DocumentCode :
668587
Title :
Fault feature extraction and diagnosis of phased array element based on wavelet and neural network
Author :
Wei Zhe ; Huang Shi-zhao
Author_Institution :
Newstar Inf. Technol. Co. Ltd., Hefei, China
Volume :
2
fYear :
2013
fDate :
23-24 Nov. 2013
Firstpage :
269
Lastpage :
272
Abstract :
In view of phased array antenna transmitting performance test is difficult, a novel method based on wavelet and neural network is proposed. A receiving antenna is utilized to measure the change of the power transmitted by phased array antenna along with scanning. Phased array scanning model is researched. For one-dimensional linear array, wavelet analysis is utilized to extract the fault characteristic vectors, and neural network is utilized to train and classify. Improvement measure is proposed aimed at slow convergence speed. MATLAB Monte Carlo simulation indicates that, proposed method is valid to diagnose phased array element faults in theory.
Keywords :
Monte Carlo methods; antenna phased arrays; feature extraction; linear antenna arrays; neural nets; receiving antennas; wavelet transforms; MATLAB; Monte Carlo simulation; feature diagnosis; feature extraction; neural network; one-dimensional linear array; phased array antenna; phased array element; phased array scanning model; receiving antenna; wavelet analysis; wavelet network; Antenna measurements; Arrays; Convergence; Feature extraction; Neural networks; Phased arrays; Wavelet analysis; Phased array antenna; fault diagnosis; neural network; wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering (ICIII), 2013 6th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4799-3985-5
Type :
conf
DOI :
10.1109/ICIII.2013.6703136
Filename :
6703136
Link To Document :
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