A multi-source signal separation method based on non-negative tensor decomposition

A non-negative tensor decomposition and source signal technology, applied in measuring devices, measuring ultrasonic/sonic/infrasonic waves, instruments, etc., can solve the problem of reducing the source signal decomposition effect, unable to adapt to different vibration signal characteristics, and unable to fully characterize the source signal vibration Features and other issues

Active Publication Date: 2019-01-15
XI AN JIAOTONG UNIV
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Problems solved by technology

[0003] The existing non-negative tensor is mainly constructed by combining two-dimensional time-frequency data with channels, while the window length in the time-frequency transformation is selected based on experience, which cannot adapt to different vibration signal characteris

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  • A multi-source signal separation method based on non-negative tensor decomposition
  • A multi-source signal separation method based on non-negative tensor decomposition
  • A multi-source signal separation method based on non-negative tensor decomposition

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[0031] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0032] refer to figure 1 , a multi-source signal separation method based on non-negative tensor decomposition, including the following steps:

[0033] Step 1: Generate four typical analog signals, namely, FM-AM signal, AM signal, AM-FM signal and periodic impact signal. Among them, the FM-AM signal simulates the meshing vibration of gears, and the carrier frequency and modulation frequency are respectively 750Hz and 25Hz. The carrier frequency and modulation frequency of the AM signal are 400Hz and 10Hz respectively, the carrier frequency and modulation frequency of the AMFM signal are 210Hz and 60Hz respectively, the oscillation frequency of the periodic impact signal is 3000Hz, and 2000 data points of each signal are taken. Get the multi-source vibration signal A 2000×4 , whose waveform and spectrum refer to figure 2 and image 3 shown;

[003...

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Abstract

A multi-source signal separation method based on non-negative tensor decomposition For multi-source vibration signal data, the optimal window length is determined based on the average information entropy method, and then the three-dimensional time-frequency tensor distribution is constructed by adopting short-time Fourier transform on the basis of the optimal window length. The optimal number of source signals is selected by using iterative steps, convergence error and kernel consistency index, and the non-negative tensor decomposition is carried out according to the optimal number of source signals. The time-frequency matrix distribution of source signals is reconstructed by using the matrix obtained from the decomposition, and then the source signals are obtained by short-time inverse Fourier transform. The invention can accurately extract the source signal from the mixed signal.

Description

technical field [0001] The invention belongs to the technical field of equipment detection and fault diagnosis, and in particular relates to a multi-source signal separation method based on non-negative tensor decomposition. Background technique [0002] With the continuous improvement of the complexity of mechanical equipment, the collected vibration signals are often a mixture of multiple vibration excitation source components, and under the interference of noise, it is difficult to identify the characteristic components of the faulty components, which affects the identification of faults. Therefore, how to separate the main characteristic components from the vibration signal is one of the urgent problems in fault diagnosis. As a new direction in the field of modern signal processing, the signal source separation technology separates the source signal from the obtained mixed signal when the number, location and transmission channel of the source signal are unknown. The co...

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Application Information

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IPC IPC(8): G06K9/62G01H17/00
CPCG01H17/00G06F18/2133G06F18/21347
Inventor 刘弹李光梁霖刘飞王宝栗茂林
Owner XI AN JIAOTONG UNIV
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