IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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Lightweight Algorithm for Digital Twin based on Diameter Measurement using Singular-Value-Decomposition

특이값 분해를 이용한 치수측정 기반 디지털 트윈 알고리즘 경량화

  • Received : 2023.01.31
  • Accepted : 2023.04.25
  • Published : 2023.06.30
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Abstract

In the machine vision inspection equipment, diameter measurement is important process in inspection of cylindrical object. However, machine vision inspection equipment requires complex algorithm processing such as camera distortion correction and perspective distortion correction, and the increase in processing time and cost required for precise diameter measurement. In this paper, we proposed the algorithm for diameter measurement of cylindrical object using the laser displacement sensor. In order to fit circle for given four input outer points, grid search algorithms using root-mean-square error and mean-absolute error are applied and compared. To solve the limitations of the grid search algorithm, we finally apply the singular-value-decomposition based circle fitting algorithm. In order to compare the performance of the algorithms, we generated the pseudo data of the outer points of the cylindrical object and applied each algorithm. As a result of the experiment, the grid search using root-mean-square error confirmed stable measurement results, but it was confirmed that real-time processing was difficult as the execution time was 10.8059 second. The execution time of mean-absolute error algorithm was greatly improved as 0.3639 second, but there was no weight according to the distance, so the result of algorithm is abnormal. On the other hand, the singular-value-decomposition method was not affected by the grid and could not only obtain precise detection results, but also confirmed a very good execution time of 0.6 millisecond.

Keywords

Acknowledgement

This study was supported by the BK21 FOUR project funded by the Ministry of Education, Korea (4199990113966), and the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1A6A1A03025109, 30%, 2020R1I1A1A01072343, 10%, NRF-2022R1I1A3069260, 10%) and by MSIT (Ministry of Science and ICT) (2020M3H2A1078119) and MSIT, Korea, under the Innovative Human Resource Development for Local Intellectualization support program (IITP-2022-RS-2022-00156389, 10%) supervised by the IITP (Institute for Information & communications Technology Planning & Evaluation). This work was partly supported by an Institute of Information and communications Technology Planning and Evaluation (IITP) grant funded by the Korean government (MSIT) (No. 2021-0-00944, Metamorphic approach of unstructured validation/verification for analyzing binary code, 30%) and (No. 2022-0-01170, PIM Semiconductor Design Research Center, 10%). The EDA tool was supported by the IC Design Education Center (IDEC), Korea.

References

  1. Y. Jung, K. H. Park, "O-ring Size Measurement Based on a Small Machine Vision Inspection Equipment," Journal of the Korea Industrial Information Systems Research, Vol. 19, No. 4, pp. 41-52, 2014 (in Korean).  https://doi.org/10.9723/JKSIIS.2014.19.4.041
  2. S. Hong, D. Park, "Lane Detection Based on Inverse Perspective Transformation and Machine Learning in Lightweight Embedded System," IEMEK J. Embed. Sys. Appl., Vol. 17, No. 1, pp. 41-49, 2022 (in Korean). 
  3. S. Lee, D. Park, P. Choi, D. Park, "Efficient Power Consumption Technique of LiDAR Sensor for Controlling Detection Accuracy Based on Vehicle Speed," IEMEK J. Embed. Sys. Appl., Vol. 15, No. 5, pp. 215-225, 2020 (in Korean). 
  4. T. Chong, D. Park, "Efficiency Low-Power Signal Processing for Multi-Channel LiDAR Sensor-based Vehicle Detection Platform," Journal of the Korea Institute of Information and Communication Engineering, Vol. 25, No. 7, pp. 977-985, 2021 (in Korean).  https://doi.org/10.6109/JKIICE.2021.25.7.977
  5. J. Garcia-Martin, J. Gomez-Gil and E. Vazquez-Sanchez, "Non-Destructive Techniques Based on Eddy Current Testing," Sensors, Vol. 11, pp. 2525-2565, 2011.  https://doi.org/10.3390/s110302525
  6. H. Yang, C. Zhu, L. Lv, Y. Du, "Light Energy Distribution Based on Ideal Detected Surface for Laser Displacement Sensor," 2022 IEEE 2nd International Conference on Data Science and Computer Application (ICDSCA), pp. 267-270, Dalian, China, 2022. 
  7. K. M. Cheon, B. C. Shin, G. H. Shin, J. I. Go, J. H. Lee, J. W. Hur, "Classification of the Rusting State of Pipe Using a Laser Displacement Sensor," Journal of the Korean Society of Manufacturing Process Engineers, Vol. 21, No. 5, pp. 46-52, 2022 (in Korean).  https://doi.org/10.14775/ksmpe.2022.21.05.046
  8. A. Mai, L. Tran, L. Tran, N. Trinh, "Vgg Deep Neural Network Compression via svd and cur Decomposition Techniques," in 2020 7th NAFOSTED Conference on Information and Computer Science (NICS), pp. 118-123, 2020. 
  9. M. K. Alam, A. A. Aziz, S. A. Latif, A. A. Aziz, "Error-control Truncated svd Technique for In-network Data Compression in Wireless Sensor Networks," IEEE Access, Vol. 9, pp. 13829-13844, 2021.  https://doi.org/10.1109/ACCESS.2021.3051978
  10. Y. Shi, G. Zhao, M. Wang, Y. Xu, "An Adaptive Grid Search Algorithm for Fitting Spherical Target of Terrestrial LiDAR," Measurement, Vol. 198, pp. 111430, 2022. 
  11. T. Chai, R. R. Draxler, "Root Mean Square Error (RMSE) or Mean Absolute Error (MAE)?-Arguments Against Avoiding RMSE in the Literature," Geosci. Model Dev, Vol. 7, No. 3, pp. 1247-1250, 2014.  https://doi.org/10.5194/gmd-7-1247-2014
  12. W. Wang, Y. Lu, "Analysis of the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) in Assessing Rounding Model," in IOP Conference Series: Materials Science and Engineering, Vol. 324, No. 1, pp. 012049, 2018.