[1]
W. Staszewski, C. Boller, G. R. Tomlinson, Health Monitoring of Aerospace Structures: Smart Sensor Technologies and Signal Processing, John Wiley & Sons, 2004.
DOI: 10.1002/0470092866
Google Scholar
[2]
F. I. Ferreira, P. R. de Aguiar, R. B. da Silva, M. J. Jackson, R. R. de Souza Ruzzi, F. G. Baptista, E. C. Bianchi, Electromechanical impedance (EMI) measurements to infer features from the grinding process, International Journal of Advanced Manufacturing Technology 106(5–6) (2019) 2035–2048.
DOI: 10.1007/s00170-019-04733-8
Google Scholar
[3]
V. Giurgiutiu, Structural Health Monitoring with Piezoelectric Wafer Active Sensors, Elsevier, 2007.
Google Scholar
[4]
M. Rosiek, A. Martowicz, T. Uhl, T. Stępiński, T. Łukomski, Electromechanical impedance method for damage detection in mechanical structures, Proceedings of the 11th IMEKO TC 10, 2010, 18–20.
Google Scholar
[5]
D. Wang, H. Song, H. Zhu, Numerical and experimental studies on damage detection of a concrete beam based on PZT admittances and correlation coefficient, Construction and Building Materials 49 (2013) 564–574.
DOI: 10.1016/j.conbuildmat.2013.08.074
Google Scholar
[6]
P. Liu, W. Wang, Y. Chen, X. Feng, L. Miao, Concrete damage diagnosis using electromechanical impedance technique, Construction and Building Materials 136 (2017) 450–455.
DOI: 10.1016/j.conbuildmat.2016.12.173
Google Scholar
[7]
S. K. Singh, R. Shanker, A. Ranjan, Health monitoring of steel structures using surface mountable and detachable PZT sensor, Journal of Intelligent Material Systems and Structures 35(4) (2024) 380–392.
DOI: 10.1177/1045389x231185613
Google Scholar
[8]
S. R. Hamzeloo, M. Shamshirsaz, S. M. Rezaei, Damage detection on hollow cylinders by electro-mechanical impedance method: Experiments and finite element modeling, Comptes Rendus Mécanique 340(9) (2012) 668–677.
DOI: 10.1016/j.crme.2012.07.001
Google Scholar
[9]
R. Z. Da Silveira, L. M. Campeiro, F. G. Baptista, Analysis of sensor installation methods in impedance-based SHM applications, Procedia Engineering 168 (2016) 1751–1754.
DOI: 10.1016/j.proeng.2016.11.506
Google Scholar
[10]
S. Na, H.-K. Lee, Neural network approach for damaged area location prediction of a composite plate using electromechanical impedance technique, Composites Science and Technology 88 (2013) 62–68.
DOI: 10.1016/j.compscitech.2013.08.019
Google Scholar
[11]
X. Hu, H. Zhu, D. Wang, A study of concrete slab damage detection based on the electromechanical impedance method, Sensors 14(10) (2014) 19897–19909.
DOI: 10.3390/s141019897
Google Scholar
[12]
D. Ai, H. Zhu, H. Luo, J. Yang, An effective electromechanical impedance technique for steel structural health monitoring, Construction and Building Materials 73 (2014) 97–104.
DOI: 10.1016/j.conbuildmat.2014.09.029
Google Scholar
[13]
D. Ai, H. Zhu, H. Luo, C. Wang, Mechanical impedance based embedded piezoelectric transducer for reinforced concrete structural impact damage detection: A comparative study, Construction and Building Materials 165 (2018) 472–483.
DOI: 10.1016/j.conbuildmat.2018.01.039
Google Scholar
[14]
D. Ai, F. Mo, F. Yang, H. Zhu, Electromechanical impedance-based concrete structural damage detection using principal component analysis incorporated with neural network, Journal of Intelligent Material Systems and Structures 33(17) (2022) 2241–2256.
DOI: 10.1177/1045389x221077440
Google Scholar
[15]
Anjum, A., Hrairi, M., Aabid, A., Yatim, N., Ali, M, Damage detection in concrete structures with impedance data and machine learning. Bulletin of the Polish Academy of Sciences Technical Sciences, 2024, e149178-e149178.
DOI: 10.24425/bpasts.2024.149178
Google Scholar
[16]
Zhang, C., Yan, Q., Liao, X., Qiu, Y., Zhang, Y., Wang, P. Deep hybrid neural network-aided electromechanical impedance method for automated damage detection of lining concrete under freeze-thaw cycling. Structural Health Monitoring, 24(3), (2025) 1725-1751.
DOI: 10.1177/14759217241259955
Google Scholar
[17]
Sakhria, B., Hamaidi, B., Djemana, M., & Benhassine, N. Harnessing neural networks for precise damage localization in photovoltaic solar via impedance-based structural health monitoring. Electrical Engineering, 107(3) (2025) 3229-3245.
DOI: 10.1007/s00202-024-02700-5
Google Scholar
[18]
Gomasa, R., Talakokula, V., Jyosyula, S. K. R., Bansal, T. Integrating electro-mechanical impedance data with machine learning for damage detection and classification of blended concrete systems. Construction and Building Materials, 445, (2024)137725.
