Short bio and area of expertise

I am a researcher at the Faculty of Mechanical Engineering and Robotics, Department of Robotics and Mechatronics, AGH University of Technology. My work focuses on the application of artificial intelligence methods to complex problems in mechanical and structural engineering.

My research integrates decision fusion, anomaly detection, classification and pattern recognition, image processing, multidimensional regression, evolutionary optimization, and deep learning. These methods are applied primarily in aircraft structural health monitoring, condition monitoring of machinery, and civil engineering diagnostics.

Recently, my work has expanded toward generative artificial intelligence for directed augmentation of SHM datasets — developing domain-specific generative models for guided waves and vibration-based diagnostics, conceptually analogous to “Stable Diffusion”-like approaches tailored to engineering data.

Papers 66

Citations 581

h-index 12

i10-index 16

Source: Google Scholar. Date of bibliometric data acquisition: 11.02.2026

Active research themes

Guided-wave imaging & SHM

Sparse sensing, vibrometric measurements, damage imaging, data-driven reconstruction, decision fusion

SHM guided waves imaging ANN Image processing

Generative AI for directed augmentation of SHM datasets

Augmentation and enhancement of SHM datasets with use of Genetarive AI methods

Generative AI Deep learning Stable diffusion Damage representations

Structural dynamics through lens of AI

Modal analysis and filtration optimization with neural networks and natural optimization methods

modal filtration Evolutionary computation ANN

Selected publications

[1] A. Jablonski, Z. Dworakowski, K. Dziedziech, and F. Chaari, “Vibration-based diagnostics of epicyclic gearboxes – From classical to soft-computing methods,” Measurement, vol. 147, p. 106811, 2019, doi: 10.1016/j.measurement.2019.07.039.
[2] Z. Dworakowski, K. Dziedziech, P. Zdziebko, and K. Mendrok, “Damage Detection in Plates with the Use of Laser-Measured Mode Shapes,” Shock Vib., vol. 2020, p. 8858126, 2020.
[3] A. Lis, Z. Dworakowski, and P. Czubak, “An anomaly detection method for rotating machinery monitoring based on the most representative data,” J. Vibroengineering, vol. 23, no. 4, pp. 861–876, 2021, doi: 10.21595/jve.2021.21622.
[4] M. Heesch, M. Dziendzikowski, K. Mendrok, and Z. Dworakowski, “Diagnostic-Quality Guided Wave Signals Synthesized Using Generative Adversarial Neural Networks,” Sensors, vol. 22, p. 3848, 2022, doi: 10.3390/s22103848.
[5] Z. Dworakowski, L. Ambrozinski, and T. Stepinski, “Multi-stage temperature compensation method for Lamb wave measurements,” J. Sound Vib., vol. 382, pp. 328–339, 2016, doi: 10.1016/j.jsv.2016.06.038.
[6] Z. Dworakowski, K. Dragan, and T. Stepinski, “Artificial neural network ensembles for fatigue damage detection in aircraft,” J. Intell. Mater. Syst. Struct., vol. 28, no. 7, pp. 851–861, 2016, doi: 10.1177/1045389X16657428.
