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Signal processing and image restorat...

Wang, Bing.

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Signal processing and image restoration techniques for two-dimensional eddy current nondestructive evaluation.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Signal processing and image restoration techniques for two-dimensional eddy current nondestructive evaluation./
作者:	Wang, Bing.
面頁冊數:	271 p.
附註:	Source: Dissertation Abstracts International, Volume: 58-06, Section: B, page: 3240.
Contained By:	Dissertation Abstracts International58-06B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9737777
ISBN:	0591477637

Signal processing and image restoration techniques for two-dimensional eddy current nondestructive evaluation.
Wang, Bing.

Signal processing and image restoration techniques for two-dimensional eddy current nondestructive evaluation. - 271 p.

Source: Dissertation Abstracts International, Volume: 58-06, Section: B, page: 3240.

Thesis (Ph.D.)--Iowa State University, 1997.

This dissertation presents a comprehensive study on the forward modeling methods, signal processing techniques, and image restoration techniques for two-dimensional eddy current nondestructive evaluation. The basic physical forward method adopted in this study is the volume integral method. We have applied this model to the eddy current modeling problem for half space geometry and thin plate geometry. To reduce the computational complexity of the volume integral method, we have developed a wavelet expansion method which utilizes the multiresolution compression capability of the wavelet basis to greatly reduce the amount of computation with small loss in accuracy. To further improve the speed of forward modeling, we have developed a fast eddy current model based on a radial basis function neural network. This dissertation also contains investigations on signal processing techniques to enhance flaw signals in two-dimensional eddy current inspection data. The processing procedures developed in this study include a set of preprocessing techniques, a background removal technique based on principal component analysis, and grayscale morphological operations to detect flaw signals. Another important part of the dissertation concerns image restoration techniques which can remove the blurring in impedance change images due to the diffusive nature of the eddy current testing. We have developed two approximate linear image restoration methods--the Wiener filtering method and the maximum entropy method. Both linear restoration methods are based on an approximate linear forward model formulated by using the Born approximation. To improve the quality of restoration, we have also developed nonlinear image restoration methods based on simulated annealing and a genetic algorithm. Those nonlinear methods are based on the neural network forward model which is more accurate than the approximate linear forward model.

ISBN: 0591477637Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Signal processing and image restoration techniques for two-dimensional eddy current nondestructive evaluation.
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502 $a Thesis (Ph.D.)--Iowa State University, 1997.
520 $a This dissertation presents a comprehensive study on the forward modeling methods, signal processing techniques, and image restoration techniques for two-dimensional eddy current nondestructive evaluation. The basic physical forward method adopted in this study is the volume integral method. We have applied this model to the eddy current modeling problem for half space geometry and thin plate geometry. To reduce the computational complexity of the volume integral method, we have developed a wavelet expansion method which utilizes the multiresolution compression capability of the wavelet basis to greatly reduce the amount of computation with small loss in accuracy. To further improve the speed of forward modeling, we have developed a fast eddy current model based on a radial basis function neural network. This dissertation also contains investigations on signal processing techniques to enhance flaw signals in two-dimensional eddy current inspection data. The processing procedures developed in this study include a set of preprocessing techniques, a background removal technique based on principal component analysis, and grayscale morphological operations to detect flaw signals. Another important part of the dissertation concerns image restoration techniques which can remove the blurring in impedance change images due to the diffusive nature of the eddy current testing. We have developed two approximate linear image restoration methods--the Wiener filtering method and the maximum entropy method. Both linear restoration methods are based on an approximate linear forward model formulated by using the Born approximation. To improve the quality of restoration, we have also developed nonlinear image restoration methods based on simulated annealing and a genetic algorithm. Those nonlinear methods are based on the neural network forward model which is more accurate than the approximate linear forward model.
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