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Notice of Retraction
Study of a Fault Diagnosis Method Based on Elman Neural Network and Trouble Dictionary

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4 Author(s)
Qu Dong-Cai ; Dept. of Control Eng., Naval Aeronaut. & Astronaut. Univ., Yantai ; Feng Yu-Guang ; Fan Shao-Li ; Chen Qi

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Because the traditional fault diagnosis methods had shortcomings, such as that the diagnosis speed was slow and it was hard to accurately fix the faults taking place at one time when it was diagnosing the complicated system or equipment, the fault diagnosis technology based on Elman neural network and trouble dictionary were introduced here. With the major failure of certain mould aircraft autopilot's flying-controlled box as the example, the real diagnosis course and method was analyzed and explained, and so on, the simulation research was made. The high-speed diagnosis for one fault and some faults taking place at one time is realized. The results show that this failure diagnosis method is effective to solve the issue.

Published in:

Natural Computation, 2008. ICNC '08. Fourth International Conference on  (Volume:2 )

Date of Conference:

18-20 Oct. 2008