[7] J. Górski, A. Klepka, K. Dziedziech, J. Mrówka, R. Radecki, and Z. Dworakowski, “Identification of the stick and slip motion between contact surfaces using artificial neural networks,” Nonlinear Dyn., 2020, doi: 10.1007/s11071-020-05515-8.
[8] K. Dziedziech, A. Jablonski, and Z. Dworakowski, “A novel method for speed recovery from vibration signal under highly non-stationary conditions,” Measurement, vol. 128, no. June, pp. 13–22, 2018, doi: 10.1016/j.measurement.2018.06.024.
[9] J. Spytek, A. Machynia, K. Dziedziech, Z. Dworakowski, and K. Holak, “Novelty detection approach for the monitoring of structural vibrations using vision-based mean frequency maps,” Mech. Syst. Signal Process., vol. 185, no. August 2022, 2023, doi: 10.1016/j.ymssp.2022.109823.
[10] Z. Dworakowski, K. Dziedziech, and A. Jabłoński, “A novelty detection approach to monitoring of epicyclic gearbox health,” Metrol. Meas. Syst., vol. 25, no. 3, pp. 459–473, 2018, doi: 10.24425/123896.Z.
[11] Z. Dworakowski, K. Kowalczyk, and M. Dziendzikowski, “Feature map field fusion of guided wave vibrometer data for increased fault localization capability,” Struct. Heal. Monit. An Int. J., 2025, doi: 10.1177/14759217251324910.
[12] Z. Dworakowski, P. Kohut, A. Gallina, K. Holak, and T. Uhl, “Vision-based algorithms for damage detection and localization in structural health monitoring,” Struct. Control Heal. Monit., vol. 23, pp. 35–50, 2016, doi: 10.1002/stc.1755.
[13] Z. Dworakowski, L. Ambrozinski, P. Packo, K. Dragan, and T. Stepinski, “Application of artificial neural networks for compounding multiple damage indices in Lamb-wave-based damage detection,” Struct. Control Heal. Monit., vol. 22, pp. 50–61, 2015, doi: 10.1002/stc.
[14] J. Gorski, A. Jablonski, M. Heesch, M. Dziendzikowski, and Z. Dworakowski, “Comparison of Novelty Detection Methods for Detection of Various Rotary Machinery Faults,” Sensors, vol. 21, no. 3536, pp. 1–20, 2021.
[15] J. Gorski, M. Heesch, M. Dziendzikowski, and Z. Dworakowski, “Fuzzy-Logic-Based Recommendation System for Processing in Condition Monitoring,” Sensors, vol. 22, p. 3695, 2022, doi: 10.3390/s22103695.
[16] M. Dziendzikowski, M. Heesch, J. Gorski, K. Dragan, and Z. Dworakowski, “Application of pzt ceramic sensors for composite structure monitoring using harmonic excitation signals and bayesian classification approach,” Materials (Basel)., vol. 14, no. 19, 2021, doi: 10.3390/ma14195468.
[17] K. Dziedziech, A. Jablonski, and Z. Dworakowski, “Epicyclic gearbox fault detection by Instantaneous Circular Pitch Cycle Map,” Mech. Syst. Signal Process., vol. 121, pp. 600–614, 2019, doi: 10.1016/j.ymssp.2018.11.053.
[18] Z. Dworakowski, P. Zdziebko, K. Dziedziech, and K. Holak, “Vision-Based Damage Detection for One-Fixed-End Structures Based on Aligned Marker Space and Decision Fusion,” Sensors, vol. 22, no. 24, 2022, doi: 10.3390/s22249820.

