Detection of rupture inside rubber bearings using active sensing method

Abstract

Rubber bearings are key components of base-isolated structures; therefore, it is important to monitor their damage states. This study investigates the effectiveness of the active sensing method for detecting rubber rupture inside rubber bearings. The mechanism of wave propagation demonstrates the potential of the active sensing method for rubber rupture damage detection. Detection tests were performed on a full-scale rubber bearing, and a swept signal from 1 kHz to 100 kHz was used as the detection signal. A linear discriminant analysis (LDA) method based on the wavelet-packet energy spectrum is proposed to detect the rubber rupture damage. The LDA method can comprehensively consider the influences of axial pressure and shear deformation, displaying a 98% accuracy for rubber rupture damage detection. In addition, detection tests were performed on a scaled rubber specimen under different damage states. The results show that the LDA method has excellent performance when detecting the degree of rupture damage, with an accuracy of 95.8%.