Vision measurement system for geometric parameters of tubing internal thread based on double-mirrored structured light Article Swipe
Xiao Li
,
Jingyu Zhou
,
Haijun Xin
,
Wei Li
,
Xiaokang Yin
,
Xin’an Yuan
,
Huaiyuan Chen
,
Xingpei Chen
,
Xin Ma
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1364/oe.479067
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1364/oe.479067
Geometric parameter measurement of tubing internal thread is critical for oil pipeline safety. In response to the shortcomings of existing methods for measuring internal thread geometric parameters, such as low efficiency, poor accuracy, and poor accessibility, this paper proposes a vision system for measuring internal thread geometric parameters based on double-mirrored structured light. Compared to previous methods, our system can completely reproduce the internal thread tooth profiles and allows multi-parameter measurement in one setup. To establish the correlation between the structural and imaging parameters of the vision system, three-dimensional (3D) optical path models (OPMs) for the vision system considering the mirror effect of the prism is proposed, which extends the scope of the optical path analysis and provides a theoretical foundation for designing the structural parameters of the vision system. Moreover, modeling and three-step calibration methods for the vision system are proposed to realize high-accuracy restoration from the two-dimensional (2D) virtual image to the actual 3D tooth profiles. Finally, a vision measurement system is developed, and experiments are carried out to verify the accuracy and measure the three geometric parameters (i.e., taper, pitch, and tooth height) of typical internal threads. Based on the validation results using the reference system, the vision measurement accuracy and efficiency are 6.7 and 120 times that of the traditional system, which verifies the measurement effectiveness and accuracy of the vision system proposed in this paper.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1364/oe.479067
- OA Status
- gold
- Cited By
- 8
- References
- 17
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4310422332Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1364/oe.479067Digital Object Identifier
- Title
-
Vision measurement system for geometric parameters of tubing internal thread based on double-mirrored structured lightWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-30Full publication date if available
- Authors
-
Xiao Li, Jingyu Zhou, Haijun Xin, Wei Li, Xiaokang Yin, Xin’an Yuan, Huaiyuan Chen, Xingpei Chen, Xin MaList of authors in order
- Landing page
-
https://doi.org/10.1364/oe.479067Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1364/oe.479067Direct OA link when available
- Concepts
-
Thread (computing), Computer science, Machine vision, Computer vision, System of measurement, Structured light, Optical path, Artificial intelligence, Optics, Physics, Operating system, AstronomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 4, 2023: 1Per-year citation counts (last 5 years)
- References (count)
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17Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.of | 3, 18, 84, 102, 111, 126, 186, 211, 222 |
| abstract_inverted_index.on | 49, 191 |
| abstract_inverted_index.to | 15, 54, 142, 152, 170 |
| abstract_inverted_index.120 | 208 |
| abstract_inverted_index.6.7 | 206 |
| abstract_inverted_index.and | 33, 67, 81, 116, 132, 165, 174, 183, 203, 207, 220 |
| abstract_inverted_index.are | 140, 167, 205 |
| abstract_inverted_index.can | 59 |
| abstract_inverted_index.for | 9, 21, 42, 94, 121, 136 |
| abstract_inverted_index.low | 29 |
| abstract_inverted_index.oil | 10 |
| abstract_inverted_index.one | 72 |
| abstract_inverted_index.our | 57 |
| abstract_inverted_index.out | 169 |
| abstract_inverted_index.the | 16, 62, 76, 79, 85, 95, 99, 103, 109, 112, 123, 127, 137, 147, 153, 172, 176, 192, 196, 199, 212, 217, 223 |
| abstract_inverted_index.(2D) | 149 |
| abstract_inverted_index.(3D) | 89 |
| abstract_inverted_index.from | 146 |
| abstract_inverted_index.path | 91, 114 |
| abstract_inverted_index.poor | 31, 34 |
| abstract_inverted_index.such | 27 |
| abstract_inverted_index.that | 210 |
| abstract_inverted_index.this | 36, 228 |
| abstract_inverted_index.Based | 190 |
| abstract_inverted_index.based | 48 |
| abstract_inverted_index.image | 151 |
| abstract_inverted_index.paper | 37 |
