A Novel Nonlinear Acoustic Health Monitoring Approach for Detecting Loose Bolts

  • Amin Baghalian
  • Volkan Y. Senyurek
  • Shervin Tashakori
  • Dwayne McDaniel
  • Ibrahim N. Tansel


To date, sensors have been the inevitable component of structural health monitoring (SHM) systems. Typically, sensory signals are digitized, processed by computers, and then the information is presented to the operator with plots or warnings depending on the sophistication of the system. This study proposes a novel nonlinear acoustic health monitoring (NAHM) approach for detection of loose bolts, which can work with and without any sensors. The structure is excited with bitonal excitations, which their difference is in the audible range. When the bolts are well tightened, the structure remains silent. But, the structure creates audible sound or verbal warnings in the presence of one or more loose bolts. There is no need for sensor(s), A/D converters or computers between the operator and the structure. However, it is also possible to attach a piezoelectric sensor or to use a microphone/sound level meter for further analysis of the structure’s response. The feasibility of the concept was demonstrated by detecting the loose bolt in a bolted plate system. For demonstrating the industrial potential of the proposed NAHM system, the concept was implemented for two simple washers held with nuts and bolts. Additionally, the intensities of the audible alarms were studied at different torque levels. The proposed NAHM may be used as a low-cost sensor-free SHM or as a backup for conventional nonlinear SHM systems.


Structural health monitoring Loose bolt detection Sensor-free Heterodyning effect Ultrasonic guided-waves 



The authors acknowledge the University Graduate School, Florida International University for providing support for this research in the form of Doctoral Evidence Acquisition (DEA) and Dissertation Year Fellowships (DYF) for Dr. Amin Baghalian and Shervin Tashakori.


  1. 1.
    Giurgiutiu, V., Zagrai, A., Jing Bao, J.: Piezoelectric wafer embedded active sensors for aging aircraft structural health monitoring. Struct. Heal. Monit. 1(1), 41–61 (2002)CrossRefGoogle Scholar
  2. 2.
    Raghavan, A., Cesnik, C.E.S.: Review of guided-wave structural health monitoring. Shock Vib. Dig. 39(2), 91–114 (2007)CrossRefGoogle Scholar
  3. 3.
    Liu, Y., Mohanty, S., Chattopadhyay, A.: Condition based structural health monitoring and prognosis of composite structures under uniaxial and biaxial loading. J. Nondestruct. Eval. 29(3), 181–188 (2010)CrossRefGoogle Scholar
  4. 4.
    Brownjohn, J.M.W.: Structural health monitoring of civil infrastructure. Philos. Trans. R. Soc. Lond. A 365(1851), 589–622 (2007)CrossRefGoogle Scholar
  5. 5.
    Baqersad, J., Poozesh, P., Niezrecki, C., Avitabile, P.: Photogrammetry and optical methods in structural dynamics—a review. Mech. Syst. Signal Process. 86, 1–18 (2016)Google Scholar
  6. 6.
    Poozesh, P., Aizawa, K., Niezrecki, C., Baqersad, J., Inalpolat, M., Heilmann, G.: Structural health monitoring of wind turbine blades using acoustic microphone array. Struct. Heal. Monit. 16(4), 471–485 (2016)CrossRefGoogle Scholar
  7. 7.
    Zhao, X., et al.: Active health monitoring of an aircraft wing with an embedded piezoelectric sensor/actuator network: II. Wireless approaches. Smart Mater. Struct. 16(4), 1218–1225 (2007)CrossRefGoogle Scholar
  8. 8.
    Park, G., Farrar, C.R., di Scalea, F.L., Coccia, S.: Performance assessment and validation of piezoelectric active-sensors in structural health monitoring. Smart Mater. Struct. 15(6), 1673–1683 (2006)CrossRefGoogle Scholar
  9. 9.
    Bhuiyan, M., Shen, Y., Giurgiutiu, V.: Guided wave based crack detection in the rivet hole using global analytical with local FEM approach. Materials (Basel) 9(7), 602 (2016)CrossRefGoogle Scholar
  10. 10.
    Giurgiutiu, V., Gresil, M., Lin, B., Cuc, A., Shen, Y., Roman, C.: Predictive modeling of piezoelectric wafer active sensors interaction with high-frequency structural waves and vibration. Acta Mech. 223(8), 1681–1691 (2012)CrossRefMATHGoogle Scholar
  11. 11.
    Staszewski, W.J., Mahzan, S., Traynor, R.: Health monitoring of aerospace composite structures—active and passive approach. Compos. Sci. Technol. 69(11–12), 1678–1685 (2009)CrossRefGoogle Scholar
  12. 12.
