Fault diagnosis for large diesel fuel engine based on chaotic fractal method. Issue 3 (September 2016)

• Record Type: Journal Article
• Authors: Li, Jie; Zhao, Jian min; Wang, Xu An
• Other Names: Xhafa Fatos guest-editor.; Wang Xu An guest-editor.
• Is Part Of: Journal of algorithms & computational technology. Volume 10:Issue 3(2016)
• Page Start: 142
• Page End: 157
• Publication Date: 2016-09
• Subjects: the largest Lyapunov exponent -- correlation dimension -- fault vibration signal -- diesel engine fuel system -- health condition assessment; Computer algorithms -- Periodicals; Numerical calculations -- Periodicals; Computer algorithms; Numerical calculations; Periodicals; 518.1
• DOI: 10.1177/1748301816640252
• Languages: English
• ISSNs: 1748-3018

Abstract

In contrast with the large diesel engine fuel system operational condition complexity, the chaotic fractal characteristics in the combustion process of the diesel engine fuel system are systematically analyzed. Then, based on chaotic fractal method, an effective fault diagnosis method is further proposed. And under the two kinds of typical failure modes, the two important characteristic parameters variation trend for chaotic system, namely, correlation dimensions and the calculation methods of the maximum Lyapunov exponent are discussed. On the process of chaotic parameters calculation the wavelet noise reduction method is used to handle the original signal to conquer the linear scaling region properly. The results show that the maximum Lyapunov exponent method is a more effective method on the diesel engine fuel system fault diagnosis than the correlation dimension method, which can be further used in health condition assessment for this type fuel engine.