod end threads impossible. In this paper, according to the prior knowledge of the measured thread profile angle, a directional edge detection operator (DEDO) was specially designed to realize the edge detection of a specific angle in the screw thread image, so as to realize the high-precision positioning of the thread teeth.…”

Section: Algorithm and Principlesmentioning

confidence: 99%

Automatic Measurement of External Thread at the End of Sucker Rod Based on Machine Vision

Wang

2022

Sensors

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Aiming at the low efficiency of manual measurement of threads and the lack of practicability in machine vision measurement before, online size measurement of threads at the end of sucker rods based on machine vision was studied. A robotic arm is used to carry an optical device to achieve high-quality image acquisition of threads. Based on the prior knowledge of the thread profile angle, the directional edge detection operator is customized to achieve the accurate detection of the left and right edges of the thread. Noise filtering, sorting, and left and right edge-matching algorithms based on connected domains are developed to eliminate the interference effects of electrostatic dust and oil pollution in online measurement, and the dimension of thread profile angles, pitches, major diameters, and minor diameters can be precisely calculated. The experimental results show that the screw thread parameter measurement time is about 0.13 s; the maximum and minimum average errors of the thread angles are 0.011° and 0.632°, respectively; and the total average deviation is less than 0.08°. For the screw thread pitch, major diameter, minor diameter, and pitch diameter parameter measurement, the deviation of the measurement results between the proposed method and the universal tool microscope (UTM) method is less than 10 μm. It fully proves the effectiveness and accuracy of the method in this paper and, at the same time, shows that the method has good real-time performance and high application significance, which lays a good foundation for the subsequent online thread measurement.

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Section: Algorithm and Principlesmentioning

confidence: 99%

Automatic Measurement of External Thread at the End of Sucker Rod Based on Machine Vision

Wang

2022

Sensors

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Research on procedure optimisation for composite grinding based on Digital Twin technology

Shen

Yang

et al. 2022

International Journal of Production Research

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Research on Digital Image Recognition Algorithm Based on Modular Intelligent Image Recognition

Shao

Zhu

2021

2021 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA)

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A parameterized automatic programming solution for composite grinding based on digital image processing

Cited by 3 publications

References 27 publications

Automatic Measurement of External Thread at the End of Sucker Rod Based on Machine Vision

Automatic Measurement of External Thread at the End of Sucker Rod Based on Machine Vision

Research on procedure optimisation for composite grinding based on Digital Twin technology

Research on Digital Image Recognition Algorithm Based on Modular Intelligent Image Recognition

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