Vol. 40

Front:[PDF file] Back:[PDF file]
Latest Volume
All Volumes
All Issues

Estimation of the Ageing of Metallic Layers in Power Semiconductor Modules Using the Eddy Current Method and Artificial Neural Networks

By Tien Anh Nguyen, Pierre-Yves Joubert, and Stephane Lefebvre
Progress In Electromagnetics Research M, Vol. 40, 129-141, 2014


In high power operations, the ageing of power semiconductor modules has been often observed by several failures due to high temperature cycling. The main failures may be metallization reconstruction, solder delaminations, bond wire lift-offs or bond wire heel crackings, conchoidal breaking of ceramics. The paper focuses on the non-contact monitoring of the ageing of the aluminum metallization top layer and of the solder bottom layer of a power die, using the eddy current method. The ageing is assumed to induce a decrease of these layers conductivity. The evaluation of both layers conductivity changes are estimated using artificial neural networks starting from eddy current data provided by finite element computations carried out in the case of several aged die configurations. The error of estimation is less than a few percent in the considered cases and it demonstrates the relevance of the eddy current method to monitor the ageing state of power modules. The proposed approach provides relevant results which will be validated on experimental data in future works.


Tien Anh Nguyen, Pierre-Yves Joubert, and Stephane Lefebvre, "Estimation of the Ageing of Metallic Layers in Power Semiconductor Modules Using the Eddy Current Method and Artificial Neural Networks," Progress In Electromagnetics Research M, Vol. 40, 129-141, 2014.


    1. Lutz, J., T. Hermann, M. Feller, R. Bayerer, T. Licht, and R. Amro, "Power cycling induced failure mechanisms in the viewpoint of rough temperature environment," Proceedings of the 5th International Conference on Integrated Power Electronic Systems, 55-58, Nuremberg, Mar. 2008.

    2. Ciappa, M., "Selected failure mechanisms of modern power modules," Microelectronics Reliability, Vol. 42, No. 4-5, 653-667, 2002.

    3. Martineau, D., T. Mazeaud, M. Legros, P. Dupuy, C. Levade, and G. Vanderschaeve, "Characterization of ageing failures on power MOSFET devices by electron and ion microscopies," Microelectronics Reliability, Vol. 49, No. 9-11, 1330-1333, 2009.

    4. Detzel, T., M. Glavanovics, and K. Weber, "Analysis of wire bond and metallisation degradation mechanisms in DMOS power transistors stressed under thermal overload conditions," Microelectronics Reliability, Vol. 44, No. 9-11, 1485-1490, 2004.

    5. Smet, V., F. Forest, J. Huselestein, A. Rashed, and F. Richardeau, "Evaluation of VCE monitoring as a real time method to estimate ageing of bon wire --- IGBT modules Stressed by power cycling," IEEE Transactions on Industrial Electronics, Vol. 60, No. 7, 2760-2770, 2013.

    6. Pietranico, S., S. Lefebvre, S. Pommier, and M. Berkani Bouaroudj, "A study of the effect of degradation of the aluminum metallization layer in the case of power semiconductor devices," Microelectronics Reliability, Vol. 51, No. 9-11, 1824-1829, 2011.

    7. Udpa, S. and P. Moore, Nondestructive Testing Handbook, 3rd Edition, Vol. 5, Electromagnetic Testing, The American Society for Nondestructive Testing, 2004.

    8. Rava, C., P.-Y. Joubert, Y. Le bihan, C. Marchand, M. Woytasik, and E. Dufour-Gergam, "Non-destructive evaluation of small defects using an eddy current microcoil sensor array," Sensor Letter, Vol. 7, No. 3, 400-405, 2009.

    9. Nguyen, T. A., P.-Y. Joubert, S. Lefebvre, G. Chaplier, and L. Rousseau, "Study for the noncontact characterization of metallization ageing of power electronic semiconductor device using the eddy current technique," Microelectronics Reliability, Vol. 51, No. 6, 1127-1135, 2011.

