Resumen
Bridges, especially cable-stayed bridges, play an important role in modern transportation systems. The safety status of bridge cables, as an important component of cable-stayed bridges, determines the health status of the entire bridge. As a non-destructive real-time detection technology, acoustic emission has the advantages of high detection efficiency and low cost. This paper focuses on the issue that a large amount of data are generated during the process of health monitoring of bridge cables. A novel acoustic emission signal segmentation algorithm is proposed with the aim to facilitate the extraction of acoustic emission signal characteristics. The proposed algorithm can save data storage space efficiently. Moreover, it can be adapted to different working conditions according to the adjustment of parameters in order to accurately screen out the target acoustic emission signal. Through the acoustic emission signal acquisition experiments of three bridges, the characteristics of the noise signal in the acquisition process are extracted. A comprehensive analysis of the signal in the time domain, frequency domain and time-frequency domain is carried out. The noise signal filtering parameter thresholds are proposed according to the analysis results.