Bolt early looseness monitoring using modified vibro-acoustic modulation by time-reversal


Unlike concrete structures, steel structures demand constant monitoring as they are more susceptible to deterioration. In particular, bolted connections are a concern that cannot be ignored reason being they are more vulnerable to cyclic loading, mechanical attacks and chemical corrosion- among others unfavorable conditions that can induce severe damages, such as: the relaxation of bolt pre-load. Thus, many researchers have carried out investigations on pre-load monitoring/inspection of bolted joints to enable assess their sustainability; where structural health monitoring methods have proven their effectiveness. A thorough review of existing literature shows that majority of the demerits that hamper various SHM approaches (such as: the electro-mechanical impedance method) have been identified. Focus has thus shifted to the more promising impact modulation and the Vibro-acoustic Modulation (VAM), which are two major implementations of the acoustic wave-modulation method. Unfortunately, the VAM approach still suffers from various deficiencies that render it impractical. Proposition to improve this approach by the Time Reversal method have also been hypothesized in the past.

Therefore, it is crystal clear that the traditional VAM approach ought to be improved so as to enhance its performance and practicality. Unfortunately, papers about modification of the VAM based monitoring method using TR method are limited. To address this, researchers from the Smart Materials and Structures Laboratory, Department of Mechanical Engineering at University of Houston: Furui Wang (PhD candidate) and Professor Gangbing Song developed a modified VAM(MVAM) in a bid to circumvent inherent shortfalls that inhibit VAM’s practical implementation. They aspired that their modifications could help improve the sensitivity of the VAM technique. Their work is currently published in the research journal, Mechanical Systems and Signal Processing.

In brief, the authors started implementing their modification by replacing the shaker used in the traditional VAM with a piezoceramic transducer to improve its practicality. In addition, instead of sine waves, the two colleagues adopted linear swept sine signals for both low frequency pump vibration and high-frequency probe wave. Subsequently, the time reversal (TR) method was applied to overcome problems including signal energy dissipation and low signal-to-noise ratio in traditional VAM. Moreover, by combining the noise-assisted multivariate empirical mode decomposition method and the multiscale multivariate sample entropy (MMSE) algorithm, they developed a novel damage index to achieve the quantitative identification of bolt early loosening. Finally, multiple repeated experiments were conducted to verify advantage of the proposed method.

In summary, Furui Wang and Professor Gangbing Song study presented a modified and improved VAM-based (MVAM) method to monitor bolt early loosening. When compared to prior available systems, their study demonstrated the feasibility of replacing shaker, which is often inappropriate in practice, by piezoceramic transducer, to provide low frequency pumping vibration wave in the VAM-based method for bolt looseness monitoring. More so, to further strengthen the damage-related nonlinearity performance in the VAM-based method, the TR method was employed to process the modulated signals and obtain focused signals.

Simplicity and practicability are two major advantages of the proposed method. To this note, the proposed MVAM method was seen to be more practical and had higher accuracy than the traditional VAM-based method, thus rendering a potential for online health monitoring of other structures, such as the composite laminate.

About the author

Furui Wang is currently a Ph.D. student of Mechanical Engineering at University of Houston. He received his B.S. degree and M.S. degree from the Department of Mechanical Engineering at Dalian university of Technology in 2014 and 2017, respectively. He has published over 10 peer-reviewed journal articles. His research interest focuses on the structural health monitoring.


About the author

Gangbing Song is the founding Director of the Smart Materials and Structures Laboratory and a Professor of Mechanical Engineering, Civil and Environmental Engineering, and Electrical & Computer Engineering at the University of Houston. Dr. Song is a recipient of the NSF CAREER award in 2001. Dr. Song received his Ph.D. and MS degrees from the Department of Mechanical Engineering at Columbia University in the City of New York in 1995 and 1991, respectively. Dr. Song received his B.S. degree in 1989 from Zhejiang University, P.R. China. He has expertise in smart materials and structures, structural vibration control, piezoceramics, ultrasonic transducers, structural health monitoring and damage detection. He has developed two new courses in smart materials and published more than 400 papers, including 196 peer reviewed journal articles.


Furui Wang, Gangbing Song. Bolt early looseness monitoring using modified vibro-acoustic modulation by time-reversal. Mechanical Systems and Signal Processing, volume 130 (2019) page 349–360.

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