An early diagnosis method for bearing faults based on adaptive frequency-shift variable-scale resonance technology

An early diagnosis and scale-changing technology, applied in the testing of mechanical components, testing of machine/structural components, instruments, etc., can solve problems such as difficulty in extracting early fault signals of bearings, achieve the effect of eliminating interference and improving signal-to-noise ratio

Active Publication Date: 2022-06-21
NANTONG UNIVERSITY
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a bearing fault early diagnosis method based on adaptive frequency shift and variable scale resonance technology, so as to solve the problem that the early fault signal of the bearing is difficult to extract

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
  • An early diagnosis method for bearing faults based on adaptive frequency-shift variable-scale resonance technology
  • An early diagnosis method for bearing faults based on adaptive frequency-shift variable-scale resonance technology
  • An early diagnosis method for bearing faults based on adaptive frequency-shift variable-scale resonance technology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] The technical solutions in the embodiments of the present invention will be described clearly and completely below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the technical solutions in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present invention.

[0029] like figure 1 , this scheme provides a bearing fault early diagnosis method based on adaptive frequency shift variable scale resonance technology, which includes the following steps:

[0030] Step 1: First, install the fault bearing to be detected on the output shaft of the motor with load, use the rotation of the motor to drive the bearing to be detected to rotate, and then use the acceleration sensor to collect the original vibration signal v(t) of the bearing of the faulty bearing to be detected.

[0031] Step...

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

The invention relates to the technical field of bearing fault diagnosis, and discloses an early diagnosis method for bearing faults based on adaptive frequency-shift variable-scale vibration resonance technology. In the method, the original vibration signal of the bearing is firstly extracted, and then the bearing vibration signal is processed by a signal processing function. Generate the superposition signal, and then use the quantum genetic algorithm to adjust the parameters of the bistable potential function for the purpose of improving the signal-to-noise ratio to optimize the superposition signal, so as to obtain a better output waveform. Beneficial effects: the method can use the collected signal to quickly optimize the parameters of the steady-state function through the quantum genetic algorithm, improve the signal-to-noise ratio of the output signal, thereby using the noise to enhance the characteristic signal of the bearing fault, and effectively detect the bearing fault, and the detection effect is better than the traditional one. The maximum correlation spectral kurtosis deconvolution method.

Description

technical field [0001] The invention relates to the technical field of bearing fault diagnosis, in particular to a bearing fault early diagnosis method based on adaptive frequency shift variable scale resonance technology. Background technique [0002] Rolling bearings are commonly used components in mechanical equipment such as hydraulic turbines and wind turbines. During the service process of rolling bearings, they are prone to wear, spalling, pitting and other faults due to external complex load impact. If the faults of rolling bearings are not detected and handled in time, Then the spread of the failure may paralyze the entire equipment, resulting in serious economic losses. Therefore, periodic inspection and maintenance of bearings is required to facilitate risk assessment and component replacement during early failures to reduce possible economic losses. [0003] Existing bearing fault detection mainly relies on fault signal processing technology. Specifically, it is...

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 谢占山田乾谭林伟吴强陈满华毛成曹宇鹏周井玲钱永明杨玉萍
Owner NANTONG UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap