Several approaches can be used to find defects in metal surfaces. Eddy current testing is a simple and efficient method for non-destructive testing of metals, identifying alloys, measuring coating thickness, and detecting corrosion. Impedance spectroscopy enables depth profiling and high-speed measurements in real-time manufacturing. For example, in the wood processing industry, early detection of cracks in high-speed band saws is crucial. Electromagnetic testing, particularly eddy-current-based methods, is widely used. This paper reviews existing solutions and investigates cracked saw blade specimens using planar coils in the 100 kHz–10 MHz range. Results show that higher frequencies improve crack detection. Future research should focus on high-speed detection and machine vision-based solutions.
1. Martens, O., Land, R., Metshein, M., Abdullayev, A., Vennikas, H. and Le Moullec, Y. Detection of cracks in a sawblade by eddy current measurements. In 2024 19th Biennial Baltic Electronics Conference (BEC), Tallinn, Estonia, 2–4 October 2024. IEEE, 2024, 1–6.
https://doi.org/10.1109/BEC61458.2024.10737981
2. Mordia, R. and Kumar Verma, A. Visual techniques for defects detection in steel products: a comparative study. Eng. Fail. Anal., 2022, 134, 106047.
https://doi.org/10.1016/j.engfailanal.2022.106047
3. García-Martín, J., Gómez-Gil, J. and Vázquez-Sánchez, E. Non-destructive techniques based on eddy current testing. Sensors (Basel), 2011, 11(3), 2525–2565.
https://doi.org/10.3390/s110302525
4. Machado, M. A. Eddy currents probe design for NDT applications: a review. Sensors, 2024, 24(17), 5819.
https://doi.org/10.3390/s24175819
5. Wikipedia. Eddy-current testing.
https://en.wikipedia.org/wiki/Eddy-current_testing (accessed 2024-12-03).
6. Center for Nondestructive Evaluation. Depth of penetration and current density.
https://www.nde-ed.org/Physics/Electricity/depthcurrentdensity.xhtml (accessed 2010-07-01).
7. Desjardins, D., Krause, T. W. and Clapham, L. Transient eddy current method for the characterization of magnetic permeability and conductivity. NDT & E Int., 2016, 80, 65–70.
https://doi.org/10.1016/j.ndteint.2016.02.010
8. Nonaka, Y. A double coil method for simultaneously measuring the resistivity, permeability, and thickness of a moving metal sheet. IEEE Trans. Instrum. Meas., 1996, 45(2), 478–482.
https://doi.org/10.1109/19.492771
9. Dodd, C. V. and Deeds, W. E. Analytical solutions to eddy-current probe-coil problems. J. Appl. Phys., 1968, 39(6), 2829–2838.
https://doi.org/10.1063/1.1656680
10. Dodd, C. V. and Deeds, W. E. Absolute eddy-current measurement of electrical conductivity. Technical report. Oak Ridge National Lab, Tennessee, USA, 1981.
https://doi.org/10.1007/978-1-4684-4262-5_48
11. Burke, S. K. and Ibrahim, M. E. Mutual impedance of air-cored coils above a conducting plate. J. Phys. D: Appl. Phys., 2004, 37(13), 1857–1868.
https://doi.org/10.1088/0022-3727/37/13/021
12. Zhang, J., Yuan, M., Xu, Z., Kim, H.-J. and Song, S.-J. Analytical approaches to eddy current nondestructive evaluation for stratified conductive structures. J. Mech. Sci. Technol., 2015, 29(10), 4159–4165.
http://dx.doi.org/10.1007/s12206-015-0910-7
13. Theodoulidis, T. P., Tsiboukis, T. D. and Kriezis, E. E. Analytical solutions in eddy current testing of layered metals with continuous conductivity profiles. IEEE Trans. Magn., 1995, 31(3), 2254–2260.
https://doi.org/10.1109/20.376236
14. Pokatilov, A., Parker, M., Kolyshkin, A., Märtens, O. and Kübarsepp, T. Inhomogeneity correction in calibration of electrical conductivity standards. Measurement, 2013, 46(4), 1535–1540.
https://doi.org/10.1016/j.measurement.2012.12.007
15. Reidla, M., Martens, O., Land, R. and Rist, M. Piccolo-stick and PCB-coil based simple coin validator. In 2012 5th European DSP Education and Research Conference (EDERC), Amsterdam, Netherlands, 13–14 September 2012. IEEE, 2012, 81–84.
https://doi.org/10.1109/EDERC.2012.6532230
16. Howells, G. Coin discriminators. US Patent 7584833, 2009-09-08.
17. Märtens, O., Min, M., Land, R., Annus, P., Saar, T. and Reidla, M. Method and device for frequency response measurement. US Patent 88540302014, 2014-10-07.
18. Land, R., Annus, P., Min, M., Märtens, O. and Ojarand, J. Method and device for broadband analysis of systems and substances. US Patent 10698023, 2020-06-30.
19. Gordon, R. et al. Eddy current validation of Euro-coins. In Lecture Notes on Impedance Spectroscopy: Measurement, Modeling and Applications 3(Kanoun, O., ed.). CRC Press, London, 2012, 47–63.
20. Märtens, O., Land, R., Gordon, R., Min, M., Rist, M. and Pokatilov, A. Precise eddy current measurements: improving accuracy of determining of the electrical conductivity of metal plates. In Lecture Notes on Impedance Spectroscopy: Measurement, Modeling and Applications 4 (Kanoun, O., ed.). Taylor & Francis, London, 2014, 109–115.
https://doi.org/10.1201/b16063-19
21. Märtens, O., Land, R., Min, M., Rist, M., Annus, P. and Pokatilov, A. Fast precise eddy current measurement of metals. In 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Houston, USA, 14–17 May 2018. IEEE, 2018, 1–5.
https://doi.org/10.1109/I2MTC.2018.8409781
22. Märtens, O., Land, R., Min, M., Rist, M., Ferenets, M. and Käsper, A. Eddy current corrosion measurement of steel. In Impedance Spectroscopy. Advanced Applications: Battery Research, Bioimpedance, System Design (Kanoun, O., ed.). De Gruyter, Berlin, Boston, 2018, 125–134.
https://doi.org/10.1515/9783110 558920-012
23. He, Y., Tian, G., Zhang, H., Alamin, M., Simm, A. and Jackson, P. Steel corrosion characterization using pulsed eddy current systems. IEEE Sens. J., 2012, 12(6), 2113–2120.
https://doi.org/10.1109/JSEN.2012.2184280
24. Laansoo, A., Kübarsepp, J., Surženkov, A., Land, R., Märtens, O. and Viljus, M. Induction brazing of cermets to steel and eddy current testing of joint quality. Weld. World, 2020, 64, 563–571.
https://doi.org/10.1007/s40194-020-00854-x
25. Kong, Y., Bennett, C. J. and Hyde, C. J. A review of non-destructive testing techniques for the in-situ investigation of fretting fatigue cracks. Mater. Des., 2020, 196, 109093.
https://doi.org/10.1016/j.matdes.2020.109093
26. Torbali, M. E., Zolotas, A. and Avdelidis, N. P. A state-of-the-art review of non-destructive testing image fusion and critical insights on the inspection of aerospace composites towards sustainable maintenance repair operations. Applied Sciences, 13(4) 2023.
https://doi.org/10.3390/app13042732
27. Silva, M. I., Malitckii, E., Santos, T. G. and Vilaca, P. Review of conventional and advanced non-destructive testing techniques for detection and characterization of small-scale defects. Prog. Mater. Sci., 2023, 138, 101155.
https://doi.org/10.1016/j.pmat sci.2023.101155
28. Hutt, T. and Cawley, P. Feasibility of digital image correlation for detection of cracks at fastener holes. NDT Int., 2009, 42(2), 141–149.
https://doi.org/10.1016/j.ndteint.2008.10.008
29. Marot, J., Bourennane, S. and Spinnler, K. Metal surface control system based on successive contour estimation. In 2010 IEEE International Conference on Image Processing, Hong Kong, China, 26–29 September 2010. IEEE, 2010, 2293–2296.
https://doi.org/10.1109/ICIP.2010.5654115
30. Senthikumar, M., Palanisamy, V. and Jaya, J. Metal surface defect detection using iterative thresholding technique. In Second International Conference on Current Trends In Engineering and Technology (ICCTET), Coimbatore, India, 8 July 2014. IEEE, 2014, 561–564.
https://doi.org/10.1109/ICCTET.2014.6966360
31. Hao, C., He, Y., Li, Y., Niu, X. and Wang, Y. An image-based hairline crack identification method for metal parts. IEEE Trans. Instrum. Meas., 2023, 72, 200114.
https://doi.org/10.1109/TIM. 2023.3324689
32. Zhang, Z., Wang, W. and Tian, X. Semantic segmentation of metal surface defects and corresponding strategies. IEEE Trans. Instrum. Meas., 2023, 72, 5016813.
https://doi.org/10.1109/TIM.2023.3282301
33. Aslam, M., Khan, T. M., Naqvi, S. S., Holmes, G. and Naffa, R. On the application of automated machine vision for leather defect inspection and grading: a survey. IEEE Access, 2019, 7, 176065–176086.
https://doi.org/10.1109/ACCESS.2019.2957427
34. Tao, X., Gong, X., Zhang, X., Yan, S. and Adak, C. Deep learning for unsupervised anomaly localization in industrial images: a survey. IEEE Trans. Instrum. Meas., 2022, 71, 5018021.
https://doi.org/10.1109/TIM.2022.3196436
35. Kumar, A. Computer-vision-based fabric defect detection: a survey. IEEE Trans. Ind. Electron., 2008, 55(1), 348–363.
https://doi.org/10.1109/TIE.1930.896476
36. Luo, Q., Fang, X., Liu, L., Yang, C. and Sun, Y. Automated visual defect detection for flat steel surface: a survey. IEEE Trans. Instrum. Meas., 2020, 69(3), 626–644.
https://doi.org/10.1109/TIM.2019.2963555
37. Agnisarman, S., Lopes, S., Chalil Madathil, K., Piratla, K. and Gramopadhye, A. A survey of automation-enabled human-in-the-loop systems for infrastructure visual inspection. Autom. Constr., 2018, 97, 52–76.
https://doi.org/10.1016/j.autcon.2018.10.019
38. Ciampa, F., Mahmoodi, P., Pinto, F. and Meo, M. Recent advances in active infrared thermography for non-destructive testing of aerospace components. Sensors, 2018, 18(2), 609.
https://doi.org/10.3390/s18020609
39. He, Y., Li, M., Meng, Z., Chen, S., Huang, S., Hu, Y. et al. An overview of acoustic emission inspection and monitoring technology in the key components of renewable energy systems. Mech. Syst. Signal Process., 2021, 148, 107146.
https://doi.org/10.1016/j.ymssp.2020.107146
40. Santos, S. D. and Furui, S. Quaternion signal processing for nonlinear ultrasonics. In 2024 19th Biennial Baltic Electronics Conference (BEC), Tallinn, Estonia, 2–4 October 2024. IEEE, 2024, 1–6.
https://doi.org/10.1109/BEC61458.2024.10737979
41. Foerster Group. Non-Destructive Material Testing: The Most Important Methods for Crack Testing and Their Applications. CT-0011 Rissprüfung ebook EN 223006, 2020.
42. Foerster Group. Statograpgh CM+ / CM.
https://www.foerstergroup.com/en/products/statograph-cm-cm (accessed 2024-08-03).
43. USNR (Millwide). BMS – Bandsaw Monitoring System.
https://www.usnr.com/en/product/bandsawmonitoringsystem (accessed 2024-12-03).
44. Lu, H. Fatigue cracking of lumber bandsaw blades. PhD thesis. University of British Columbia, Canada, 1993.
http://dx.doi.org/10.14288/1.0081019
45. Tuck, D. L. Bandsaw diagnostics by neurocomputing-two are better than one! In Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, Dunedin, New Zealand, 20–23 November 1995. IEEE, 1995, 330–333.
https://doi.org/10.1109/ANNES.1995.499501
46. Zhu, N., Tanaka, C. and Ohtani, T. Automatic detection of a damaged cutting tool during machining II: method to detect gullet crack in a bandsaw during sawing. J. Wood Sci., 2001, 47, 490–492.
https://doi.org/10.1007/BF00767903
47. Zhuo, R., Deng, Z., Chen, B., Liu, T., Ge, J., Liu, G. et al. Research on online intelligent monitoring system of band saw blade wear status based on multi-feature fusion of acoustic emission signals. Int. J. Adv. Manuf. Technol., 2022, 121, 4533–4548.
https://doi.org/10.1007/s00170-022-09515-3
48. Auld, B. A. and Moulder, J. C. Review of advances in quantitative eddy current nondestructive evaluation. J. Nondestruct. Eval., 1999, 18, 3–36.
https://doi.org/10.1023/A:1021898520626
49. Li, P., Xie, S., Wang, K., Zhao, Y., Zhang, L., Chen, Z. et al. A novel frequency-band-selecting pulsed eddy current testing method for the detection of a certain depth range of defects. NDT Int., 2019, 107, 102154.
https://doi.org/10.1016/j.ndteint.2019.102154
50. Xie, S., Chen, Z., Takagi, T. and Uchimoto, T. Efficient numerical solver for simulation of pulsed eddy-current testing signals. IEEE Trans. Magn., 2011, 47(11), 4582–4591.
https://doi.org/10.1109/TMAG.2011.2151872
51. Huang, P., Li, Z., Long, J., Xu, L. and Xie, Y. Measurement of lift-off distance and thickness of nonmagnetic metallic plate using pulsed eddy current testing. IEEE Trans. Instrum. Meas., 2023, 72, 6006810.
https://doi.org/10.1109/TIM.2023.3285918
52. Chen, Z., Miya, K. and Kurokawa, M. Rapid prediction of eddy current testing signals using A–φ method and database. NDT & E International, 1999, 32(1), 29–36.
https://doi.org/10.1016/S0963-8695(98)00025-5
53. Skarlatos, A., Theodoulidis, T. and Poulakis, N. A fast and robust semi-analytical approach for the calculation of coil transient eddy-current response above planar specimens. IEEE Trans. Magn., 2022, 58(9), 6301609.
https://doi.org/10.1109/TMAG.2022.3183019
54. Xia, Z., Huang, R., Chen, Z., Yu, K., Zhang, Z., Salas-Avila, J. R. et al. Eddy current measurement for planar structures. Sensors, 2022, 22(22), 8695.
https://doi.org/10.3390/s22228695
55. Silva, M. I., Malitckii, E., Santos, T. G. and Vilaça, P. Review of conventional and advanced non-destructive testing techniques for detection and characterization of small-scale defects. Prog. Mater. Sci., 2023, 138, 101155.
https://doi.org/10.1016/j.pmatsci.2023.101155
56. Fukutomi, H., Huang, H., Takagi, T. and Tani, J. Identification of crack depths from eddy current testing signal. IEEE Trans. Magn., 1998, 34(5), 2893–2896.
https://doi.org/10.1109/20.717674
57. Mirshekar-Syahkal, D. and Mostafavi, R. F. 1-D probe array for ACFM inspection of large metal plates. IEEE Trans. Instrum. Meas., 2002, 51(2), 374–382.
https://doi.org/10.1109/19.997840
58. Chen, G.-M., Li, W. and Wang, Z. Structural optimization of 2-D array probe for alternating current field measurement. NDT Int., 2007, 40(6), 455–461.
https://doi.org/10.1016/j.ndteint.2007.03.002
59. Karpenko, O., Efremov, A., Ye, C. and Udpa, L. Multi-frequency fusion algorithm for detection of defects under fasteners with EC-GMR probe data. NDT Int., 2020, 110, 102227.
https://doi.org/10.1016/j.ndteint.2020.102227
60. Martens, O. Precise synchronous detectors with improved dynamic reserve. IEEE Trans. Instrum. Meas., 2002, 49(5), 1046–1049.
https://doi.org/10.1109/19.872928
61. Texas Instruments. LDC Reference Coils User’s Guide. Literature No. SNOU136, 2015.
62. Theodoulidis, T. and Kotouzas, M. Eddy current testing simulation on a personal computer. In 15th World Conference on Nondestructive Testing, Roma, Italy, 15–21 October 2000. AIPnD, 2000.
63. Priidel, E., Pesti, K., Min, M., Ojarand, J. and Märtens, O. FPGA-based 16-bit 20 MHz device for the inductive measurement of electrical bio-impedance. In 2021 IEEE International Instrumentation and Measurement Technology Conference (I2MTC),, Glasgow, UK, 17–20 May 2021. IEEE, 2021, 1–6.
https://doi.org/10.1109/I2MTC50364.2021.9460073
64. Gavrijaseva, A., Märtens, O., Land, R. and Reidla, M. Coin recognition using line scan camera. In 2014 14th Biennial Baltic Electronic Conference (BEC),Tallinn, Estonia, 6–8 October 2014. IEEE, 2014, 161–164.
https://doi.org/10.1109/BEC.2014.7320581
65. Molder, A., Martens, O., Saar, T. and Land, R. Adaptively undersampled image processing for fast multiline laser detection. In 2013 IEEE 8th International Symposium on Intelligent Signal Processing, Funchal, Portugal, 16–18 September 2013. IEEE, 2013, 60–64.
https://doi.org/10.1109/WISP.2013.6657483