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Reference signal constraint-based mechanical characteristic acoustic signal frequency-domain semi-blind extraction method

A reference signal and extraction method technology, which is applied in the field of mechanical equipment operation and maintenance, can solve the problems of weakening background noise interference, etc., and achieve the effect of weakening background noise interference, effective and accurate extraction, and simple test methods

Active Publication Date: 2015-04-29
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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  • Reference signal constraint-based mechanical characteristic acoustic signal frequency-domain semi-blind extraction method
  • Reference signal constraint-based mechanical characteristic acoustic signal frequency-domain semi-blind extraction method
  • Reference signal constraint-based mechanical characteristic acoustic signal frequency-domain semi-blind extraction method

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Embodiment 1

[0036] Embodiment 1: as Figure 1-8 As shown, a frequency-domain semi-blind extraction method of mechanical characteristic sound signals based on reference signal constraints, the specific steps of the frequency-domain semi-blind extraction method of mechanical characteristic sound signals based on reference signal constraints are as follows:

[0037] Step1. Initialize the structural parameters of the parts, calculate the characteristic frequency according to the structural parameters, construct the reference signal r(t), and perform centralization and whitening processing on the sound observation signal x(t) received by the microphone to remove the correlation between signals;

[0038] Step2. Use the improved multi-scale morphological filter to suppress the noise of the observation signal x(t), which is used to weaken the background noise interference to the greatest extent, and obtain the filtered time domain observation signal

[0039] Step3, use windowed STFT to observe ...

Embodiment 2

[0054] Embodiment 2: as Figure 1-8 As shown, a frequency-domain semi-blind extraction method of mechanical characteristic acoustic signals based on reference signal constraints, this embodiment is the same as Embodiment 1, the difference is that this embodiment uses the acoustic extraction of rolling bearing faults in a rotating test bench in the actual sound field The experiment is an implementation example:

[0055] figure 1 Indicates 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 transmission shaft 4, the faulty bearing 6 is installed in the bearing seat 5, and is driven by the transmission shaft 4 to rotate. Microphone I 3, microphone II 7, and microphone III 8 are all 1m above the ground, and microphone I 3 and microphone II 7 are at a 90° angle to each other. Microphone III 8 is placed vertically on test bench 2. Microphone I 3, microphone II 7, and...

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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 failure 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 sound signal generation, and sound signal is the continuation of vibration signal propagation, and the two are mutually unified whole. When a mechanical system such as a rolling bearing or a gear fails, its characteristic signal often has an obvious impact component, and at the same time the acoustic characteristics will also change, thus containing equipment status information. Acoustic signal test has many advantages such as non-contact measurement, simple test method, online test and no influence of attachments, etc. It i...

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Application Information

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Patent Type & Authority Applications(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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