The top cover bolts of hydropower turbines are crucial components that connect the top cover to the seat ring. Their safety status is of paramount importance for the safe operation of hydroelectric power stations. To effectively monitor the cracking and damage of top cover bolts, this paper proposes a denoising method for ultrasonic detection-based crack detection echo signals of hydropower turbine cover bolts. This method combines the Adaptive Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and wavelet denoising to achieve denoising of the crack detection echo signals obtained from ultrasonic detection. The proposed CEEMDAN combined with wavelet denoising method is applied to process simulated signals, and the results demonstrate that the algorithm proposed in the paper yields good SNR and denoising performance. Finally, the proposed algorithm is employed to process actual defect data, and similarly, promising experimental results are obtained.