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A frequency-domain semi-blind extraction method of mechanical characteristic acoustic signals based on reference signal constraints

A reference signal and blind extraction technology, which is applied in the testing of mechanical components, testing of machine/structural components, and measurement of ultrasonic/sonic/infrasonic waves, etc., can solve problems such as weakening background noise interference, and achieve effective and accurate reduction of background noise interference. The effect of simple extraction and testing methods

Active Publication Date: 2017-04-12
KUNMING UNIV OF SCI & TECH
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Problems solved by technology

[0005] The frequency-domain semi-blind extraction method of mechanical characteristic acoustic signals based on reference signal constraints in the present invention is realized in the following way: firstly, based on the dynamic particle swarm optimization algorithm with strong global optimization ability, a multi-scale morphological filter for fault signal characteristics is constructed to minimize the Background noise interference; combined with the structural parameters of mechanical parts to construct reference signals, and then perform blind separation of complex components segment by segment through the unit reference signal constrained semi-blind extraction method; then use the improved KL distance between complex components to solve the order uncertainty problem, and finally realize mechanical Extract and separate the fault characteristic signal, and then analyze the envelope demodulation spectrum of the separated signal

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  • A frequency-domain semi-blind extraction method of mechanical characteristic acoustic signals based on reference signal constraints
  • A frequency-domain semi-blind extraction method of mechanical characteristic acoustic signals based on reference signal constraints
  • A frequency-domain semi-blind extraction method of mechanical characteristic acoustic signals based on reference signal constraints

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Embodiment 1

[0035] Example 1: Such as Figure 1-8 As shown, a mechanical feature acoustic signal frequency domain semi-blind extraction method based on reference signal constraints, the specific steps of the reference signal constraint-based mechanical feature acoustic signal frequency domain semi-blind extraction method are as follows:

[0036] Step1. Initialize the structural parameters of the components, calculate the characteristic frequency according to the structural parameters, construct the reference signal r(t), and perform centralization and whitening of the sound observation signal x(t) received by the microphone to remove the correlation between the signals;

[0037] Step2: Use the improved multi-scale morphological filter to suppress the noise of the observation signal x(t), which is used to minimize the background noise interference to obtain the filtered time domain observation signal

[0038] Step3, use windowed STFT to observe the signal in the time domain And the reference si...

Embodiment 2

[0052] Example 2: Such as Figure 1-8 As shown, a method for semi-blind extraction of mechanical characteristic acoustic signals in the frequency domain based on reference signal constraints. This embodiment is the same as Embodiment 1, except that this embodiment uses the acoustic extraction of a rolling bearing fault in a rotating test rig in the actual sound field. The experiment is an implementation example:

[0053] figure 1 Shows the positional relationship between the two microphones and the test bench. The control box 1 is connected to the motor 9 through wires, the motor 9 is connected to the drive shaft 4, and the faulty bearing 6 is installed in the bearing housing 5 and driven by the drive shaft 4 to rotate. The height of microphone I3, microphone II 7, and microphone III 8 is 1m from the ground. Microphone I 3 and microphone II 7 are at 90° to each other, microphone III 8 is placed vertically on test bench 2, microphone I 3, microphone II 7, and microphone III The ...

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Abstract

The invention relates to a reference signal constraint-based mechanical characteristic acoustic signal frequency-domain semi-blind extraction method, and belongs to the technical field of operation maintenance of mechanical equipment. The method comprises the following steps: constructing a multi-scale morphology filter for a failure signal characteristic on the basis of a dynamic particle swarm algorithm with higher global optimization capability, and maximally weakening background noise interference; constructing a reference signal in combination with structural parameters of a mechanical part, and further performing complex component blind separation band by band by virtue of a unit reference signal constraint semi-blind extraction method; solving order uncertainty problems to obtain a separated and restored source signal to finally realize the extraction and separation of the mechanical failure characteristic signal by virtue of the improved KL distance between complex components. Different from vibration monitoring requiring the mounting of a sensor on the surface of mechanical equipment, acoustic monitoring only requires the placement of 1 to 2 microphones around the equipment, and then the failure characteristic signal can be extracted from a picked up mechanical acoustic signal for further failure source positioning.

Description

Technical field [0001] The invention relates to a frequency domain semi-blind extraction method of mechanical characteristic acoustic signals based on reference signal constraints, which separates and extracts mechanical fault characteristic information by constructing reference signals, and belongs to the technical field of mechanical equipment operation and maintenance. Background technique [0002] In mechanical equipment, vibration is the source of acoustic signals, and acoustic signals are the continuation of the propagation of vibration signals. The two are a unified whole. When mechanical systems such as rolling bearings or gears fail, their characteristic signals often have obvious impact components, and at the same time the acoustic characteristics will also change, which contains equipment status information. Acoustic signal test has many advantages such as non-contact measurement, simple test method, online test and no attachments, etc. It is especially suitable for in...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01H17/00G01M13/00
Inventor 潘楠刘畅伍星刘凤
Owner KUNMING UNIV OF SCI & TECH
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