Effective Denoising of Firing Shock Force on Shoulder by Morphological Wavelet

Wavelet transform is one of the most desirable tools for depressing noise. However, the traditional linear wavelets are not always suitable for any real world signals with strong background noises. In this work, we present a new morphological wavelet, named averaged dilation-erosion morphological wavelet (ADEMW), for depressing the noise in signals of firing shock force on the shoulder. Simulated signals with different SNRs are generated to evaluate and compare the proposed new wavelet scheme with the traditional linear wavelet and another two morphological wavelets presented in literature. Experimental results reveal that the presented ADEMW gives the most promising noise suppression performance. Then, the ADEMW is employed to process the real-world signals acquired from a firing shock force testing system. Processing results demonstrate that the ADEMW also outperforms another three wavelets obviously for depressing the strong background noise in the signals of firing shock force on the shoulder. The main impulsive components in the firing shock force can be clearly detected for analyzing the impacts on shoulder during the shooting process. The presented ADEMW scheme has provided a novel desirable tool for analyzing the complicated signals with strong noise.

from ! Human Diseases via Alexandros G.Sfakianakis on Inoreader https://ift.tt/2SF7Vma