    10. Nguyen, T. A., P.-Y. Joubert, S. Lefebvre, and S. Bontemps, "Monitoring of ageing chips of semiconductor power modules using eddy current sensor," Electronics Letters, Vol. 49, No. 6, 415-417, 2013.

    11. Rojas, R., Neural Networks: A Systematic Introduction, Springer, Berlin, 1996.

    12. Vernon, S.-N., "The universal impedance diagram of the ferrite pot core eddy current transducer," IEEE Transactions on Magnetics, Vol. 25, No. 3, 2639-2645, 1989.

    13. Le Bihan, Y., "Study on the transformer equivalent circuit of eddy current nondestructive evaluation," NDT&E International, Vol. 36, No. 5, 297-302, 2003.

    14. Bore, T., P.-Y, Joubert, and D. Placko, "A differential DPSM based modeling applied to eddy current imaging problems," Progress In Electromagnetics Research, Vol. 148, 209-221, 2014.

    15. Cacciola, M., F. C. Morabito, D. Polimeni, and M. Versaci, "Fuzzy characterization of flawed metallic plates with eddy current tests," Progress In Electromagnetics Research, Vol. 72, 241-252, 2007.

    16. Joubert, P.-Y., E. Vourc’h, and V. Thomas, "Experimental validation of an eddy current probe dedicated to the multi-frequency imaging of bore holes," Sensors and Actuators A, Vol. 185, 132-138, 2012.

    17. Hasanzadeh, R. P. R., A. R. Moghaddamjoo, S. H. H. Sade Ghi, A. H. Rezaie, and M. Ahmadi, "Optimal signal-adaptive maximum likelihood filter for enhancement of defects in eddy current C-scan images," NDT&E International, Vol. 41, No. 5, 371-377, 2008.

    18. Yusa, N., N. Huang, and K. Miya, "Numerical evaluation of the ill-posedness of eddy current problems to size real cracks," NDT&E International, Vol. 40, No. 3, 185-191, 2007.

    19. Agatonovic, M., Z. Stankovic, I. Milovanovic, N. Doncov, L. Sit, T. Zwick, and B. Milovanovic, "Efficient neural network approach for 2D DOA estimation based on antenna array measurements," Progress In Electromagnetics Research, Vol. 137, 741-758, 2013.

    20. Wefky, A., F. Espinosa, L. D. Santiago, A. Gardel, P. Revenga, and M. Martinez, "Modeling radiated electromagnetic emissions of electric motorcycles in terms of driving profile using MLP neural networks," Progress In Electromagnetics Research, Vol. 135, 231-244, 2013.

    21. Hornik, K., M. Stinchcombe, and H. White, "Multilayer feed-forward networks are universal approximators," Neural Networks, Vol. 2, No. 5, 359-366, 1989.

    22. Peng, X., "Eddy current crack extension direction evaluation based on neural network," Proceedings of IEEE Sensors, 1-4, 2012.

    23. Vourc’h, E., P.-Y. Joubert, G. Le Gac, and P. Larzabal, "Nondestructive evaluation of loose assemblies using multi-frequency eddy currents and artificial neural networks," Measurement Science and Technology, Vol. 24, No. 12, 7 Pages, 2013.

    24. Demuth, H. and M. Beale, Neural Network Toolbox for Use with MATLAB, Neural Network Toolbox for Use with MATLAB Sep. 2000.

    25. Levenberg, K., "A method for the solution of certain non-linear problems in least squares," Quarterly Journal of Applied Mathematics, Vol. II, No. 2, 164-168, 1944.

    26. Hagan, M. T. and M. Menhaj, "Training feed-forward networks with the Levenberg-Marquardt algorithm," IEEE Transactions on Neural Networks, Vol. 5, No. 6, 989-993, 1994.

    27. Smith, M., Neural Network for Statistical Modeling, Van Nostrand-Reinhold, New York, 1993.