Single source point detection-based underdetermined blind source separation method

Abstract

The invention discloses a single source point detection-based underdetermined blind source separation method. The method comprises the steps of firstly performing short-time Fourier transform on to-be-analyzed observation signals to obtain corresponding time frequency domain complex matrixes; secondly vectorizing and normalizing the time frequency complex matrix of each observation signal; thirdlydetecting out all equal column vectors in the normalized time frequency matrix by utilizing cosine included angle criteria of the vectors, wherein the extracted column vectors are namely single source points; fourthly performing hierarchical clustering on the extracted single source points to obtain a clustering center, thereby realizing estimation of a mixed matrix, wherein the center of each type corresponds to a column of the mixed matrix; and finally by utilizing the estimated mixed matrix, realizing time frequency estimation of all sources at all time frequency points through a least square method, and obtaining time domain forms of the sources through time domain inverse transform. According to the method disclosed by the invention, a linear relationship among different single source points is considered, and the detection of the single source points can be realized only by judging whether the vectors are same or not, so that efficient and high-precision estimation of the mixedmatrix and source signals can be realized under the underdetermined condition.

Description

technical field [0001] The invention relates to the field of mechanical vibration signal and acoustic radiation signal processing, in particular to an underdetermined blind source separation method based on single source point detection. Background technique [0002] Vibration and noise have an important impact on the performance and safety of mechanical systems. It is very important to find the source of vibration and noise and take measures to reduce its impact. Vibration signals contain a wealth of information, so analyzing the vibration signals of mechanical systems is a common means of reducing vibration and noise. However, due to the gradual increase in size, complexity and precision of the mechanical system, it often contains multiple vibration sources, and the signal collected by the sensor is the superposition of vibration signals caused by multiple vibration sources at the collection point. Therefore, the signal of interest is often submerged by other vibration si...

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Problems solved by technology

However, when the number of single-source points is small or the noise is large, sparse coding takes a long time, and the efficiency is difficult to guarantee.

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