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.


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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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