incipient gearbox fault diagnosis based on the reverse state transformation of the chaotic duffing oscillator and sampling integral technology

incipient gearbox fault diagnosis based on the reverse state transformation of the chaotic duffing oscillator and sampling integral technology

;Li Jie;Zhao Jianmin
journal of power sources 2015 Vol. 2015 pp. -
141
jie2015mathematicalincipient

Abstract

Incipient fault for a gearbox diagnosis is difficult because the signals with low signal-to-noise ratio (SNR) are corrupted with background noise. A method based on chaos theory and sampling integral technology will be presented to detect the incipient fault of gearbox according to the characters of the gearbox vibration signals. Sampling integral technology was used to improve the tracking ability of fault signals with lower SNR. The small changes in the sidebands of meshing frequency can be detected by the transformation of chaotic phase diagram and its Hu moment invariants, and on this basis the incipient faults can be diagnosed. The results based on gearboxes experiment justify the effectiveness of the method.

Citation

ID: 128404
Ref Key: jie2015mathematicalincipient
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
128404
Unique Identifier:
10.1155/2015/535398
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet