Abstract
The presence of fault in a structure may lead to catastrophic failure if it remains undetected. So the damage diagnosis is an essential part in health monitoring of structures. Damage in a structure leads to change in the dynamic response which will be helpful for diagnosis of the structure. The relation between modal response and damage vector is in such a way that there exist unique change in response for unique damage. So damage detection is an inverse problem where it is required to relate the modal response to the damage state.
Problems of damage detection are too intricate and the distinct boundary between crisp values cannot be identified for expressing the damage level and measurement deltas. Thus, mapping technique like Fuzzy Logic Inference System (FLIS) can be used for such problems. A fuzzy logic will operate on linguistic variables and associate the data (structural response) with the damage conditions and provide output as level of damage and damage location.
In this study, the change of modal response due to damage in a cantilever beam is investigated and a FLIS is designed for the structural health monitoring purpose. The change in natural frequency is the measurement delta. FLIS is designed using data pool obtained from Finite Element (FE) analysis of different damaged scenarios of the specimen. The FLIS is tested with noise up to 20% and it is found to be robust against small contamination in measurement deltas.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Pawar, P., Ganguli, R.: Structural Heath Monitoring using Genetic Fuzzy System, 1st edn. Springer, London (2011)
Nayak, B.B., Sahu, S., Roy, S.: Damage detection in structural elements: using optimization of fuzzified rules. Mater. Today Proc. 44, 797–800 (2021)
Parhi, D.R.K., Kumar, D.A.: Analysis of methodologies applied for diagnosis of fault in vibrating structures. Int. J. Veh. Noise Vib. 5(4), 271–286 (2009)
Zadeh, L.A.: Information and control. Fuzzy sets 8(3), 338–353 (1965)
Agarwalla, D.K., Parhi, D.R.: Effect of crack on modal parameters of a cantilever beam subjected to vibration. Procedia Eng. 51, 665–669 (2013)
Quila, M., Mondal, S.C., Sarkar, S.: Free vibration analysis of an un-cracked & cracked fixed beam. J. Mech. Civil Eng. 11(3), 76–83 (2014)
Sazonov, E.S., Klinkhachorn, P., Gangarao, H.V., Halabe, U.B.: Fuzzy logic expert system for automated damage detection from changes in strain energy mode shapes. Nondestruct. Test. Eval. 18(1), 1–20 (2002)
Vestroni, F., Capecchi, D.: Damage detection in beam structures based on frequency measurements. J. Eng. Mech. 126(7), 761–768 (2000)
Das, H.C., Parhi, D.R.: Online fuzzy logic crack detection of a cantilever beam. Int. J. Knowl.-Based Intell. Eng. Syst. 12(2), 157–171 (2008)
Ashigbi, D.M., Sackey, M.N., Fiagbe, Y.A., Quaye-Ballard, J.: Vibration response based crack diagnosis in beam-like structures using fuzzy inference system. Sci. Afr. 14, e01051 (2021)
Yu, W., Wang, Y., Gui, W., Yang, C.: A vibration fault diagnosis system of HGS based on FNN. IFAC Proc. Vol. 39(13), 252–257 (2006)
Sawyer, J.P., Rao, S.S.: Structural damage detection and identification using fuzzy logic. AIAA J. 38(12), 2328–2335 (2000)
Angelov, P.P., Filev, D.P.: An approach to online identification of Takagi-Sugeno fuzzy models. IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 34(1), 484–498 (2004)
Pawar, P.M., Ganguli, R.: Matrix crack detection in thin-walled composite beam using genetic fuzzy system. J. Intell. Mater. Syst. Struct. 16(5), 395–409 (2005)
Chandrashekhar, M., Ganguli, R.: Uncertainty handling in structural damage detection using fuzzy logic and probabilistic simulation. Mech. Syst. Signal Process. 23(2), 384–404 (2009)
Mohan, V., Parivallal, S., Kesavan, K., Arunsundaram, B., Ahmed, A.F., Ravisankar, K.: Studies on damage detection using frequency change correlation approach for health assessment. Procedia Eng. 86, 503–510 (2014)
Das, H.C., Parhi, D.R.: Detection of the crack in cantilever structures using fuzzy Gaussian inference technique. AIAA J. 47(1), 105–115 (2009)
Ross, T.J.: Fuzzy Logic With Engineering Applications, 3rd edn. John Wiley & Sons, United Kingdom (2005)
Chandrupatla, T.R., Belegundu, A.D.: Introduction to Finite Elements in Engineering. Prentice Hall, Englewood Cliffs (2001)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Sharma, A., Thankachan, P., Pillai, T.M.M. (2023). Fuzzy Logic-Based Inference System for Structural Health Monitoring of a Cantilever Beam. In: Marano, G.C., Rahul, A.V., Antony, J., Unni Kartha, G., Kavitha, P.E., Preethi, M. (eds) Proceedings of SECON'22. SECON 2022. Lecture Notes in Civil Engineering, vol 284. Springer, Cham. https://doi.org/10.1007/978-3-031-12011-4_69
Download citation
DOI: https://doi.org/10.1007/978-3-031-12011-4_69
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-12010-7
Online ISBN: 978-3-031-12011-4
eBook Packages: EngineeringEngineering (R0)