    Zaleha, M., Mahzan, S., Idris, M.I.: Passive damage detection of natural fibre reinforced composites using sensor response data. Appl. Mech. Mater. 534, 17–23 (2014)CrossRefGoogle Scholar
  13. 13.
    Bhuiyan, M.Y., Bao, J., Poddar, B., Giurgiutiu, V.: Towards identifying crack-length related resonances in acoustic emission waveforms for SHM applications. Struct. Heal. Monit. Int. J. (2017).
  14. 14.
    Sabra, K.G., Huston, S.: Passive structural health monitoring of a high-speed naval ship from ambient vibrations. J. Acoust. Soc. Am. 129(5), 2991–2999 (2011)CrossRefGoogle Scholar
  15. 15.
    Joseph, R., Bhuiyan, M. Y., Giurgiutiu, V.: Acoustic emission source modeling in a plate using buried moment tensors. In: Proceedings of SPIE on Health Monitoring of Structural and Biological Systems, vol. 10170, pp. 1017028-1–8 (2017)Google Scholar
  16. 16.
    Stoyko, D.K., Popplewell, N., Shah, A.H.: Finding a pipe’s elastic and dimensional properties using ultrasonic guided wave cut-off frequencies. NDT&E Int. 43(7), 568–578 (2010)CrossRefGoogle Scholar
  17. 17.
    Siqueira, M.H.S., Gatts, C.E.N., Da Silva, R.R., Rebello, J.M.A.: The use of ultrasonic guided waves and wavelets analysis in pipe inspection. Ultrasonics 41(10), 785–797 (2004)CrossRefGoogle Scholar
  18. 18.
    Glaser, S.D., Li, M., Wang, M.L., Ou, J., Lynch, J.: Sensor technology innovation for the advancement of structural health monitoring: a strategic program of US-China research for the next decade. Smart Struct. Syst. 3(2), 221–244 (2007)CrossRefGoogle Scholar
  19. 19.
    Giurgiutiu, V.: Tuned lamb wave excitation and detection with piezoelectric wafer active sensors for structural health monitoring. J. Intell. Mater. Syst. Struct. 16(4), 291–305 (2005)CrossRefGoogle Scholar
  20. 20.
    Carandente, R., Lovstad, A., Cawley, P.: The influence of sharp edges in corrosion profiles on the reflection of guided waves. NDT&E Int. 52, 57–68 (2012)CrossRefGoogle Scholar
  21. 21.
    Yuan, W.C., Zhou, L., Yuan, F.G.: Wave reflection and transmission in composite beams containing semi-infinite delamination. J. Sound Vib. 313(3–5), 676–695 (2008)CrossRefGoogle Scholar
  22. 22.
    Ma, S., Wu, Z., Wang, Y., Liu, K.: The reflection of guided waves from simple dents in pipes. Ultrasonics 57, 190–197 (2015)CrossRefGoogle Scholar
  23. 23.
    Ihn, J.B., Chang, F.-K.: Pitch-catch active sensing methods in structural health monitoring for aircraft structures. Struct. Heal. Monit. 7(1), 5–19 (2008)CrossRefGoogle Scholar
  24. 24.
    Stoyko, D.K., Popplewell, N., Shah, A.H.: Detecting and describing a notch in a pipe using singularities. Int. J. Solids Struct. 51(15), 2729–2743 (2014)CrossRefGoogle Scholar
  25. 25.
    Li, F., Liu, Z., Sun, X., Li, H., Meng, G.: Propagation of guided waves in pressure vessel. Wave Motion 52, 216–228 (2015)CrossRefGoogle Scholar
  26. 26.
    Kim, H.W., Lee, H.J., Kim, Y.Y.: Health monitoring of axially-cracked pipes by using helically propagating shear-horizontal waves. NDT&E Int. 46(1), 115–121 (2012)CrossRefGoogle Scholar
  27. 27.
    Lee, J.-H., Lee, S.-J.: Application of laser-generated guided wave for evaluation of corrosion in carbon steel pipe. NDT&E Int. 42(3), 222–227 (2009)CrossRefGoogle Scholar
  28. 28.
    Senyurek, V.Y., Baghalian, A., Tashakori, S., McDaniel, D., Tansel, I.N.: Localization of multiple defects using the compact phased array (CPA) method. J. Sound Vib. 413, 383–394 (2018)CrossRefGoogle Scholar
  29. 29.
    Giurgiutiu, V., Bao, J.: Embedded-ultrasonics structural radar for in situ structural health monitoring of thin-wall structures. Struct. Heal. Monit. 3(2), 121–140 (2004)CrossRefGoogle Scholar
  30. 30.
    Annamdas, V.G., Radhika, M.A.: Electromechanical impedance of piezoelectric transducers for monitoring metallic and non-metallic structures: a review of wired, wireless and energy-harvesting methods. J. Intell. Mater. Syst. Struct. 24(9), 1021–1042 (2013)CrossRefGoogle Scholar
  31. 31.
    Gresil, M., Yu, L., Giurgiutiu, V., Sutton, M.: Predictive modeling of electromechanical impedance spectroscopy for composite materials. Struct. Heal. Monit. 11(6), 671–683 (2012)CrossRefGoogle Scholar
  32. 32.
    Kamas, T., Giurgiutiu, V., Lin, B.: E/M impedance modeling and experimentation for the piezoelectric wafer active sensor. Smart Mater. Struct. 24(11), 115040 (2015)CrossRefGoogle Scholar
  33. 33.
    Overly, T.G.S., et al.: Development of an extremely compact impedance-based wireless sensing device. Smart Mater. Struct. 17(6), 65011 (2008)CrossRefGoogle Scholar
  34. 34.
    Tuncay Kamas, B.L., Victor, G.: odeling and experimentation of thickness mode E/M impedance and rayleigh wave propagation for piezoelectric wafer active sensors on thick plates. In: ASME 2014 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (2014)Google Scholar
  35. 35.
    Baghalian, A., Tashakori, S., Senyurek, V.Y., Mcdaniel, D., Fekrmandi, H., Tansel, I.N.: Non-contact quantification of longitudinal and circumferential defects in pipes using the surface response to excitation (SuRE) method. Int. J. Progn. Heal. Manag. 8(2), 8 (2017)Google Scholar
  36. 36.
    Baghalian, A., Tashakori, S., Soto, J.R., Senyurek, V.Y., Tansel, I.N., Uragun, B.: Internal defect detection in hollow cylindrical structures using the surface response to excitation (SuRE) method. In: Proceedings of 8th International Conference on Recent Advances in Space Technologies, RAST 2017, pp. 523–527 (2017)Google Scholar
  37. 37.
    Tashakori, S., Baghalian, A., Cuervo, J., Senyurek, V.Y., Tansel, I.N., Uragun, B.: Inspection of the machined features created at the embedded sensor aluminum plates. In: 2017 8th International Conference on Recent Advances in Space Technologies (RAST), pp. 517–522 (2017)Google Scholar
  38. 38.
    Fekrmandi, H., et al.: A non-contact method for part-based process performance monitoring in end milling operations. Int. J. Adv. Manuf. Technol. 83(1–4), 13–20 (2016)CrossRefGoogle Scholar
  39. 39.
    Tashakori, S., et al.: Load monitoring using surface response to excitation method. In: Ralph, W.C., Singh, R., Tandon, G., Thakre, P.R., Zavattieri, P., Zhu, Y. (eds.) Mechanics of Composite and Multi-functional Materials, vol. 7. Springer, Cham (2017)Google Scholar
  40. 40.
    Baghalian, A., et al.: Implementation of the surface response to excitation method for pipes. In: Mechanics of Composite and Multi-functional Materials, pp. 261–266. Springer (2017)Google Scholar
  41. 41.
    Xu, B., Giurgiutiu, V.: Single mode tuning effects on lamb wave time reversal with piezoelectric wafer active sensors for structural health monitoring. J. Nondestruct. Eval. 26(2–4), 123–134 (2007)CrossRefGoogle Scholar
  42. 42.
    Watkins, R., Jha, R.: A modified time reversal method for Lamb wave based diagnostics of composite structures. Mech. Syst. Signal Process. 31, 345–354 (2012)CrossRefGoogle Scholar
  43. 43.
    Leutenegger, T., Dual, J.: Non-destructive testing of tubes using a time reverse numerical simulation (TRNS) method. Ultrasonics 41(10), 811–822 (2004)CrossRefGoogle Scholar
  44. 44.
    Zumpano, G., Meo, M.: Damage localization using transient non-linear elastic wave spectroscopy on composite structures 43, 217–230 (2008)Google Scholar
  45. 45.
    Van Den Abeele, K.E., Sutin, A., Carmeliet, J., Johnson, P.A.: Micro-damage diagnostics using nonlinear elastic wave spectroscopy (NEWS). NDT&E Int. 34(4), 239–248 (2001)CrossRefGoogle Scholar
  46. 46.
    Meo, M., Polimeno, U., Zumpano, G.: Detecting damage in composite material using nonlinear elastic wave spectroscopy methods. Appl. Compos. Mater. 15(3), 115–126 (2008)CrossRefGoogle Scholar
  47. 47.
    He, Q., Lin, Y.: Assessing the severity of fatigue crack using acoustics modulated by hysteretic vibration for a cantilever beam. J. Sound Vib. 370, 306–318 (2016)CrossRefGoogle Scholar
  48. 48.
    Fierro, G.P.M., Ciampa, F., Ginzburg, D., Onder, E., Meo, M.: Nonlinear ultrasound modelling and validation of fatigue damage. J. Sound Vib. 343, 121–130 (2015)CrossRefGoogle Scholar
  49. 49.
    Van Den Abeele, K.E.-A., Carmeliet, J., Ten Cate, J.A., Johnson, P.A.: Nonlinear elastic wave spectroscopy (NEWS) techniques to discern material damage, Part II: Single-mode nonlinear resonance acoustic spectroscopy. Res. Nondestruct. Eval. 12(1), 31–42 (2000)CrossRefGoogle Scholar
  50. 50.
    Ulrich, T.J., Remillieux, M., Le Bas, P.-Y., Payan, C.: Multimode nonlinear resonant ultrasound spectroscopy (NRUS): from one-dimensional to three-dimensional characterization of the hysteretic elastic nonlinearity. J. Acoust. Soc. Am. 138(3), 1886–1886 (2015)CrossRefGoogle Scholar
  51. 51.
    Payan, C., Garnier, V., Moysan, J., Johnson, P.A.: Applying nonlinear resonant ultrasound spectroscopy to improving thermal damage assessment in concrete. J. Acoust. Soc. Am. 121(4), EL125–EL130 (2007)CrossRefGoogle Scholar
  52. 52.
    Kober, J., Prevorovsky, Z.: Theoretical investigation of nonlinear ultrasonic wave modulation spectroscopy at crack interface. NDT&E Int. 61, 10–15 (2014)CrossRefGoogle Scholar
  53. 53.
    Baghalian, A., Tashakori, S., Senyurek, V.Y., Unal, M., Tansel, I.N.: Novel approaches for loose bolt detection with and without sensors using heterodyning effect. In: Proceedings of the Eleventh International Workshop on Structural Health Monitoring (2017)Google Scholar
  54. 54.
    Zhang, Z., Xu, H., Liao, Y., Su, Z., Xiao, Y.: Vibro-acoustic modulation (VAM)-inspired structural integrity monitoring and its applications to bolted composite joints. Compos. Struct. 176, 505–515 (2017)CrossRefGoogle Scholar
  55. 55.
    Tashakori, S., Baghalian, A., Senyurek, V.Y., Unal, M., McDaniel, D., Tansel, I.N.: Implementation of heterodyning effect for monitoring the health of adhesively bonded and fastened composite joints. Appl. Ocean Res. 72, 51–59 (2018)CrossRefGoogle Scholar
  56. 56.
    Farhangdoust, S., Younesian, D., Esmailzadeh, E.: Interaction of higher modes in nonlinear free vibration of stiffened rectangular plates. In: 29th Conference on Mechanical Vibration and Noise, vol. 8, p. V008T12A043 (2017)Google Scholar
  57. 57.
    Poon, T.-C.: Detection\({\vert }\)heterodyning. In: Encyclopedia of Modern Optics, pp. 201–206 (2005)Google Scholar
  58. 58.
    Sandalidis, H.G., Tsiftsis, T.A., Karagiannidis, G.K.: Optical wireless communications with heterodyne detection over turbulence channels with pointing errors. J. Light. Technol. 27(20), 4440–4445 (2009)CrossRefGoogle Scholar
  59. 59.
    Weng, C., Lin, Y., Way, W.I.: Radio-over-fiber 16-QAM, 100-km transmission at 5 Gb/s using DSB-SC transmitter and remote heterodyne detection. J. Light. Technol. 26(6), 643–653 (2008)CrossRefGoogle Scholar
  60. 60.
    Joo, K.-N., Ellis, J.D., Buice, E.S., Spronck, J.W., Schmidt, R.H.M.: High resolution heterodyne interferometer without detectable periodic nonlinearity. Opt. Express 18(2), 1159–1165 (2010)CrossRefGoogle Scholar
  61. 61.
    Amerini, F., Meo, M.: Structural health monitoring of bolted joints using linear and nonlinear acoustic/ultrasound methods. Struct. Heal. Monit. 10(6), 659–672 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Mechanical and Materials Engineering DepartmentFlorida International UniversityMiamiUSA
  2. 2.Electrical and Computer Engineering DepartmentUniversity of AlabamaTuscaloosaUSA
  3. 3.Applied Research CenterFlorida International UniversityMiamiUSA

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