Complex Point Cloud Registration and Optimized Data Processing for High-Speed Railway Turnout

WANG Peijun; LÜ Dongxu; CHEN Peng

doi:10.3969/j.issn.0258-2724.2018.04.019

Volume 31 Issue 4

Jul. 2018

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Journal of Southwest Jiaotong University > 2018 > 53(4): 806-812, 849.

WANG Peijun, LÜ Dongxu, CHEN Peng. Complex Point Cloud Registration and Optimized Data Processing for High-Speed Railway Turnout[J]. Journal of Southwest Jiaotong University, 2018, 53(4): 806-812, 849. doi: 10.3969/j.issn.0258-2724.2018.04.019

Citation:

WANG Peijun, LÜ Dongxu, CHEN Peng. Complex Point Cloud Registration and Optimized Data Processing for High-Speed Railway Turnout[J]. Journal of Southwest Jiaotong University, 2018, 53(4): 806-812, 849. doi: 10.3969/j.issn.0258-2724.2018.04.019

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Complex Point Cloud Registration and Optimized Data Processing for High-Speed Railway Turnout

doi: 10.3969/j.issn.0258-2724.2018.04.019

Received Date: 11 May 2017
Publish Date: 01 Aug 2018

Abstract

Abstract

To enhance the inspection efficiency of high-speed switch rail wear, a complex registration based on a distance encoder is proposed, considering the inspection standards and the geometric characteristics of high-speed switch rail. The distance information was combined with the point cloud registration to improve automatic inspection. Additionally, the OpenCL (open computing language) heterogeneous acceleration model was introduced to achieve parallel data processing with higher speed during computation of the point feature histograms (PFH). In the on-site inspection of high-speed switch rail wear, the system function was verified on the structured light inspection platform, and the total inspection performance was increased by up to 70% by the optimized point cloud registration and data processing methods.
- wear,
- 3D point cloud,
- registration,
- inspection,
- OpenCL

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References(18)

References

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