An improved particle filtering algorithm for aircraft engine gas-path fault diagnosis. (July 2016)

• Record Type: Journal Article
• Authors: Wang, Qihang; Huang, Jinquan; Lu, Feng
• Is Part Of: Advances in mechanical engineering. Volume 8:Number 7(2016:Jul.)
• Publication Date: 2016-07
• Subjects: Aircraft engine -- fault diagnosis -- particle filter -- electromagnetism-like mechanism -- non-Gaussian noise; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/1687814016659602
• Languages: English
• ISSNs: 1687-8132

Abstract

In this article, an improved particle filter with electromagnetism-like mechanism algorithm is proposed for aircraft engine gas-path component abrupt fault diagnosis. In order to avoid the particle degeneracy and sample impoverishment of normal particle filter, the electromagnetism-like mechanism optimization algorithm is introduced into resampling procedure, which adjusts the position of the particles through simulating attraction–repulsion mechanism between charged particles of the electromagnetism theory. The improved particle filter can solve the particle degradation problem and ensure the diversity of the particle set. Meanwhile, it enhances the ability of tracking abrupt fault due to considering the latest measurement information. Comparison of the proposed method with three different filter algorithms is carried out on a univariate nonstationary growth model. Simulations on a turbofan engine model indicate that compared to the normal particle filter, the improved particle filter can ensure the completion of the fault diagnosis within less sampling period and the root mean square error of parameters estimation is reduced.