Approach and Application of Semi-Blind Source Separation for Aero-Engine Vibration Signals Using ICA-R

Lujie Shi, Yankai Wang, Mingfu Liao, Yunfan Jiang

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

In this paper, the approach and application of semi-blind source separation (SBSS) in aero-engine vibration signal is studied. Firstly, the features of aero-engine vibration signal and difficulties for blind source separation (BSS) are summarized, and the SBSS incorporated the available prior knowledge is match to the goal of signal processing. Then, the ICA with reference (ICA-R) algorithm based on classical FastICA is introduced, with Newton iteration and gradient descent iteration approach to obtain optimal solution. The unique parameters in ICA-R for aero-engine vibration signal are also provided. Finally, the efficacy and the accuracy of the ICA-R algorithm are verified by numerical simulations and real engine vibration signals. The approach of SBSS in this paper perfectly suited to handle aero-engine vibration source separation and it lead to efficient implementation in fault diagnosis.

Original languageEnglish
Article number012030
JournalJournal of Physics: Conference Series
Volume1215
Issue number1
DOIs
StatePublished - 22 May 2019
Event2018 9th Asia Conference on Mechanical and Aerospace Engineering, ACMAE 2018 - Singapore, Singapore
Duration: 29 Dec 201831 Dec 2018

Fingerprint

Dive into the research topics of 'Approach and Application of Semi-Blind Source Separation for Aero-Engine Vibration Signals Using ICA-R'. Together they form a unique fingerprint.

Cite this