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Vol. 172, Issue 6, June 2014, pp. 241-246

 

Bullet

 

The Application of Helicopter Rotor Defect Detection Using Wavelet Analysis
and Neural Network Technique
 

1 Jin-Li Sun, 1,* Xiao-Li Li, 2 Zheng-Long Li

1 Naval Aeronautical Engineering Institute Qingdao branch campus, No. 2 Siliu Middle Road, Qingdao, 266041, P.R. of China
2 Nanchang Hang Kong University, Nanchang, 330063, P. R. of China.
* Tel.: 13791812782

* E-mail: qdlixl@163.com

 

Received: 11 April 2014 /Accepted: 30 May 2014 /Published: 30 June 2014

Digital Sensors and Sensor Sysstems

 

Abstract: When detect the helicopter rotor beam with ultrasonic testing, it is difficult to realize the noise removing and quantitative testing. This paper used the wavelet analysis technique to remove the noise among the ultrasonic detection signal and highlight the signal feature of defect, then drew the curve of defect size and signal amplitude. Based on the relationship of defect size and signal amplitude, a BP neural network was built up and the corresponding estimated value of the simulate defect was obtained by repeating training. It was confirmed that the wavelet analysis and neural network technique met the requirements of practical testing.

 

Keywords: Ultrasonic testing, Wavelet analysis, Artificial neural network, Helicopter rotor defect.

 

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