Abstract: When steel strands are subjected to long-term loads, they are prone to various damages such as wear, corrosion, and wire breakage, and monitoring their damage is particularly important. Acoustic emission detection technology has significant advantages in steel strand damage monitoring due to its dynamic detection characteristics. This article first conducts tensile loading tests on steel strands, monitors the entire damage process of steel strands through acoustic emission, and collects acoustic emission signals during the initiation, propagation, and fracture stages of tensile cracks. Then, wavelet packet decomposition is used to process the acoustic emission signals of different damage stages, and the spectral characteristics and energy distribution maps of these stages are calculated. Finally, by comparing and analyzing the spectral characteristics and energy distribution maps of acoustic emission signals at different damage stages, the signal characteristic information of different damage stages can be identified, which can achieve a quantitative evaluation of the damage process of steel strands. This method can also be applied to the quantitative evaluation of damage processes in other metal materials.