Projects - Principal Investigator

2017 - 2020, SONATA 2016/21/D/ST8/01678IDER/1/0001/L-11/19/NCBR/2020 "Inteligentne algorytmy sterowania adaptacyjnego w celu kompensacji drgań konstrukcji" - Projekt badawczy poświęcony opracowaniu nowych adaptacyjnych algorytmów aktywnego tłumienia drgań obiektów o nieznanej i nieidentyfikowalnej transmitancji zmiennej w czasie.
2018 - 2022, LIDER/3/0005/L-9/17/NCBR/2018: "SYPIN" "System automatycznego przetwarzania i interpretacji danych w monitorowaniu stanu struktur" - Projekt badawczy poświęcony samokonfigurujących się systemów wstępnego przetwarzania danych, interpretacji danych oraz podejmowania decyzji w warunkach monitorowania populacji struktur.

Projects - researcher

2022 - ..., LIDER13/0132/2022: "TAPSES", "Opracowanie technologii oraz prototypu systemu monitorowania elementów strukturalnych konstrukcji w oparciu o fuzję danych z sieci sensorów zintegrowanych"
2021 - 2021, LIDER/1/0001/L-11/19/NCBR/2020: "3DT", "Bezkontaktowe obrazowanie uszkodzeń w konstrukcjach kompozytowych z wykorzystaniem termografii laserowej"
2020 - 2023, POIR.04.01.04-00-0080/19: "BLASTER", "Nowa era FTF dla systemów oceny stanu technicznego maszyn wirnikowych - od urządzeń on-site do serwerów Industry 4.0"
2018 - 2022, LIDER/26/0103/L-9/17/NCBR/2018: "MAGWIZ", " System wizyjny do monitorowania stanu konstrukcji wykorzystujący algorytmy wzmacniania ruchu i deformacji"
2017 - 2019, POIR.01.02.00-00-0317/16:, "Opracowanie i wdrożenie nowych numerycznych i pomiarowych metod modelowania i symulacji maszyn i procesów w celu predykcji stanu technicznego dla podniesienia dyspozycyjności urządzeń krytycznych i poprawy efektywności procesu wytwarzania energii z wykorzystaniem zaawansowanej technologii Distributed Edge Computing oraz Chmury Hybrydowej"
2015 - 2018, PBS3/B6/21/2015: "EPICLA", "Opracowanie modelu eksperymentalnego systemu oceny stanu technicznego hybrydowych przekładni obiegowych dużej mocy dla energetyki wiatrowej i górnictwa, pracujących w silnie zmiennych warunkach eksploatacyjnych"
2015 - 2018, GEKON1/02/214108/19/2014: "GEKON", "Dynamiczne zarządzanie zdolnościami przesyłowymi sieci elektroenergetycznych przy wykorzystaniu innowacyjnych technik pomiarowych"
2015 - 2018, 60/030/0027/11/Z/J, "Opracowanie innowacyjnej metodyki i informatycznego systemu zarządzania dla kodyfikacji linii kolejowych"
2015 - 2018, LIDER/35/43/L-2/10/NCBiR/2011: "SYMOST", "Opracowanie systemu monitorowania stanu technicznego samolotu PZL_ORLIK TC II w oparciu o wieloprzetwornikową sieć czujników PZT"

Conference activities

Z. Dworakowski, T. Stepinski, K. Dragan, A. Jablonski, and T. Barszcz, “Ensemble ANN Classifier for Structural Health Monitoring,” in ICAISC 2016, Part I, LNAI, 2016, vol. 2, no. 9692, pp. 81–90.
Z. Dworakowski, K. Dragan, and T. Stepinski, “Lamb-wave-based monitoring of the aircraft during full-scale fatigue experiment - results and conclusions,” in 8th European Workshop on Structural Health Monitoring (EWSHM), 2016, no. July 2016, pp. 5–8.
Z. Dworakowski, L. Ambrozinski, and T. Stepinski, “Data fusion for compensation of temperature variations in Lamb-wave based SHM systems,” in SPIE Smart Structures NDE, 2015.
Z. Dworakowski, A. Jablonski, and P. Kijanka, “Diagnostic approaches for epicyclic gearboxes condition monitoring,” in 8th European Workshop on Structural Health Monitoring (EWSHM), 2016, pp. 5–8.
Z. Dworakowski, L. Ambrozinski, K. Dragan, T. Stepinski, and T. Uhl, “Voting Neural Network Classifier for Detection of Fatigue Damage in Aircrafts,” in 7th European Workshop on Structural Health Monitoring, 2014, pp. 1894–1901.
Z. Dworakowski and K. Mendrok, “Ambient temperature effect elimination using local modal filters,” in VI World Conference on Structural Control and Monitoring, 2014 - referat wygłoszony osobiście.
Z. Dworakowski, L. Ambrozinski, and K. Mendrok, “Damage localization in plates with use of the procedure based on Modal Filtration,” J. Phys. Conf. Ser., vol. 628, p. 012028, 2015.
Z. Dworakowski, O. Graja, A. Jablonski, Z. Dworakowski, K. Dziedziech, O. Graja, A. Jablonski, K. D. Ziemowit Dworakowski, O. Graja, and A. Jablonski, “Speed extraction from vibration signal using ANNs and broadband features,” in 11th International Workshop on Structural Health Monitoring, Stanford, USA, 2017
Z.Dworakowski, K. Mendrok, "Indirect structural change detection based on control algorithm's performance" European Workshop on Structural Health Monitoring, Manchester, UK, 2018
M. Heesch, Z. Dworakowski "Neural Net Model Predictive Controller for Adaptive Active Vibration Suppression of an Unknown System" ICAISC 2019, LNAI 11508, pp. 102–112, 2019
Z. Dworakowski "Reinforcement-learning-based identification of the system for the purpose of structural change detection" 12th International Workshop on Structural Health Monitoring, Stanford, USA, 2019