Fingerprint pattern-based nonlinear ultrasonic method for stress-loss monitoring in prestressed concrete structures

Prestressed concrete (PSC) structures are abundantly used in various kinds of civil infrastructure. However, prestress loss due to stress relaxation in tendons, as well as time-dependent creep and shrinkage, can severely affect the performance and safety of PSC structures. Therefore, a nondestructive evaluation (NDE)- based stress monitoring technique is highly desirable to address the health concerns of in-service structures in a timely manner. Nonlinear Dynamic Wavelet Fingerprint (DWFP) analysis, which is a pattern-based auto-detection tool, can quantitatively assess stress-induced nonlinearity by projecting a 3D wavelet scalogram (produced by Continuous Wavelet Transform-CWT) onto a 2D binary feature. In this study, a nonlinear ultrasonic DWFP parameter, namely, moving threshold -based slice masking on scalogram (MSMS or MS²), has been introduced. The MS² method is based on a modified contour slice operation combined with a moving threshold averaging technique. The method is found to be equally sensitive to several user-defined parameters (such as white ratio and excitation frequency). The repeatability of the experimental results is verified by applying the MS² method to different regions of the PSC beam as well. The present study establishes a feature-based nonlinear ultrasonic (NLU) parameter using DWFP analysis and carries out advanced signal processing methodologies to demonstrate the efficacy of the proposed NLU parameter for the detection of stress-state variation (in low-stress regime) in a laboratory-scaled PSC structure under different stages of prestress loss. The robust nonlinear DWFP analysis using MS² parameter offers a novel solution to several practical challenges associated with stress/damage monitoring of structures in real-time.