A Cross Electro-Mechanical Impedance Method Using a Distributed Piezoelectric Array for Bolt Loosening Detection

As a critical connection method in modern engineering structures, the health condition of bolted joints significantly influences overall structural safety and durability. Although the drive-point electro-mechanical impedance (EMI) technique has proven effective for bolt loosening detection, it suffers from certain shortcomings, especially for the quantitative identification of bolt loosening. This study proposed a novel bolt loosening detection approach based on the cross electro-mechanical impedance (EMI) technique through experimental measurements and numerical simulations. First, a distributed piezoelectric array was used to conduct a comparative study on bar-type specimens under three different bolt loosening states. Both drive-point admittance and cross-admittance signals were measured before and after bolt loosening. Qualitative assessment of bolt loosening was carried out by analyzing variations in conductance curves under different conditions, supplemented by quantitative evaluation using the normalized root mean square deviation (RMSD) index. The results demonstrated that cross-admittance signals exhibit superior sensitivity over drive-point admittance, allowing more accurate identification of both the severity and location of bolt loosening. Subsequently, an experiment was conducted on a rectangular specimen by applying cross EMI under various bolt loosening states. The results confirmed the effectiveness of the proposed detection technique. Finally, finite element models were established to simulate bolt loosening. The simulations validated the capability of the numerical cross conductance signals to accurately detect different loosening states. The present investigations showed that the cross-admittance technique not only demonstrates superior capability in bolt loosening detection over the conventional drive-point method but also significantly expands the technical means for EMI-based structural health monitoring with improved detection performance.