A Novel Mechanical Fault Diagnosis Scheme Based on the Convex 1-D Second-Order Total Variation Denoising Algorithm

Abstract

Convex 1-D first-order total variation (TV) denoising is an effective method for eliminating signal noise, which can be defined as convex optimization consisting of a quadratic data fidelity term and a non-convex regularization term. It not only ensures strict convex for optimization problems, but also improves the sparseness of the total variation term by introducing the non-convex penalty function. The convex 1-D first-order total variation denoising method has greater superiority in recovering signals with flat regions. However, it often produces undesirable staircase artifacts. Moreover, actual denoising efficacy largely depends on the selection of the regularization parameter, which is utilized to adjust the weights between the fidelity term and total variation term. Using this, algorithms based on second-order total variation regularization and regularization parameter optimization selection are proposed in this paper. The parameter selection index is determined by the permutation entropy and cross-correlation coefficient to avoid the interference by human experience. This yields the convex 1-D second-order total variation denoising method based on the non-convex framework. Comparing with traditional wavelet denoising and first-order total variation denoising, the validity of the proposed method is verified by analyzing the numerical simulation signal and the vibration signal of fault bearing in practice.

Denoising and Feature Extraction Algorithms Using NPE Combined with VMD and Their Applications in Ship-Radiated Noise

“…In addition, the results of SNRs for different variances of Gaussian white noise and different denoising algorithms are shown in Table 9. The results of the other three denoising algorithms can be seen in [32]. As shown in Table 9, the proposed denoising algorithm has high SNRs for different variances of Gaussian white noise.…”

“…In research [32], the convex 1-D 2-order total variation denoising algorithm for vibration signal is proposed. In order to validate the effectiveness of the proposed denoising algorithm in this paper, the same simulation experiments are carried out.…”

Experimental Damage Identification of a Model Reticulated Shell

“…In the aerospace industry, several application areas have garnered significant interests. Rapid inspection of satellite structures for pre-launch verification has been achieved using the SHM technologies [20][21][22].…”

Research on the Blind Source Separation Method Based on Regenerated Phase-Shifted Sinusoid-Assisted EMD and Its Application in Diagnosing Rolling-Bearing Faults

“…There is no doubt that fault diagnosis technology, based on vibration signal processing, is critical for monitoring the health of key structures or equipment [1][2][3][4][5]. Generally, different sensors are utilized to obtain mechanical vibration information, from which the features of the running state are characterized [6][7][8].…”