Intelligent Diagnosis of Aircraft Electrical Faults Based on RMBP Neural Network

Authors

Lishan Jia, 1. Tianjin Key Laboratory for Civil Aircraft Airworthiness and Maintenance of Civil Aviation University of China, Civil Aviation University of China, Tianjin 300300, China;;2. Ground Support Equipments Research Base of Civil University of China, Civil Aviation University of China, Tianjin 300300, China;;
Zhe Liu, 1. Tianjin Key Laboratory for Civil Aircraft Airworthiness and Maintenance of Civil Aviation University of China, Civil Aviation University of China, Tianjin 300300, China;;2. Ground Support Equipments Research Base of Civil University of China, Civil Aviation University of China, Tianjin 300300, China;;3. Beijing Aircraft Maintenance and Engineering Corporation Tianjin branch, Tianjin 300300, China;
Sun Yi, 1. Tianjin Key Laboratory for Civil Aircraft Airworthiness and Maintenance of Civil Aviation University of China, Civil Aviation University of China, Tianjin 300300, China;;2. Ground Support Equipments Research Base of Civil University of China, Civil Aviation University of China, Tianjin 300300, China;;

Abstract

Abstract: To the characteristics of multiple properties, hard to remove and high cost of time and manpower of aircraft electrical faults maintenance in aircraft maintenance of civil aviation, construction of intelligent aircraft electrical faults diagnosis system using RMBP neural network is proposed. RMBP algorithm is used to study sample data in the intelligent faults diagnosis system as it can overcome the faults of long time of convergence and easy to go into local minima of common BP algorithm, and is suitable for training large-scale neural network,. Experience data are collected, samples are made, samples training and experiment are carried out. Results of experiment show that intelligent diagnosis system of aircraft electrical faults can diagnose the faults of test samples correctly, which verifies that it can meet the requirement of aircraft electrical faults maintenance of civil aviation.

Recommended Citation

Jia, Lishan; Liu, Zhe; and Yi, Sun (2019) "Intelligent Diagnosis of Aircraft Electrical Faults Based on RMBP Neural Network," Journal of System Simulation: Vol. 30: Iss. 9, Article 34.
DOI: 10.16182/j.issn1004731x.joss.201809034
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss9/34

First Page

3493

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201809034

Last Page

3501

CLC

TP183;TP181;TP182

Recommended Citation

Jia Lishan, Liu Zhe, Sun Yi. Intelligent Diagnosis of Aircraft Electrical Faults Based on RMBP Neural Network[J]. Journal of System Simulation, 2018, 30(9): 3493-3501.

DOI

10.16182/j.issn1004731x.joss.201809034