Underdetermined blind source separation method, system and device based on minimization and maximization

Abstract

The invention discloses an underdetermined blind source separation method, system and device based on minimization and maximization. The method comprises the steps of converting a time-domain instantaneous mixed signal into a frequency-domain instantaneous mixed signal on each frequency band through short-time Fourier transform, extracting a real part vector and an imaginary part vector of a complex value hybrid matrix based on the sparsity of a source signal, performing single source point judgment and extraction through cosine angles, performing normalization and modular arithmetic on singlesource points, and achieving hybrid matrix estimation through hierarchical clustering of the single source points; and converting a source signal recovery problem into an l1 norm optimization problemby utilizing the hybrid matrix and the sparsity hypothesis of the source signal, and converting the source signal of the time-frequency domain back to the time domain by adopting short-time inverse Fourier transform after the source signal is recovered in the time-frequency domain so as to realize underdetermined blind source separation. The non-convex penalty function is constructed, so that theoptimization of the objective function is close to the optimization of the l0 norm, the systematic underestimation of the conventional l1 norm regularization and the source signal recovered accordingto the sparsity hypothesis are avoided, and the convexity of the objective function is ensured.

Description

technical field [0001] The invention belongs to the field of mechanical vibration and noise signal processing, and in particular relates to an underdetermined blind source separation method, system and device based on minimization and maximization. Background technique [0002] There are many high-end equipment parts such as gas turbines, and the vibration caused by the unbalanced movement of the rotor, misalignment of the rotor, and loose clamping accelerates the wear of its connecting parts, which seriously affects the performance and life of the equipment, while the radiation noise generated by the vibration reduces the concealment of military equipment. It seriously affects the combat capability of the army. Vibration and noise reduction measures for high-end equipment such as gas turbines can effectively suppress vibration and noise. High-end equipment such as gas turbines has the characteristics of complex and precise structures, numerous vibration and noise sources, a...

AI Technical Summary

Problems solved by technology

At present, the underdetermined blind source separation method mainly extracts single-source points by clustering signals in the transform domain and estimates the mixing matrix, and then uses the mixing matrix to adopt l 0 Norm optimization recovers the source signal, but l 0 Discontinuity leads to a large error in the recovered source signal, which cannot effectively separate the internal mechanical mixed signals of high-end equipment such as shipboard gas turbines

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