A Novel Strong Tracking Fault Prognosis Algorithm. (8th June 2015)

• Record Type: Journal Article
• Authors: Zhang, Qi; Jiang, Wei; Li, Tian-Mei; Zheng, Jian-Fei
• Other Names: Li Gang Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2015(2015)
• Publication Date: 2015-06-08
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2015/676289
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : Improving the ability to track abruptly changing states and resolving the degeneracy are two difficult problems to particle filter applied to fault prognosis. In this paper, a novel strong tracking fault prognosis algorithm is proposed to settle the above problems. In the proposed algorithm, the artificial immunity algorithm is first introduced to resolve the degeneracy problem, and then the strong tracking filter is introduced to enhance the ability to track abruptly changing states. The particles are updated by strong tracking filter, and better particles are selected by utilizing the artificial immune algorithm to estimate states. As a result, the degeneracy problem is resolved and the accuracy of the proposed fault prognosis algorithm is improved accordingly. The feasibility and validity of the proposed algorithm are demonstrated by the simulation results of the standard validation model and the DTS200 system.