Damage detection for UHPFRC communication tower based on frequency data and particle swarm optimization
Abstract
Advances in the telecommunication and broadcasting sectors have increased the need for networking equipment of communication towers. Slender structures, such as towers, are sensitive to dynamic loads, such as vibration forces. Therefore, the stability and reliability performance of towers can be maintained effectively through the prompt detection, localization, and quantification of structural damages by obtaining the dynamic frequency response of towers. However, frequency analysis for damaged structures requires long computational procedures and is difficult to perform because of the damages in real structures, particularly in towers. Therefore, this study proposed a correlation factor that can identify the relationship between frequenciesunderhealthy and damaged conditions of ultra high performance fiber-reinforced concrete (UHPFRC) communication towers using particle swarm optimization. The finite element method was implemented to simulate three UHPFRC communication towers, and an experimental test was conducted to validate and verify the developed correlation factor.
Keyword : communication towers, ultrahigh performance concrete (UHPC), dynamic nonlinear analysis, frequency response, correlation factor, finite element method, particle swarm optimization (PSO)
How to Cite
Jabbar, S., Hejazi, F., Hanoon, A. N., & Rashid, R. S. M. (2019). Damage detection for UHPFRC communication tower based on frequency data and particle swarm optimization. Journal of Civil Engineering and Management, 25(6), 495-517. https://doi.org/10.3846/jcem.2019.8002
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Alaghebandha, M., Hajipour, V., & Hemmati, M. (2017). Optimizing multi-objective sequencing problem in mixed-model assembly line on just-in-time: particle swarm optimization algorithm. International Journal of Management Science and Engineering Management, 12(4), 288-298. https://doi.org/10.1080/17509653.2016.1258593
Antunes, P., Travanca, R., Varum, H., & André, P. (2012). Dynamic monitoring and numerical modelling of communication towers with FBG based accelerometers. Journal of Constructional Steel Research, 74, 58-62. https://doi.org/10.1016/j.jcsr.2012.02.006
Ashour, A. F., & Rishi, G. (2000). Tests of reinforced concrete continuous deep beams with web openings. ACI Structural Journal, 97(3), 418-426.
Begambre, O., & Laier, J. E. (2009). A hybrid Particle Swarm Optimization–Simplex algorithm (PSOS) for structural damage identification. Advances in Engineering Software, 40(9), 883-891. https://doi.org/10.1016/j.advengsoft.2009.01.004
Chagwiza, G., Jones, B. C., Hove-Musekwa, S. D., & Mtisi, S. (2018). A new hybrid matheuristic optimization algorithm for solving design and network engineering problems. International Journal of Management Science and Engineering Management, 13(1), 11-19. https://doi.org/10.1080/17509653.2016.1269136
Dassault Systèmes Simulia Corp. (2014). ABAQUS standard user’s manual. Version 6. RI, USA: Providence,. RI, USA.
Dong, R., Xu, J., & Lin, B. (2017). ROI-based study on impact factors of distributed PV projects by LSSVM-PSO. Energy, 124, 336-349. https://doi.org/10.1016/j.energy.2017.02.056
Dua, R., Watkins, S. E., Wunsch, D. C., Chandrashekhara, K., & Akhavan, F. (2001, July). Detection and classification of impact-induced damage in composite plates using neural networks. In Proceedings of the International Joint Conference on Neural Networks (IJCNN’01), 15–19 July 2001, Washington, DC, USA. https://doi.org/10.1109/IJCNN.2001.939106
Eberhart, R., & Kennedy, J. (1995, October). A new optimizer using particle swarm theory. In Proceedings of the Sixth International Symposium on the Micro Machine and Human Science (MHS’95), 4–6 October 1995, Nagoya, Japan. https://doi.org/10.1109/MHS.1995.494215
European Committee for Standardization (CEN). (2005). EN 1991-1-4, Eurocode 1: Actions on structures, part 1–4: general actions – wind actions.
