An NCFA-Based Notch Frequency Feature Extraction Method for Guided Waves and Its Application in Steel Strand Tension Detection

Abstract

The rapid and accurate identification of steel strand tension is critical in ensuring the safety of load-bearing structures and structural members, such as bridge cables. Ultrasonic-guided waves (UGWs) have a reasonable propagation distance and reliable detection efficiency, and they are promising for ensuring the safe monitoring of long-distance structures. The L(0,1) waveguide mode of the steel strand has a missing frequency band, and the center frequency of the missing band (notch frequency) positively correlates with axial tension. Based on this feature, a method for detecting the axial tension of steel strands was developed in this study based on notch frequency analysis. First, normalized complex frequency analysis (NCFA) was applied to investigate the trailing and amplitude attenuation of UGW signals generated by the missing frequency band to obtain the characteristic parameters related to the notch frequency under different tensions. Subsequently, a multiple nonlinear regression model was developed to predict the strand tension using the parameter samples. The experimental results showed that the proposed method can overcome the resolution limitation when using only frequency as the parameter. Moreover, the proposed method had an improved parameter and noise robustness. The average error of the prediction results was 1.843 kN within a loading force range of 50–150 kN, demonstrating the potential for practical engineering applications.