Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Fault diagnosis method for rolling bearings based on enhanced modulation bispectral analysis

A rolling bearing and fault diagnosis technology, applied in the testing of mechanical components, testing of machine/structural components, instruments, etc., can solve the problems of high-order spectrum interference of signals, fault feature extraction and analysis of adverse effects, etc., to achieve the effect of superior performance

Active Publication Date: 2020-12-11
HEBEI UNIV OF TECH
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, MSB can completely suppress Gaussian noise in theory, and is powerless against non-Gaussian noise, and the existence of these non-Gaussian noises will interfere with the high-order spectrum of the signal, thus adversely affecting the extraction and analysis of fault features

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fault diagnosis method for rolling bearings based on enhanced modulation bispectral analysis
  • Fault diagnosis method for rolling bearings based on enhanced modulation bispectral analysis
  • Fault diagnosis method for rolling bearings based on enhanced modulation bispectral analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0040] This embodiment provides a rolling bearing fault diagnosis method based on enhanced modulation bispectral analysis:

[0041] Step 1: Measure the vibration signal of the inner ring of the rolling bearing through the vibration sensor. The sampling frequency of the vibration signal is 96kHz, the sampling length is 2880000 points, and the fault frequency of the outer ring of the bearing is 65.17Hz. The waveform diagram and frequency domain diagram of the vibration signal are as follows: figure 1 , figure 2 As shown, it can be seen that there is a lot of noise and the component of the fault characteristic frequency cannot be extracted.

[0042] Step 2: Use the maximum kurtosis principle to adaptively determine the optimal order of the AR model, such as image 3 As shown; by selecting the order of the best AR model, the AR model is used to reduce the noise of the vibration signal, and the noise-reduced vibration signal is obtained;

[0043] Step 3: Separating the modulati...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

A fault diagnosis method employing enhanced modulation signal bispectrum analysis for a rolling bearing, proposed to address the drawback of modulation signal bispectrum analysis in which Gaussian noise can be suppressed in theory, but the analysis cannot address non-Gaussian noise. The method specifically comprises: measuring a vibration signal of a rolling bearing under test by means of a vibration sensor; performing noise reduction processing on the obtained vibration signal according to an AR model, and obtaining a reduced-noise vibration signal; and performing MSB separation on the reduced-noise vibration signal to obtain modulation components, and extracting a fault characteristic frequency. The fault diagnosis method employing enhanced modulation signal bispectrum analysis for a rolling bearing effectively extracts weak characteristic information of a faulty bearing amidst high background noise, thereby facilitating early fault detection of bearings.

Description

technical field [0001] The invention relates to the technical field of mechanical equipment state monitoring and fault diagnosis, in particular to a rolling bearing fault diagnosis method based on enhanced modulation bispectral analysis. Background technique [0002] Rolling bearings are the most widely used mechanical parts in rotating machinery, and they are also one of the most easily damaged components. In the vibration signals of rotating machinery, a large number of signals are non-stationary and non-Gaussian distribution signals, especially when faults occur. However, traditional power spectrum analysis and time-frequency analysis cannot reflect the phase information between frequency components, and usually cannot deal with non-minimum phase systems and non-Gaussian signals, while modulation bispectral analysis (MSB) is to analyze non-stationary and non-Gaussian signals powerful tool. MSB makes up for the defect that the second-order statistics do not contain phase...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/045
CPCG01M13/045
Inventor 甄冬郭俊超谷丰收张浩师占群
Owner HEBEI UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com