In this article, bolt group looseness monitoring in a clamping support structure model, which is under environmental random excitation, is experimentally investigated. The bolt group has 12 bolts, providing an essential clamping force to fix cargo during transportation. Seven kinds of bolt group looseness degree developed gradually are simulated in experiment. From an economic point of view, vibration transducer of accelerometer is used for monitoring. Time series analysis of Auto-Regressive with eXogenous model with input known and Auto-Regressive-Auto-Regressive with eXogenous model with input unknown are constructed, and the statistical indices of the model residual error are defined as the damage characteristic parameter indicating the bolt group looseness degree. The experimental analysis shows the effectiveness of the proposed method in monitoring the bolt group looseness at early stage, while the variation of structural resonance frequency can only be used to monitor large bolt group looseness degree. The experimental analysis also shows that under a stationary, broadband random excitation, the Auto-Regressive-Auto-Regressive with eXogenous model has the same bolt group looseness monitoring capability with the Auto-Regressive with eXogenous model.

Bolted joints are widely used in industrial applications and joint failure can cause a disastrous accident if loosening happens. Bolt loosening detection can be made by regular manual inspection or by using sensors based on different physical principles, such as acoustoelastic effect, piezoelectric active sensing, and electromechanical impedance. Compared with the above methods, vibration based bolt looseness monitoring using accelerometers is appealing for its economy and convenience for measurement. In this paper, cargo bolts looseness monitoring under random excitation is studied based on vibration transmissibility, which overcomes the drawback of commonly used vibration methods in finding local bolt looseness. Vibration transmissibility analysis only uses two vibration transducers to monitor bolt group looseness, where the vibration signal below the cargo bolts is used as the “input” and the other one above the cargo bolts is used as the “output.” There are 12 bolts in the cargo bolts studied in this paper, providing an essential clamping force to fix cargo during transportation. Six kinds of bolt group looseness with an increasing degree are simulated in the experiment. The experimental analysis shows that variation of the spectral moment can be used to monitor the global variation of the torque wrench exerted on the cargo bolts. The early stage of the bolt group looseness is that some one or two bolts begin to loose; however, the spectrum moment factor is insensitive to the local bolt looseness in the bolt group. To address this issue, the eigensystem realization algorithm (ERA) based on random input and output is utilized to find the subtle eigenvalue variation of the system matrix, which is neglected by the frequency transmissibility function. The experimental results show the effectiveness of the proposed method for detecting local bolt looseness.

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