Abstract: To accurately identify the fault data of wire rope defects and eliminate the noise in the measured signal，this paper used a combined noise reduction model based on the Bayesian optimization-wavelet transform-variational moda decomposition （BO-WTVMD）for noise reduction. Firstly，the wavelet transform（WT）was used to process the original signal. Then，the variational mode decomposition（VMD）was used for the modal decomposition of the signal processed by the wavelet transform. The correlation coefficient between the decomposed mode and the original signal was calculated to complete the signal mode selection and reconstruction. Finally，the Bayesian optimization（BO）algorithm was used to search for parameters K and the value α in the VMD algorithm，avoiding the impact of sequence decomposition and prediction accuracy，in order to find the optimal hyperparameter combination. Furthermore，in simulation trials and real data，the SNR and RMSE of the BO-WT-VMD，WT，and VDM algorithms are calculated respectively，which were（17. 340 3，0. 101 0），（15. 617 0，0. 123 2），（15. 649 2，0. 122 7），indicating that the algorithm proposed in this paper can effectively eliminate signal noise.

Key words: magnetic leakage detection, wavelet transform, variational mode decomposition, Bayesian optimization, wire rope, noise reduction