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Technologies, processes, and systems are not immune to failure, which is why robust monitoring systems are crucial to ensure their continued functionality and safety. An interdisciplinary approach that combines engineering, data science, and material science allows for more comprehensive measurement and analysis, enabling better decision-making and more accurate predictions of performance. The integration of these technologies leads to increased safety, reduced human error, and significant cost savings by preventing costly repairs and downtime. Continuous monitoring helps in avoiding catastrophic failures, allowing for early detection of issues before they escalate. Additionally, it opens opportunities for improving the design of mechanical systems and structures, optimizing the organization of maintenance. By reducing human impact and enhancing safety, these monitoring systems offer a more secure and efficient operation. Furthermore, through advanced predictive analytics, the remaining service life can be estimated, facilitating more effective planning. The development of such smart, intelligent mechanical systems and structures promises a future where maintenance is proactive rather than reactive, creating a safer, more sustainable environment for both operators and systems by leveraging advanced sensors, data analytics, and adaptive technologies for real-time monitoring and damage detection.
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Tom
Strony
377--393
Opis fizyczny
Bibliogr. 46 poz., rys.
Twórcy
autor
- Faculty of Mechanical Engineering, Ss. Cyril and Methodius University in Skopje, marjan.djidrov@mf.edu.mk
Bibliografia
- ABDELGAWAD A., YELAMARTHI K. 2017. Internet of things (IoT) platform for structure health monitoring. Wireless Communications and Mobile Computing, 1: 6560797.
- AONO K., LAJNEF N., FARIDAZAR F., CHAKRABARTTY S. 2016. Infrastructural health monitoring using self-powered internet-of-things. In 2016 IEEE international symposium on circuits and systems (ISCAS).
- ARAVANIS T.C., SAKELLARIOU J., FASSOIS S. 2021. On the functional model-based method for vibration-based robust damage detection: versions and experimental assessment. Structural Health Monitoring, 20(2): 456-474.
- BADIHI H., ZHANG Y., JIANG B., PILLAY P., RAKHEJA S. 2022. A comprehensive review on signal-based and model-based condition monitoring of wind turbines: Fault diagnosis and lifetime prognosis. Proceedings of the IEEE, 110(6): 754-806.
- BALAGEAS D., FRITZEN C.P., GÜEMES A. (Eds.). 2010. Structural health monitoring. Vol. 90. John Wiley & Sons, New York.
- BEHESHTI AVAL S.B., AHMADIAN V., MALDAR M., DARVISHAN E. 2020. Damage detection of structures using signal processing and artificial neural networks. Advances in Structural Engineering, 23(5): 884-897.
- BINI CHIESA M., BODINI I., PETROGALLI C., PROVEZZA L., FACCOLI M., MAZZU A., SOLAZZI L., SANSONI G., LANCINI M. 2018. K-means clustering approach for damage evolution monitoring in RCF tests. Journal of Physics: Conference Series, 1065(10): 102018. 10.1088/1742-6596/1065/10/102018
- BLANKE M., KINNAERT M., LUNZE J., STAROSWIECKI M. 2006. Diagnosis and fault-tolerant control. 2nd Edition. Springer-Verlag, Berlin, Heidelberg,
- CASOLI P., PASTORI M., SCOLARI F., RUNDO M. 2019. A vibration signal-based method for fault identification and classification in hydraulic axial piston pumps. Energies, 12(5): 953.
- CHEN J., PATTON R.J. 1999. Robust model-based fault diagnosis for dynamic systems. The International Series on Asian Studies in Computer and Information Science, Kluwer Academic Publishers.
- DE BELIE N., GRUYAERT E., AL‐TABBAA A., ANTONACI P., BAERA C., BAJARE D., JONKERS H.M. 2018. A review of self‐healing concrete for damage management of structures. Advanced Materials Interfaces, 5(17): 1800074.