European Committee for Standardization (CEN). (2006). EN 1993-3-1, Eurocode 3: Design of steel structures, part 3–1:
towers, masts and chimneys – towers and masts.
Frank, I. E., & Todeschini, R. (1994). The data analysis handbook. Vol. 14. Amsterdam, Netherlands: Elsevier. Gomes, F. P. (2000). Experimental statistics. Piracicaba: FEALQ (in Portuguese).
Grünbaum, C. (2008). Structures of tall buildings (Rapport TVBK-5156). Lund: Lunds Tekniska Högskola.
Guidorzi, R., Diversi, R., Vincenzi, L., Mazzotti, C., & Simioli, V. (2014). Structural monitoring of a tower by means of MEMSbased sensing and enhanced autoregressive models. European Journal of Control, 20(1), 4-13. https://doi.org/10.1016/j.ejcon.2013.06.004
Hanoon, A. N., Jaafar, M. S., Hejazi, F., & Abdul Aziz, F. N. (2017a). Strut-and-tie model for externally bonded CFRPstrengthened reinforced concrete deep beams based on particle swarm optimization algorithm: CFRP debonding and rupture. Construction and Building Materials, 147, 428-447. https://doi.org/10.1016/j.conbuildmat.2017.04.094
Hanoon, A. N., Jaafar, M. S., Hejazi, F., & Abdul Aziz, F. N. (2017b). Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique. Engineering Optimization, 49(9), 1483-1501. https://doi.org/10.1080/0305215X.2016.1256729
Joint Technical Committee. (2002). AS/NZS 1170.2 Structural design actions, Part 2: wind actions. Australian/New Zealand Standard. Sydney: Standards Australia International Ltd and Wellington: Standards New Zealand.
Kaveh, A., & Zolghadr, A. (2015). An improved CSS for damage detection of truss structures using changes in natural frequencies and mode shapes. Advances in Engineering Software, 80, 93-100. https://doi.org/10.1016/j.advengsoft.2014.09.010
Kazemi, M. A., Nazari, F., Karimi, M., Baghalian, S., Rahbarikahjogh, M. A., & Khodabandelou, A. M. (2011, April). Detection of multiple cracks in beams using particle swarm optimization and artificial neural network. In The 4th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO), 19–21 April 2011, Kuala Lumpur, Malaysia. https://doi.org/10.1109/ICMSAO.2011.5775595
Kessler, S. S., Spearing, S. M., Atalla, M. J., Cesnik, C. E. S., & Soutis, C. (2002). Damage detection in composite materials using frequency response methods. Composites Part B: Engineering, 33(1), 87-95. https://doi.org/10.1016/S1359-8368(01)00050-6
Kim, J-T., & Stubbs, N. (2002). Improved damage identification method based on modal information. Journal of Sound and Vibration, 252(2), 223-238. https://doi.org/10.1006/jsvi.2001.3749
Kulkarni, R. V., & Venayagamoorthy, G. K. (2011). Particle swarm optimization in wireless-sensor networks: A brief survey. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41(2), 262-267. https://doi.org/10.1109/TSMCC.2010.2054080
Lavanya, D., & Udgata, S. K. (2011). Swarm intelligence based localization in wireless sensor networks. In the International Workshop on Multi-disciplinary Trends in Artificial Intelligence. https://doi.org/10.1007/978-3-642-25725-4_28
Majumdar, A., Nanda, B., Maiti, D. K., & Maity, D. (2014). Structural damage detection based on modal parameters using continuous ant colony optimization. Advances in Civil Engineering, Article ID 174185. https://doi.org/10.1155/2014/174185
Mhaske, M. S., & Shelke, R. S. (2015). Detection of depth and location of crack in a beam by vibration measurement and its comparative validation in ANN and GA. International Engineering Research Journal (IERJ), Special Issue 2, 488-493.
Negm, H. M., & Maalawi, K. Y. (2000). Structural design optimization of wind turbine towers. Computers & Structures, 74 (6), 649-666. https://doi.org/10.1016/S0045-7949(99)00079-6
Nhamage, I. A., Lopez, R. H., & Miguel, L. F. F. (2016). An improved hybrid optimization algorithm for vibration baseddamage detection. Advances in Engineering Software, 93, 4764. https://doi.org/10.1016/j.advengsoft.2015.12.003
Oros Gmbh. (2006). 3-Series/NVGate reference manual.
Paultre, P., Weber, B., Mousseau, S., & Proulx, J. (2016). Detection and prediction of seismic damage to a high-strength concrete moment resisting frame structure. Engineering Structures, 114, 209-225. https://doi.org/10.1016/j.engstruct.2016.02.013
Rardin, R. L. (1998). Optimization in operations research. New York: Prentice Hall.
Ren, W.-X., & De Roeck, G. (2002). Structural damage identification using modal data. II: Test verification. Journal of Structural Engineering, 128(1), 96-104. https://doi.org/10.1061/(ASCE)0733-9445(2002)128:1(96)
Saisi, A., Gentile, C., & Guidobaldi, M. (2015). Post-earthquake continuous dynamic monitoring of the Gabbia Tower in Mantua, Italy. Construction and Building Materials, 81, 101-112. https://doi.org/10.1016/j.conbuildmat.2015.02.010
Shi, Y., & Eberhart, R. (1998). A modified particle swarm optimizer. In Proceedings of the IEEE International Conference on the Evolutionary Computation, IEEE World Congress on Computational Intelligence, 4–9 May 1998, Anchorage, AK, USA. https://doi.org/10.1109/ICEC.1998.699146
Sinou, J.-J. (2009). A review of damage detection and health monitoring of mechanical systems from changes in the measurement of linear and non-linear vibrations. Nova Science Publishers, Inc.
Smith, K. B., & Shust, W. C. (2004). Bounding natural frequencies in structures I: Gross geometry, material and boundary conditions. In Proceedings of the XXII International Modal Analysis Conference, Society of Experimental Mechanics.
Sutar, M. K. (2012). Finite element analysis of a cracked cantilever beam. International Journal of Advanced Engineering Research and Studies, 1(2), 285-289.
Xie, F., Wang, Q-j., & Li, G-l. (2012). Optimization research of FOC based on PSO of induction motors. In 15th International Conference on Electrical Machines and Systems (ICEMS), 21– 24 October 2012, Sapporo, Japan.
Yang, X. F., Swamidas, A. S. J., & Seshadri, R. (2001). Crack identification in vibrating beams using the energy method. Journal of Sound and Vibration, 244(2), 339-357. https://doi.org/10.1006/jsvi.2000.3498
Antunes, P., Travanca, R., Varum, H., & André, P. (2012). Dynamic monitoring and numerical modelling of communication towers with FBG based accelerometers. Journal of Constructional Steel Research, 74, 58-62. https://doi.org/10.1016/j.jcsr.2012.02.006
Ashour, A. F., & Rishi, G. (2000). Tests of reinforced concrete continuous deep beams with web openings. ACI Structural Journal, 97(3), 418-426.
Begambre, O., & Laier, J. E. (2009). A hybrid Particle Swarm Optimization–Simplex algorithm (PSOS) for structural damage identification. Advances in Engineering Software, 40(9), 883-891. https://doi.org/10.1016/j.advengsoft.2009.01.004
Chagwiza, G., Jones, B. C., Hove-Musekwa, S. D., & Mtisi, S. (2018). A new hybrid matheuristic optimization algorithm for solving design and network engineering problems. International Journal of Management Science and Engineering Management, 13(1), 11-19. https://doi.org/10.1080/17509653.2016.1269136
Dassault Systèmes Simulia Corp. (2014). ABAQUS standard user’s manual. Version 6. RI, USA: Providence,. RI, USA.
Dong, R., Xu, J., & Lin, B. (2017). ROI-based study on impact factors of distributed PV projects by LSSVM-PSO. Energy, 124, 336-349. https://doi.org/10.1016/j.energy.2017.02.056
Dua, R., Watkins, S. E., Wunsch, D. C., Chandrashekhara, K., & Akhavan, F. (2001, July). Detection and classification of impact-induced damage in composite plates using neural networks. In Proceedings of the International Joint Conference on Neural Networks (IJCNN’01), 15–19 July 2001, Washington, DC, USA. https://doi.org/10.1109/IJCNN.2001.939106
Eberhart, R., & Kennedy, J. (1995, October). A new optimizer using particle swarm theory. In Proceedings of the Sixth International Symposium on the Micro Machine and Human Science (MHS’95), 4–6 October 1995, Nagoya, Japan. https://doi.org/10.1109/MHS.1995.494215
European Committee for Standardization (CEN). (2005). EN 1991-1-4, Eurocode 1: Actions on structures, part 1–4: general actions – wind actions.
European Committee for Standardization (CEN). (2006). EN 1993-3-1, Eurocode 3: Design of steel structures, part 3–1:
towers, masts and chimneys – towers and masts.
Frank, I. E., & Todeschini, R. (1994). The data analysis handbook. Vol. 14. Amsterdam, Netherlands: Elsevier. Gomes, F. P. (2000). Experimental statistics. Piracicaba: FEALQ (in Portuguese).
Grünbaum, C. (2008). Structures of tall buildings (Rapport TVBK-5156). Lund: Lunds Tekniska Högskola.
Guidorzi, R., Diversi, R., Vincenzi, L., Mazzotti, C., & Simioli, V. (2014). Structural monitoring of a tower by means of MEMSbased sensing and enhanced autoregressive models. European Journal of Control, 20(1), 4-13. https://doi.org/10.1016/j.ejcon.2013.06.004
Hanoon, A. N., Jaafar, M. S., Hejazi, F., & Abdul Aziz, F. N. (2017a). Strut-and-tie model for externally bonded CFRPstrengthened reinforced concrete deep beams based on particle swarm optimization algorithm: CFRP debonding and rupture. Construction and Building Materials, 147, 428-447. https://doi.org/10.1016/j.conbuildmat.2017.04.094
Hanoon, A. N., Jaafar, M. S., Hejazi, F., & Abdul Aziz, F. N. (2017b). Energy absorption evaluation of reinforced concrete beams under various loading rates based on particle swarm optimization technique. Engineering Optimization, 49(9), 1483-1501. https://doi.org/10.1080/0305215X.2016.1256729
Joint Technical Committee. (2002). AS/NZS 1170.2 Structural design actions, Part 2: wind actions. Australian/New Zealand Standard. Sydney: Standards Australia International Ltd and Wellington: Standards New Zealand.
Kaveh, A., & Zolghadr, A. (2015). An improved CSS for damage detection of truss structures using changes in natural frequencies and mode shapes. Advances in Engineering Software, 80, 93-100. https://doi.org/10.1016/j.advengsoft.2014.09.010
Kazemi, M. A., Nazari, F., Karimi, M., Baghalian, S., Rahbarikahjogh, M. A., & Khodabandelou, A. M. (2011, April). Detection of multiple cracks in beams using particle swarm optimization and artificial neural network. In The 4th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO), 19–21 April 2011, Kuala Lumpur, Malaysia. https://doi.org/10.1109/ICMSAO.2011.5775595
Kessler, S. S., Spearing, S. M., Atalla, M. J., Cesnik, C. E. S., & Soutis, C. (2002). Damage detection in composite materials using frequency response methods. Composites Part B: Engineering, 33(1), 87-95. https://doi.org/10.1016/S1359-8368(01)00050-6
Kim, J-T., & Stubbs, N. (2002). Improved damage identification method based on modal information. Journal of Sound and Vibration, 252(2), 223-238. https://doi.org/10.1006/jsvi.2001.3749
Kulkarni, R. V., & Venayagamoorthy, G. K. (2011). Particle swarm optimization in wireless-sensor networks: A brief survey. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41(2), 262-267. https://doi.org/10.1109/TSMCC.2010.2054080
Lavanya, D., & Udgata, S. K. (2011). Swarm intelligence based localization in wireless sensor networks. In the International Workshop on Multi-disciplinary Trends in Artificial Intelligence. https://doi.org/10.1007/978-3-642-25725-4_28
Majumdar, A., Nanda, B., Maiti, D. K., & Maity, D. (2014). Structural damage detection based on modal parameters using continuous ant colony optimization. Advances in Civil Engineering, Article ID 174185. https://doi.org/10.1155/2014/174185
Mhaske, M. S., & Shelke, R. S. (2015). Detection of depth and location of crack in a beam by vibration measurement and its comparative validation in ANN and GA. International Engineering Research Journal (IERJ), Special Issue 2, 488-493.
Negm, H. M., & Maalawi, K. Y. (2000). Structural design optimization of wind turbine towers. Computers & Structures, 74 (6), 649-666. https://doi.org/10.1016/S0045-7949(99)00079-6
Nhamage, I. A., Lopez, R. H., & Miguel, L. F. F. (2016). An improved hybrid optimization algorithm for vibration baseddamage detection. Advances in Engineering Software, 93, 4764. https://doi.org/10.1016/j.advengsoft.2015.12.003
Oros Gmbh. (2006). 3-Series/NVGate reference manual.
Paultre, P., Weber, B., Mousseau, S., & Proulx, J. (2016). Detection and prediction of seismic damage to a high-strength concrete moment resisting frame structure. Engineering Structures, 114, 209-225. https://doi.org/10.1016/j.engstruct.2016.02.013
Rardin, R. L. (1998). Optimization in operations research. New York: Prentice Hall.
Ren, W.-X., & De Roeck, G. (2002). Structural damage identification using modal data. II: Test verification. Journal of Structural Engineering, 128(1), 96-104. https://doi.org/10.1061/(ASCE)0733-9445(2002)128:1(96)
Saisi, A., Gentile, C., & Guidobaldi, M. (2015). Post-earthquake continuous dynamic monitoring of the Gabbia Tower in Mantua, Italy. Construction and Building Materials, 81, 101-112. https://doi.org/10.1016/j.conbuildmat.2015.02.010
Shi, Y., & Eberhart, R. (1998). A modified particle swarm optimizer. In Proceedings of the IEEE International Conference on the Evolutionary Computation, IEEE World Congress on Computational Intelligence, 4–9 May 1998, Anchorage, AK, USA. https://doi.org/10.1109/ICEC.1998.699146
Sinou, J.-J. (2009). A review of damage detection and health monitoring of mechanical systems from changes in the measurement of linear and non-linear vibrations. Nova Science Publishers, Inc.
Smith, K. B., & Shust, W. C. (2004). Bounding natural frequencies in structures I: Gross geometry, material and boundary conditions. In Proceedings of the XXII International Modal Analysis Conference, Society of Experimental Mechanics.
Sutar, M. K. (2012). Finite element analysis of a cracked cantilever beam. International Journal of Advanced Engineering Research and Studies, 1(2), 285-289.
Xie, F., Wang, Q-j., & Li, G-l. (2012). Optimization research of FOC based on PSO of induction motors. In 15th International Conference on Electrical Machines and Systems (ICEMS), 21– 24 October 2012, Sapporo, Japan.
Yang, X. F., Swamidas, A. S. J., & Seshadri, R. (2001). Crack identification in vibrating beams using the energy method. Journal of Sound and Vibration, 244(2), 339-357. https://doi.org/10.1006/jsvi.2000.3498