A Multi-source Signal Separation Method Based on Non-negative Tensor Decomposition

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

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

CN109214469BActive Publication Date: 2020-06-26XI AN JIAOTONG UNIV
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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 short-time Fourier transform is adopted on the basis of the optimal window length Construct a three-dimensional time-frequency tensor distribution, and use the number of iteration steps, convergence error and kernel consistency index to select the optimal number of source signals, perform non-negative tensor decomposition according to the optimal number of source signals, and use the matrix weight obtained by the decomposition The time-frequency matrix distribution of the source signal is constructed, and then the source signal is obtained by inverse short-time 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

Patent Timeline
26 Jun 2020
Publication
CN109214469B
IPC
G06K9/62; G01H17/00
CPC
G01H17/00; G06F18/2133; G06F18/21347
Inventors
刘弹; 李光