Primary Research on Real-Time Fault Diagnosis Platform for Fuel Tank System of an Aircraft

doi:10.1007/s12204-015-1637-4

摘要/Abstract

摘要： Sub-tanks in fuel tank systems of aircrafts transfer fuel to engines in certain order. These sub-tanks and attached tank-accessories affect each other, and make fault diagnosis in such systems rather difficult. Without real measured data, this paper analyzes fault modes and fault effects of the fuel tank system, including its tankaccessories, of a given aircraft. Fault model of the system is built theoretically, and fault diagnosis criteria are deduced. Such criteria are then quantified to train a back propagation neural network (BPNN) as fault diagnosis model. To realize fault diagnosis of the real fuel tank system, a real-time fault diagnosis platform based on LabView and VxWorks to perform this diagnosis method is discussed. This platform is a technical groundwork for fault diagnosis in real fuel tank systems.

关键词: fuel tank systems, fault diagnosis, real-time platform, neural network

Abstract: Sub-tanks in fuel tank systems of aircrafts transfer fuel to engines in certain order. These sub-tanks and attached tank-accessories affect each other, and make fault diagnosis in such systems rather difficult. Without real measured data, this paper analyzes fault modes and fault effects of the fuel tank system, including its tankaccessories, of a given aircraft. Fault model of the system is built theoretically, and fault diagnosis criteria are deduced. Such criteria are then quantified to train a back propagation neural network (BPNN) as fault diagnosis model. To realize fault diagnosis of the real fuel tank system, a real-time fault diagnosis platform based on LabView and VxWorks to perform this diagnosis method is discussed. This platform is a technical groundwork for fault diagnosis in real fuel tank systems.

Key words: fuel tank systems, fault diagnosis, real-time platform, neural network

中图分类号:

TP 277

BAO Yong-lin (鲍泳林). Primary Research on Real-Time Fault Diagnosis Platform for Fuel Tank System of an Aircraft[J]. 上海交通大学学报（英文版）, 2015, 20(3): 358-362.

BAO Yong-lin (鲍泳林). Primary Research on Real-Time Fault Diagnosis Platform for Fuel Tank System of an Aircraft[J]. Journal of shanghai Jiaotong University (Science), 2015, 20(3): 358-362.

参考文献 6

[1]	Yin Chao. Research on real-time flight simulator based on MATLAB/RTW and VxWorks [J]. Software Guide,2010, 9(12): 86-87 (in Chinese).
[2]	Guo Jun. Research on BP neural network algorithm [D]. Wuhan, China: College of Computer Science,Huazhong University of Science and Technology, 2005(in Chinese).
[3]	Wang Jian-mei, Tan Wen-zhong. BP neural network classifier based on Levenberg-Marquardt algorithm [J].Geomatics and Information Science of Wuhan University,2005, 30(10): 928-931 (in Chinese).
[4]	Tang Zhong, Xie Tao. Application and simulation of MATLAB neuron network tool NNTool [J]. Computer and Modernization, 2012, 208(12): 44-47 (in Chinese).
[5]	Liao Shen-qin, Peng Liang-yu, Jiang Yong. BP neural network’s realization and application in LabVIEW[J]. Modern Electronics Technique, 2009, 291(4): 72-75 (in Chinese).
[6]	Shi Wei-jia, He Peng-ju, Li Jie, Real-time simulation and embedded system development based on MATLAB/RTW [J]. Microcontrollers & Embedded Systems,2009 (10): 42-44 (in Chinese).

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