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Rolling bearing fault detection method based on DS adaptive spectrum reconstruction

A rolling bearing and fault detection technology, applied in the testing of machine/structural components, testing of mechanical components, measuring devices, etc., can solve problems such as low recognition accuracy and bearing failure mode judgment

Active Publication Date: 2019-06-25
SOUTHEAST UNIV
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Problems solved by technology

However, the recognition accuracy of a single eigenvector is low, and it is difficult to accurately judge the bearing fault mode

Method used

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  • Rolling bearing fault detection method based on DS adaptive spectrum reconstruction
  • Rolling bearing fault detection method based on DS adaptive spectrum reconstruction
  • Rolling bearing fault detection method based on DS adaptive spectrum reconstruction

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Embodiment Construction

[0066] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0067] Preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0068] Such as figure 1 As shown, the purpose of the present invention is to provide a rolling bearing fault detection method based on DS adaptive spectrum reconstruction, and the specific extraction process of the feature vector includes:

[0069] Step 101: arranging the acceleration sensor to collect the fault vibration signal x(t) of the rolling bearing;

[0070] Step 102: Carry out Fourier transform to x(t), obtain its frequency band X(f), and cut X(f) into the minimum frequency band subset X(f)={X 1 ,X 2 ,...,X K ,...,X M}, K∈[1,M],

[0071] Extract six time-frequency domain indicators such as frequency band subset kurtosis, impulse factor, sparse factor, margin factor, kurtosis coefficient and Hilbert envel...

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Abstract

The invention discloses a rolling bearing fault detection method based on DS adaptive spectrum reconstruction. The method comprises the steps of: acquiring a vibration time signal x(t) as a source signal; defining the Fourier transform of the bearing vibration time signal x(t) as X (f), and subdividing the X (f) into a minimum spectrum subset set; creating an evaluation subset function by using animproved DS evidence theory; reconstructing the spectrum by using a bottom-up method and by using the evaluation function as a feature index in order to search for the optimal resonance band; performing the inverse Fourier transform on the optimal resonance band, and then performing Hilbert transform; performing envelope spectrum analysis; identifying whether the fault feature has an obvious peakaccording to the envelope spectrum; if not, determining that the bearing operates normally; and if so, determining that the bearing has a fault and needs to be stopped. The rolling bearing fault detection method based on DS adaptive spectrum reconstruction is a feature vector extraction method for timely and accurately realizing the rolling bearing fault pattern recognition and state monitoring.

Description

technical field [0001] The invention relates to a rolling bearing fault feature extraction and pattern recognition method, belonging to the technical field of mechanical fault diagnosis and signal processing. Background technique [0002] As a key component of rotating machinery, rolling bearings are widely used in rotating machinery, and faults occurring in bearings must be detected as early as possible to avoid fatal mechanical failures that may cause production losses and casualties. According to the way to obtain effective fault information, the commonly used rolling bearing fault diagnosis methods mainly include: temperature detection method, oil liquid detection method, acoustic emission method, oil film resistance diagnosis method, optical fiber detection diagnosis method, gap measurement diagnosis method and vibration analysis method Wait. Among them, the vibration analysis method is one of the most commonly used methods for bearing fault diagnosis, which can effect...

Claims

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Application Information

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IPC IPC(8): G01M13/045
Inventor 胡建中徐亚东许飞云贾民平彭英
Owner SOUTHEAST UNIV
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