Noise reduction for lidar returns using self-adaptive wavelet neural network

2017 ◽  
Vol 24 (3) ◽  
pp. 416-427
Author(s):  
Xuezhen Qin ◽  
Jiandong Mao
Keyword(s):  
Neural Network ◽  
Noise Reduction ◽  
Wavelet Neural Network ◽  
Adaptive Wavelet ◽  
Self Adaptive

The Application of Self-Adaptive Wavelet Neural Network in Multi-Layered Structure Ultrasonic Testing of the Solid Rocket-Motor

2013 ◽  
Vol 421 ◽  
pp. 474-478
Author(s):  
Xi Peng Yin ◽  
You Li ◽  
Wei Cheng ◽  
Chang Chen
Keyword(s):  
Neural Network ◽  
Layered Structure ◽  
Ultrasonic Testing ◽  
Wavelet Neural Network ◽  
Rocket Motor ◽  
Testing System ◽  
Solid Rocket Motor ◽  
Adaptive Wavelet ◽  
Solid Rocket ◽  
Self Adaptive

t is important to remove the noise signal effectively in non-destructive ultrasonic testing. Use the wavelet and neural network algorithm in multi-layered structure ultrasonic testing system of the solid rocket-motor, and construct self-adaptive wavelet neural network in the ultrasonic testing in order to restrain the noise. Better fitting signal is achieved by choosing Orthogonal Daubechies wavelet group and optimize the scale parameter by a searching algorithm. The simulation result shows that the wavelet neural network can make the testing system less distortion and better noise cancellation, and the method can be widely applied to ultrasonic detecting.

TIG Auto Welding Process Using Adaptive Wavelet Neural Network Controller

2015 ◽  
Vol 764-765 ◽  
pp. 634-639
Author(s):  
Yen Bin Chen ◽  
Yung Lung Lee ◽  
Shou Jen Hsu ◽  
Chin Chun Chang ◽  
Yi Wei Chen
Keyword(s):  
Neural Network ◽  
Vacuum Chamber ◽  
Welding Current ◽  
Wavelet Neural Network ◽  
Feed Speed ◽  
Automatic Welding ◽  
Adaptive Wavelet ◽  
Neural Network Controller ◽  
Network Controller ◽  
Wire Feed Speed

The study proposed adaptive wavelet neural network controller can achieve good and precise welding control performance and use synchrotron radiation research center developed multi-gun group automatic welding system to verify the validity of the research method. Multi-gun group welding system is applied in Taiwan Photon Source (TPS). Storage ring aluminum alloy vacuum chamber of Taiwan Photon Source .In the past aluminum alloy vacuum chamber welding, it all depends on the empirical welding rule of operator to give appropriate welding current, argon flow, wire feed speed and welding speed for control. Therefore, the paper uses automatic welding skill, which takes National Instruments PXI-8180 system as basic structure, and adaptive wavelet neural network controlled four optimized parameters, I.E. welding current, wire feed speed, flow rate of argon gas and welding speed, The vacuum chamber pressure value is also up to 6.2X10-10Torr/mA. It is successfully applied to the TPS system. Therefore, it can prove the effectiveness and practicality of the method proposed in this study.

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