- DI NUZZO F., BRUNELLI D., POLONELLI T., BENINI L. 2021. Structural health monitoring system with narrowband IoT and MEMS sensors. IEEE Sensors Journal, 21(14): 16371-16380.
- DJIDROV M., GAVRILOSKI V., JOVANOVA J. 2014. Vibration analysis of cantilever beam for damage detection. FME Transactions, 42(4): 311-316.
- DJIDROV M., GAVRILOSKI V., JOVANOVA J. 2017. Dynamic analysis of cantilever beam with bonded piezoelectric transducers by finite element method. Mechanical Engineering – Scientific Journal, 35(2): 121-127.
- ETXANIZ J., ARANGUREN G., GIL-GARCÍA J.M., SÁNCHEZ J., VIVAS G., GONZÁLEZ J. 2023. Ultrasound-based structural health monitoring methodology employing active and passive techniques. Engineering Failure Analysis, 146: 107077.
- FANG L., ZHOU Y., JIANG Y., PEI Y., YI W. 2020. Vibration‐based damage detection of a steel‐concrete composite slab using non‐model‐based and model‐based methods. Advances in Civil Engineering, 1: 8889277.
- FENG C., LIU C., JIANG D., KONG D., ZHANG W. 2023. Multivariate Anomaly Detection and Early Warning Framework for Wind Turbine Condition Monitoring Using SCADA Data. Journal of Energy Engineering, 149(6): 04023040.
- FENG D., FENG M.Q. 2021. Computer vision for structural dynamics and health monitoring. John Wiley & Sons, New York.
- GOPALAKRISHNAN S., RUZZENE M., HANAGUD S. 2011. Computational techniques for structural health monitoring. Springer, London.
- GULGEC N.S., TAKÁČ M., PAKZAD S.N. 2019. Convolutional neural network approach for robust structural damage detection and localization. Journal of Computing in Civil Engineering, 33(3): 04019005.
- HO L.V., NGUYEN D.H., MOUSAVI M., DE ROECK G., BUI-TIEN T., GANDOMI A.H., WAHAB M.A. 2021. A hybrid computational intelligence approach for structural damage detection using marine predator algorithm and feedforward neural networks. Computers & Structures, 252: 106568.
- ISERMANN R. 2005. Fault-diagnosis systems: an introduction from fault detection to fault tolerance. Springer-Verlag, Berlin, Heidelberg,
- JAN-HWANG LOH K. 2011. Development of multifunctional carbon nanotube nanocomposite sensors for structural health monitoring. ProQuest, UMI Dissertation Publishing.
- JAROSZEWICZ J., ŁUKASZEWICZ K. 2018. Analysis of natural frequency of flexural vibrations of a single-span beam with the consideration of Timoshenko effect. Technical Sciences, 21(3): 215-232. https://doi.org/10.31648/ts.2890
- JO B.W., KHAN R.M.A., LEE Y.S., JO J.H., SALEEM N. 2018. A fiber bragg grating‐based condition monitoring and early damage detection system for the structural safety of underground coal mines using the internet of things. Journal of Sensors, 1: 9301873.
- KESSLER S.S., SPEARING S.M., ATALLA M.J., CESNIK C.E., SOUTIS C. 2002. Damage detection in composite materials using frequency response methods. Composites Part B: Engineering, 33(1): 87-95.
- KOTHAMASU R., HUANG S.H., VERDUIN W.H. 2006. System health monitoring and prognostics – A review of current paradigms and practices. The International Journal of Advanced Manufacturing Technology, 28(9-10): 1012-1024.
- MORADI POUR P., CHAN T., GALLAGE C. 2015. An improved modal strain energy method for structural damage detection, 2D simulation. Structural Engineering and Mechanics, 54(1): 105-119.
- RAMANAMURTHY E.V.V., CHANDRASEKARAN K. 2011. Vibration analysis on a composite beam to identify damage and damage severity using finite element method. IJEST – International Journal of Engineering Science and Technology, 3(7): 5865-5888.