DOI: 10.1016/j.conbuildmat.2024.137725
Google Scholar
[19]
Yan, Q., Yang, Y., Zhang, C., Xiong, Z., Zhong, H., Xu, Y., Yang, W. Intelligent monitoring of impact damage within concrete through deep learning-empowered electromechanical impedance technique. Measurement, (2025) 117642.
DOI: 10.1016/j.measurement.2025.117642
Google Scholar
[20]
Meher, U., Sunny, M. R. Localization and quantification of delamination/disbond inside a composite lap-joint using novel cross and drive point mechanical impedance based feature. Mechanical Systems and Signal Processing, 220, (2024) 111661.
DOI: 10.1016/j.ymssp.2024.111661
Google Scholar
[21]
M. Marchi, F. G. Baptista, P. R. de Aguiar, E. C. Bianchi, Grinding process monitoring based on electromechanical impedance measurements, Measurement Science and Technology 26(4) (2015).
DOI: 10.1088/0957-0233/26/4/045601
Google Scholar
[22]
P. O. Júnior, P. R. de Aguiar, R. Ruzzi, S. Conte, M. Viera, F. Alexandre, F. G. Baptista, Tool condition monitoring in grinding operation using piezoelectric impedance and wavelet transform, Proceedings 42(1) (2019) 10.
DOI: 10.3390/ecsa-6-06589
Google Scholar
[23]
H. B. Hübner, R. B. da Silva, M. A. V. Duarte, M. B. da Silva, F. I. Ferreira, P. R. de Aguiar, F. G. Baptista, A comparative study of two indirect methods to monitor surface integrity of ground components, Structural Health Monitoring 19(6) (2020) 1856–1870.
DOI: 10.1177/1475921720903442
Google Scholar
[24]
M. Tekkalmaz, Ü. Er, F. H. Çakır, F. Bozkurt, A new approach to monitoring the operational success of shot peening with electromechanical impedance technique, International Journal of Advanced Manufacturing Technology 117(11) (2021) 3503–3513.
DOI: 10.1007/s00170-021-07933-3
Google Scholar
[25]
M. A. Sofuoğlu, G. Haydarlar, M. C. Kuşhan, S. Orak, M. Tekkalmaz, Investigation of electromechanical impedance and residual stress relation for samples machined by hot ultrasonic-assisted turning, Proceedings of the Institution of Mechanical Engineers Part C: Journal of Mechanical Engineering Science 236(8) (2022) 4180–4193.
DOI: 10.1177/09544062211050473
Google Scholar
[26]
M. Tekkalmaz, Ü. Er, F. H. Çakır, F. Bozkurt, A new approach to monitor wear tracks propagation on-site with electromechanical impedance technique, Journal of Intelligent Material Systems and Structures 33(2) (2022) 342–351.
DOI: 10.1177/1045389x211014951
Google Scholar
[27]
F. H. Çakır, Ü. Er, M. Tekkalmaz, Monitoring the wear of turning tools with the electromechanical impedance technique, Journal of Intelligent Material Systems and Structures 34(11) (2023) 1341–1352.
DOI: 10.1177/1045389x221135027
Google Scholar
[28]
E. Rivière, V. Stalon, O. Van der Abeele, E. Filippi, Chatter detection techniques using microphone, Seventh National Congress on Theoretical and Applied Mechanics, 2006, 1–8.
Google Scholar
[29]
R. Wang, Q. Song, Z. Liu, H. Ma, M. K. Gupta, Z. Liu, A novel unsupervised machine learning-based method for chatter detection in the milling of thin-walled parts, Sensors 21(17) (2021) 5779.
DOI: 10.3390/s21175779
Google Scholar
[30]
M. Tran, M. Liu, M. Elsisi, Effective multi-sensor data fusion for chatter detection in milling process, ISA Transactions 125 (2022) 514–527.
DOI: 10.1016/j.isatra.2021.07.005
Google Scholar
[31]
M. Kuntoğlu, H. Sağlam, Investigation of signal behaviors for sensor fusion with tool condition monitoring system in turning, Measurement 173 (2021) 108582.
DOI: 10.1016/j.measurement.2020.108582
Google Scholar
[32]
L. Skarbek, T. Wandowski, S. Opoka, P. H. Malinowski, W. M. Ostachowicz, Electromechanical impedance technique and scanning vibrometry for structure characterization, 6th European Workshop on Structural Health Monitoring (EWSHM 2012), Dresden, Germany, 2012.
DOI: 10.4028/www.scientific.net/kem.569-570.687
Google Scholar
[33]
D. M. Peairs, G. Park, D. J. Inman, Improving accessibility of the impedance-based structural health monitoring method, Journal of Intelligent Material Systems and Structures 15(2) (2004) 129–139.
DOI: 10.1177/1045389x04039914
Google Scholar
[34]
Dormer Pramet, Solid Milling Catalog 2024. Available at: https://5wyuco84ao39w9tsgkkmnmx.blob.core.windows.net/cms/KATI-%C3%96%C4%9E%C3%9UTME-2024-TR.pdf.
Google Scholar