Structural health monitoring (SHM) technology for surveillance and evaluation of existing and newly built long-span bridges has been widely developed, and the significance of the technique has been recognized by many administrative authorities. The paper reviews the recent progress of the SHM technology that has been applied to long-span bridges. The deployment of a SHM system is introduced. Subsequently, the data analysis and condition assessment including techniques on modal identification, methods on signal processing, and damage identification were reviewed and summarized. A case study about a SHM system of a long-span arch bridge (the Jiubao bridge in China) was systematically incorporated in each part to advance our understanding of deployment and investigation of a SHM system for long-span arch bridges. The applications of SHM systems of long-span arch bridge were also introduced. From the illustrations, the challenges and future trends for development a SHM system were concluded.
Accurate identification of tension in multiwire strands is a key issue to ensure structural safety and durability of prestressed concrete structures, cable-stayed bridges, and hoist elevators. This paper proposes a method to identify strand tensions based on scale energy entropy spectra of ultrasonic guided waves (UGWs). A numerical method was first developed to simulate UGW propagation in a seven-wire strand, employing the wavelet transform to extract UGW time-frequency energy distributions for different loadings. Mode separation and frequency band loss of (0, 1) were then found for increasing tension, and UGW scale energy entropy spectra were extracted to establish a tension identification index. A good linear relationship was found between the proposed identification index and tensile force, and effects of propagation distance and propagation path were analyzed. Finally, UGWs propagation was examined experimentally for a long seven-wire strand to investigate attenuation and long distance propagation. Numerical and experimental results verified that the proposed method not only can effectively identify strand tensions but can also adapt to long distance tests for practical engineering.
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