- RYCHLIK A., LIGIER K. 2017. Fatigue crack detection method using analysis of vibration signal. Technical Sciences, 20(1): 63-74. https://doi.org/10.31648/ts.2909
- RYTTER A. 1993. Vibration based inspection of civil engineering structures. Ph.D. Dissertation, Department of Building Technology and Structural Engineering, Aalborg University, Denmark.
- SAEEDIFAR M., MANSVELDER J., MOHAMMADI R., ZAROUCHAS D. 2019. Using passive and active acoustic methods for impact damage assessment of composite structures. Composite Structures, 226: 111252.
- SAKARIS C.S., SAKELLARIOU J.S., FASSOIS S.D. 2017. Random-vibration-based damage detection and precise localization on a lab-scale aircraft stabilizer structure via the Generalized Functional Model Based Method. Structural Health Monitoring, 16(5): 594-610.
- SIMANI S., FANTUZZI C., PATTON R.J. 2002. Model-based fault diagnosis in dynamic systems using identification techniques (Advances in Industrial Control). Springer-Verlag, Berlin Heidelberg.
- SOFI A., REGITA J.J., RANE B., LAU H.H. 2022. Structural health monitoring using wireless smart sensor network. An overview. Mechanical Systems and Signal Processing, 163: 108113.
- STASZEWSKI W.J., MAHZAN S., TRAYNOR R. 2009. Health monitoring of aerospace composite structures – Active and passive approach. Composites Science And Technology, 69(11-12): 1678-1685.
- STEPINSKI T., UHL T., STASZEWSKI W. 2013. Advanced structural damage detection – From theory to engineering applications. John Wiley and Sons, New York.
- TAVARES A., DI LORENZO E., PEETERS B., COPPOTELLI G., SILVESTRE N. 2021. Damage detection in lightweight structures using artificial intelligence techniques. Experimental Techniques, 45(3): 389-410.
- TOKOGNON C.A., GAO B., TIAN G.Y., YAN Y. 2017. Structural health monitoring framework based on Internet of Things: A survey. IEEE Internet of Things Journal, 4(3): 619-635.
- TORRES‐ARREDONDO M.A., SIERRA‐PÉREZ J., TIBADUIZA D.A., MCGUGAN M., RODELLAR J., FRITZEN C.P. 2015. Signal‐based nonlinear modelling for damage assessment under variable temperature conditions by means of acousto‐ultrasonics. Structural Control and Health Monitoring, 22(8): 1103-1118.
- TOWSYFYAN H., BIGURI A., BOARDMAN R., BLUMENSATH T. 2020. Successes and challenges in non-destructive testing of aircraft composite structures. Chinese Journal of Aeronautics, 33(3): 771-791.
- VENKAT V., RENGASWAMY R., YIN K., KAVURI S.N. 2003. A review of process fault detection and diagnosis. Part I. Quantitative model-based methods. Computers & Chemical Engineering, 27(3): 293-311.
- WANG C.S., CHANG F.-K. 1999. “Built-in diagnostics for impact damage identification of composite structures”, Structural Health Monitoring 2000. Proceedings of the Second International Workshop on Structural Health Monitoring, Stanford, CA, September 8-10. Technomic Publishing, Lancaster–Basel.
- ZAKIROV R., GIYASOVA F. 2022. Application of fiber-optic sensors for the aircraft structure monitoring. Safety in Aviation and Space Technologies: Select Proceedings of the 9th World Congress “Aviation in the XXI Century”. Springer International Publishing, Berlin.
- ZHANG W., ZHENG Q., ASHOUR A., HAN B. 2020. Self-healing cement concrete composites for resilient infrastructures: A review. Composites. Part B: Engineering, 189: 107892.
- ZHONG H., YANG M. 2016. Damage detection for plate-like structures using generalized curvature mode shape method. Journal of Civil Structural Health Monitoring, 6: 141-152.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-b51fa357-bd94-472a-b602-982be9623f49