Title :
Fault diagnosis about aviation-engine based on information integrating
Author :
Han, Yilun ; Ma Jun
Author_Institution :
Inst. of Mechano-Electron. Eng., Shandong Univ. of Technol., Qingdao, China
Abstract :
The article discussed the advantage and disadvantage about neural network and expert system. According to the feature of fault for aviation engine, the paper puts forward the system of multi-parallel neural networks which are harmonized by expert system based on information integrating for the fault diagnosis of aviation engine. The expert system is used to monitor the work condition of aviation engine and harmonize the operation of neural networks. The neural networks are used to diagnose fault according to the order of expert coordination system. The system uses the modularity structure and is programmed by C and MATLAB language, the neural network toolbox is used to develop BP neural network which diagnose the fault. The system takes advantage of neural network and expert system rand overcomes their disadvantages. The simulating test and practical use show that the accuracy and work efficiency of fault diagnosis are greatly increased.
Keywords :
C language; aerospace engines; backpropagation; expert systems; fault diagnosis; mechanical engineering computing; neural nets; reliability; BP neural network; C language; MATLAB language; aviation-engine; expert coordination system; fault diagnosis; information integrating method; modularity structure; multiparallel neural network; Atmospheric modeling; Compressors; Degradation; Engines; Fault diagnosis; MATLAB; Neural networks; aviation engine; fault; neural network;
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
DOI :
10.1109/ICCSN.2011.6014215