Variational mode decomposition denoising combined with the Euclidean distance for diesel engine vibration signal

Abstract

Variational mode decomposition (VMD) is a recently introduced adaptive signal decomposition algorithm with a solid theoretical foundation and good noise robustness compared with empirical mode decomposition (EMD). There is a lot of background noise in the vibration signal of diesel engine. To solve the problem, a denoising algorithm based on VMD and Euclidean Distance is proposed. Firstly, a multi-component, non-Gauss, and noisy simulation signal is established, and decomposed into a given number K of band-limited intrinsic mode functions by VMD. Then the Euclidean distance between the probability density function of each mode and that of the simulation signal are calculated. The signal is reconstructed using the relevant modes, which are selected on the basis of noticeable similarities between the probability density function of the simulation signal and that of each mode. Finally, the vibration signals of diesel engine connecting rod bearing faults are analyzed by the proposed method. The results show that compared with other denoising algorithms, the proposed method has better denoising effect, and the fault characteristics of vibration signals of diesel engine connecting rod bearings can be effectively enhanced.

A receptive field transfer strategy via layer-aligned distillation learning for fault signal denoising

“…As their usage grows and external environmental factors take their toll, these devices are susceptible to various faults [1][2][3]. Traditional manual inspection and maintenance methods are no longer sufficient to meet the maintenance needs of large-scale and complex electromechanical equipment [4][5][6]. Therefore, advanced technical means are required to achieve automated monitoring and predictive maintenance [7].…”

Investigation of VMD denoising method based on Monte Carlo simulation: a comparative study between newly introduced autocorrelation-based method and PDF distance based method

“…Couple of studies show that VMD combined with distance measurement can successfully denoise the signal. One study uses Hausdorff distance (Ma et al, 2017), whereas, another study focuses on calculating Euclidean distance of the PDFs (Ren et al, 2017) obtained from the IMFs and that of the signal.…”