| abstract_inverted_index.prism | 104 |
| abstract_inverted_index.scope | 110 |
| abstract_inverted_index.three | 177 |
| abstract_inverted_index.times | 209 |
| abstract_inverted_index.tooth | 65, 156, 184 |
| abstract_inverted_index.using | 195 |
| abstract_inverted_index.which | 107, 215 |
| abstract_inverted_index.(OPMs) | 93 |
| abstract_inverted_index.(i.e., | 180 |
| abstract_inverted_index.actual | 154 |
| abstract_inverted_index.allows | 68 |
| abstract_inverted_index.effect | 101 |
| abstract_inverted_index.light. | 52 |
| abstract_inverted_index.mirror | 100 |
| abstract_inverted_index.models | 92 |
| abstract_inverted_index.paper. | 229 |
| abstract_inverted_index.pitch, | 182 |
| abstract_inverted_index.setup. | 73 |
| abstract_inverted_index.system | 41, 58, 97, 139, 162, 225 |
| abstract_inverted_index.taper, | 181 |
| abstract_inverted_index.thread | 6, 24, 45, 64 |
| abstract_inverted_index.tubing | 4 |
| abstract_inverted_index.verify | 171 |
| abstract_inverted_index.vision | 40, 86, 96, 128, 138, 160, 200, 224 |
| abstract_inverted_index.between | 78 |
| abstract_inverted_index.carried | 168 |
| abstract_inverted_index.extends | 108 |
| abstract_inverted_index.height) | 185 |
| abstract_inverted_index.imaging | 82 |
| abstract_inverted_index.measure | 175 |
| abstract_inverted_index.methods | 20, 135 |
| abstract_inverted_index.optical | 90, 113 |
| abstract_inverted_index.realize | 143 |
| abstract_inverted_index.results | 194 |
| abstract_inverted_index.safety. | 12 |
| abstract_inverted_index.system, | 87, 198, 214 |
| abstract_inverted_index.system. | 129 |
| abstract_inverted_index.typical | 187 |
| abstract_inverted_index.virtual | 150 |
| abstract_inverted_index.Compared | 53 |
| abstract_inverted_index.Finally, | 158 |
| abstract_inverted_index.accuracy | 173, 202, 221 |
| abstract_inverted_index.analysis | 115 |
| abstract_inverted_index.critical | 8 |
| abstract_inverted_index.existing | 19 |
| abstract_inverted_index.internal | 5, 23, 44, 63, 188 |
| abstract_inverted_index.methods, | 56 |
| abstract_inverted_index.modeling | 131 |
| abstract_inverted_index.pipeline | 11 |
| abstract_inverted_index.previous | 55 |
| abstract_inverted_index.profiles | 66 |
| abstract_inverted_index.proposed | 141, 226 |
| abstract_inverted_index.proposes | 38 |
| abstract_inverted_index.provides | 117 |
| abstract_inverted_index.response | 14 |
| abstract_inverted_index.threads. | 189 |
| abstract_inverted_index.verifies | 216 |
| abstract_inverted_index.Geometric | 0 |
| abstract_inverted_index.Moreover, | 130 |
| abstract_inverted_index.accuracy, | 32 |
| abstract_inverted_index.designing | 122 |
| abstract_inverted_index.establish | 75 |
| abstract_inverted_index.geometric | 25, 46, 178 |
| abstract_inverted_index.measuring | 22, 43 |
| abstract_inverted_index.parameter | 1 |
| abstract_inverted_index.profiles. | 157 |
| abstract_inverted_index.proposed, | 106 |
| abstract_inverted_index.reference | 197 |
| abstract_inverted_index.reproduce | 61 |
| abstract_inverted_index.completely | 60 |
| abstract_inverted_index.developed, | 164 |
| abstract_inverted_index.efficiency | 204 |
| abstract_inverted_index.foundation | 120 |
| abstract_inverted_index.parameters | 47, 83, 125, 179 |
| abstract_inverted_index.structural | 80, 124 |
| abstract_inverted_index.structured | 51 |
| abstract_inverted_index.three-step | 133 |
| abstract_inverted_index.validation | 193 |
| abstract_inverted_index.calibration | 134 |
| abstract_inverted_index.considering | 98 |
| abstract_inverted_index.correlation | 77 |
| abstract_inverted_index.efficiency, | 30 |
| abstract_inverted_index.experiments | 166 |
| abstract_inverted_index.measurement | 2, 70, 161, 201, 218 |
| abstract_inverted_index.parameters, | 26 |
| abstract_inverted_index.restoration | 145 |
| abstract_inverted_index.theoretical | 119 |
| abstract_inverted_index.traditional | 213 |
| abstract_inverted_index.shortcomings | 17 |
| abstract_inverted_index.effectiveness | 219 |
| abstract_inverted_index.high-accuracy | 144 |
| abstract_inverted_index.accessibility, | 35 |
| abstract_inverted_index.double-mirrored | 50 |
| abstract_inverted_index.multi-parameter | 69 |
| abstract_inverted_index.two-dimensional | 148 |
| abstract_inverted_index.three-dimensional | 88 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 9 |
| citation_normalized_percentile.value | 0.75376374 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |