An experimental-based python programming for structural health monitoring of non-engineered RC frame

  • Umesh T. Jagadale
  • Chittaranjan B. NayakEmail author
  • Asmita Mankar
  • Sunil B. Thakare
  • Wasudeo N. Deulkar
Technical papers


Most of the damages were experienced on the buildings which were conventionally built without any consideration of IS codal provisions conveniently called non-engineered structures. Non-engineered structures are frequently affected by vibrations due to various natural and artificial sources. Thus, it needs special attention. It is, therefore, necessary to check the performance of non-engineered structures through various health monitoring techniques. A piezoelectric-ceramic (PZT) sensor-based technique called electromechanical impedance (EMI), in which the sensors efficiently operate at a high-frequency range and can typically detect damage at the initial level which is implemented for the purpose. In this research work, experimental tests are performed on the non-engineered reinforced concrete frame using EMI technique by utilizing a PZT sensor which is bonded to the structure using the high-strength epoxy adhesive. The experiment is carried out to identify and locate the damages using frequency variations, and the severity was checked using extracted equivalent parameter; damage index. Second, a Python programming is developed by the authors to identify and quantify the damage index and root mean square deviation index in the frame. The frequency responses obtained from the experimental tests are used in the programming. The performance of the program is compared with the experimentally calculated parameters to check the efficiency of the programming. According to the results of the comparison, it is observed that python programming can be effectively used for damage detection.


Non-engineered Health monitoring Electromechanical impedance PZT Damage index and Python 


Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.


  1. 1.
    Nayak CB, Thakare SB (2019) Seismic performance of existing water tank after condition ranking using non-destructive testing. Int J Adv Struct Eng 11(4):395–410. CrossRefGoogle Scholar
  2. 2.
    Jagtap A, Nayak CB (2019) Corrosion monitoring of RCC structure by using corrosion expansion sensor. Techno-Societal 2018:205–216. CrossRefGoogle Scholar
  3. 3.
    Arya A (2000) Non-engineered construction in developing countries: an approach toward earthquake risk preduction. In: 12th world conference on earthquake engineering, vol 33CrossRefGoogle Scholar
  4. 4.
    Boen T (2015) Earthquake resistant design of a non-engineered building in Indonesia. In: Proceedings in Workshop of the EQTAP-IV, EDM Press, p 1–34Google Scholar
  5. 5.
    Kusumastuti D, Pribadi KS, Rildova R (2008) Reducing earthquake vulnerability of non-engineered buildings: case study of retrofitting of school building in Indonesia. In: 12th world conference on earthquake engineering, p 1–8Google Scholar
  6. 6.
    Park S (2010) Experimental and analytical studies on old reinforced concrete buildings with seismically vulnerable beam-column joints. Doctoral dissertation, UC BerkeleyGoogle Scholar
  7. 7.
    Watanabe S, Shima N, Fujita K (2018) Research on non-engineered housing construction based on a field investigation in Jakarta. J Asian Archit Build Eng 12(1):33–40. CrossRefGoogle Scholar
  8. 8.
    Teguh M (2016) structural behaviour of precast reinforced concrete frames on a non-engineered building subjected to lateral loads. Int J Eng Technol Innov 6(2):152–164Google Scholar
  9. 9.
    Reyes JC, Yamin LE, Hassan WM, Sandoval JD, Gonzalez CD, Galvis FA (2018) Shear behavior of adobe and rammed earth walls of heritage structures. Eng Struct 174:526–537. CrossRefGoogle Scholar
  10. 10.
    Kaur N, Bhalla S (2016) Numerical investigations on energy harvesting potential of thin PZT patches adhesively bonded on RC structure. Sens Actuators 241:44–59. CrossRefGoogle Scholar
  11. 11.
    Hui L, Jinping O (2011) Structural health monitoring: from sensing technology stepping to health diagnosis. Proc Eng 14:753–760. CrossRefGoogle Scholar
  12. 12.
    Kaveh A, Zolghadr A (2012) An improved charged system search for structural damage identification in beams and frames using changes in natural frequencies. Int J Optim Civ Eng 2(3):321–339Google Scholar
  13. 13.
    Park G, Cudney HH, Inman Daniel J (2000) Impedance-based health monitoring of civil structural components. J Infrastruct Syst 6:153–160. CrossRefGoogle Scholar
  14. 14.
    Bhalla S, Soh CK (2004) Structural health monitoring by piezo-impedance transducers, I: modeling. J Aerosp Eng. CrossRefGoogle Scholar
  15. 15.
    Yan AM, Kerschen G, Boe PD, Golinval JC (2005) Structural damage diagnosis under varying environmental conditions part I: a linear analysis. Mech Syst Signal Process 19(4):847–864. CrossRefGoogle Scholar
  16. 16.
    Li H, Huang Y, Han W, Ou JP (2009) Damage warning of fatigue test of cable based on acoustic emission and fractal theory. In: Proceedings. of the 4th international conference on structural health monitoring on intelligent infrastructure (SHMII-4), Zurich, Switzerland, Paper No. 332Google Scholar
  17. 17.
    Hu X, Zhu H, Wang D (2014) A study of concrete slab damage detection based on the electromechanical impedance method. Sensors 14(10):19897–19909. CrossRefGoogle Scholar
  18. 18.
    Karayannis CG, Chalioris CE, Angeli GM, Papadopolous NA, Favvata MJ, Providakis CP (2016) Experimental damage evaluation of reinforced concrete steel bars using piezoelectric sensors. Constr Build Mater 105:227–244. CrossRefGoogle Scholar
  19. 19.
    Kaveh A, Maniat M (2015) Damage detection based on MCSS and PSO using modal data. Smart Struct Syst 15(5):1253–1270. CrossRefGoogle Scholar
  20. 20.
    Kaveh A, Vaez SRH, Hosseini P, Fallah N (2016) Detection of damage in truss structures using Simplified Dolphin Echolocation algorithm based on modal data. Smart Struct Syst 18(5):983–1004. CrossRefGoogle Scholar
  21. 21.
    Na W, Baek J (2018) A review of the piezoelectric electromechanical impedance based structural health monitoring technique for engineering structures. Sensors 18(5):1–18. CrossRefGoogle Scholar
  22. 22.
    Nayak CB, Pawar S (2013) An experimental study on vibration control of civil structure using smart materials. Int J Mult Res 1(10):10–15Google Scholar
  23. 23.
    Jagadale UT, Narute G, Nayak CB, Deulkar WN (2018) Structural health monitoring using piezo-ceramics smart material. In: 9th international conference on sustainable built environment at University of Paradeniya, Kandy, SriLanka, p 1–5Google Scholar
  24. 24.
    Morfidisa K, Kostinakis K (2019) Comparative evaluation of MFP and RBF neural networks’ ability for instant estimation of r/c buildings’ seismic damage level. Eng Struct 197:1–19. CrossRefGoogle Scholar
  25. 25.
    Jagadale UT, Kharade R, Nayak CB, Deulkar WN (2019) Experimental invetigation for damage evaluation of bridges using piezo-transducers. International Association for Computer Methods and Advances in Geomechanics (IACMAG), IIT Gandhinagar, India, p 1–10Google Scholar
  26. 26.
    Kaveh A, Hoseini Vaez SR, Hosseini P (2019) Enhanced vibrating particles system algorithm for damage identification of truss structures. Scientia Iranica 26(1):246–256. CrossRefGoogle Scholar
  27. 27.
    Kare V, Nayak CB, Jagadale UT, Deulkar W (2020) Earthquake response of 3D frames with strap footing considering soil structure interaction. In: Techno-Societal 2018, pp 895–904. Google Scholar
  28. 28.
    Nayak CB, Walke S, Kokare S (2019) Optimal structural design of diagrid structure for tall structure. In: ICRRM 2019 -System reliability, quality control, safety, maintenance and management, pp 263–271. Google Scholar
  29. 29.
    Liao W, Lin CH, Hwang JS, Song G (2013) Seismic health monitoring of RC frame structures using smart aggregates. Earthq Eng Eng Vib 12(1):25–32. CrossRefGoogle Scholar
  30. 30.
    Soh CK, Tseng KH, Bhalla S, Gupta A (2000) Performance of smart piezoceramic patches in health monitoring of a RC bridge. Smart Mater Struct 9(4):533–542. CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Umesh T. Jagadale
    • 1
  • Chittaranjan B. Nayak
    • 2
    Email author
  • Asmita Mankar
    • 2
  • Sunil B. Thakare
    • 3
  • Wasudeo N. Deulkar
    • 4
  1. 1.JSPM’s Rajarshi Shahu College of EngineeringPuneIndia
  2. 2.Vidya Pratishthan Vidya Pratishthans Kamalnayan Bajaj Institute of Engineering and TechnologyBaramatiIndia
  3. 3.Akhil Bhartiya Maratha Shikshan Parishads Anantrao Pawar College of Engineering and ResearchPuneIndia
  4. 4.Government College of Engineering and Research, Avasari KhurdAmbegaonIndia

Personalised recommendations