journal article·2024-11-16

Defect detection of metallic samples by electromagnetic tomography using closed-loop fuzzy PID-controlled iterative Landweber method

Pu Huang, Xiaofei Huang, Zhiying Li, Yuedong Xie

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Abstract

Electromagnetic tomography (EMT) uses the mutual inductance of the coil to visualise the conductivity distribution of interesting regions. Since the conductivity of defects and metal samples are different, the metal samples with defects can be treated as binary-valued material distributions. This paper investigates the closed-loop fuzzy proportional, integral and derivative (PID)-controlled iterative Landweber method. The whole method includes fuzzy PID controller, the Landweber reconstruction method, and the Dirichlet-to-Neumann map. Specifically, the differential signal between the mutual inductance of the coil and the feedback signal is used as the input of the fuzzy PID controller. The fuzzy controller can automatically adjust three parameters (Kp, Ki and Kd) of PID controller. Subsequently, the output of the PID controller can serve as the input of the Landweber algorithm to reconstruct the distribution of conductivity. Furthermore, the Dirichlet-to-Neumann map is used to calculate the mutual inductance, acting as the feedback signal based on the reconstruction conductivity distribution. Finally, both the numerical simulation and experiments are applied to verify the proposed method. The results indicate that the proposed method can reconstruct the image with a clear edge, and the average correlation coefficient can reach 0.792.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Electrical and Bioimpedance Tomography · Non-Destructive Testing Techniques · Geophysical and Geoelectrical Methods

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Key Laboratory of Precision Opto-mechatronics Technology of Education Ministry, School of Instrumentation and Opto-Electronic Engineering, Beihang University, Beijing, China

Funding

Fundamental Research Funds for the Central Universities · National Natural Science Foundation of China · Academic Excellence Foundation of BUAA for Ph.D. Students

References (34)

Show source-provided references
1. 10.1080/10589759.2023.228707110.1080/10589759.2023.2287071 ↗
2. 10.1080/10589759.2014.91420910.1080/10589759.2014.914209 ↗
3. 10.1007/s10921-020-00718-w10.1007/s10921-020-00718-w ↗
4. 10.1080/10589759.2021.190901210.1080/10589759.2021.1909012 ↗
5. 10.1007/s10921-018-0499-810.1007/s10921-018-0499-8 ↗
6. 10.1080/1058975080261334710.1080/10589750802613347 ↗
7. 10.1007/s10921-022-00858-110.1007/s10921-022-00858-1 ↗
8. 10.1109/TMAG.2008.200314210.1109/TMAG.2008.2003142 ↗
9. 10.1109/JSEN.2019.292762910.1109/JSEN.2019.2927629 ↗
10. 10.1109/TIM.2007.89559810.1109/TIM.2007.895598 ↗
11. 10.1063/5.001869910.1063/5.0018699 ↗
12. 10.1088/0957-0233/24/7/07400410.1088/0957-0233/24/7/074004 ↗
13. 10.1109/TIM.2021.309838810.1109/TIM.2021.3098388 ↗
14. 10.1088/0957-0233/26/7/07530310.1088/0957-0233/26/7/075303 ↗
15. 10.1088/1361-6420/aa909a10.1088/1361-6420/aa909a ↗
16. 10.1007/s11220-021-00374-y10.1007/s11220-021-00374-y ↗
17. 10.1016/j.flowmeasinst.2012.04.01110.1016/j.flowmeasinst.2012.04.011 ↗
18. 10.1007/s11220-019-0250-210.1007/s11220-019-0250-2 ↗
19. 10.1016/j.flowmeasinst.2012.10.00710.1016/j.flowmeasinst.2012.10.007 ↗
20. 10.1109/TIM.2023.324200110.1109/TIM.2023.3242001 ↗
21. 10.1109/TMAG.2015.243028310.1109/TMAG.2015.2430283 ↗
22. 10.1109/JSEN.2020.296627410.1109/JSEN.2020.2966274 ↗
23. 10.1109/JSEN.2018.280948510.1109/JSEN.2018.2809485 ↗
24. 10.1063/1.512011810.1063/1.5120118 ↗
25. 10.1088/0957-0233/25/5/05540410.1088/0957-0233/25/5/055404 ↗
26. 10.1016/j.ijmultiphaseflow.2015.02.01310.1016/j.ijmultiphaseflow.2015.02.013 ↗
27. 10.1109/TIM.2009.202470410.1109/TIM.2009.2024704 ↗
28. 10.1109/TMAG.2012.223230110.1109/TMAG.2012.2232301 ↗
29. 10.1109/TIM.2023.325030010.1109/TIM.2023.3250300 ↗
30. 10.1109/TIM.2020.304475610.1109/TIM.2020.3044756 ↗
31. 10.1109/TIM.2023.325030010.1109/TIM.2023.3250300 ↗
32. 10.1016/j.ndteint.2011.11.01310.1016/j.ndteint.2011.11.013 ↗
33. 10.1109/JSEN.2020.296573110.1109/JSEN.2020.2965731 ↗
34. Huang P Huang X Peng G et al. Online defect detection on metallic plates using electromagnetic tomography. accepted in Insight 2023.10.1784/insi.2024.66.2.109 ↗