Guided wave-based cable tension estimation in multi-wire steel strands using principal component analysis

In-service monitoring of the stress state of steel strands or cables is essential for estimating the loading capacity of the entire structure. The traditional wave velocity–based method may not be sensitive to changes in cable tension. To address this issue, a principal component analysis (PCA)-based method was presented in this study, using longitudinal guided waves generated by a pair of magnetostrictive transducers. First, semi-analytical finite element analysis was performed considering the effect of the external load to investigate the changes in wave velocity under various guided wave modes in the lower frequency range. Then, experimental studies were conducted on a seven-wire steel strand under various cable tension levels. The directarrival wave packets of the reference signals were used to construct the PCA model. Score values corresponding to the principal components (PCs) of the reference signals were calculated, and the PCs whose scores were closely related to the tension variations were determined. A linear regression curve for the scores and cable tensions was constructed and used to determine the cable tensions for the test signals. The results show that the proposed method can accurately estimate cable tension and performs better than the notch frequency-based method.