Study of the hydroacoustic emitter based on the antisymmetric lamb wave in a piezoelectric ceramic plate

2011 ◽  
Vol 56 (11) ◽  
pp. 1382-1386 ◽  
Author(s):  
I. E. Kuznetsova ◽  
B. D. Zaitsev ◽  
I. A. Borodina ◽  
V. V. Kolesov ◽  
A. I. Sknarya ◽  
...  
Keyword(s):  
Lamb Wave ◽  
Piezoelectric Ceramic ◽  
Ceramic Plate

Propagation of thickness-twist waves in a piezoelectric ceramic plate in contact with viscous fluids

2009 ◽  
Vol 212 (3-4) ◽  
pp. 263-270 ◽  
Author(s):  
Zheng-Hua Qian ◽  
Nan Liu ◽  
Jiashi Yang ◽  
Sohichi Hirose
Keyword(s):  
Piezoelectric Ceramic ◽  
Viscous Fluids ◽  
Ceramic Plate

Trapped-energy vibratory gyroscopes using a partially polarized piezoelectric ceramic plate

2001 ◽  
Vol 84 (3) ◽  
pp. 44-52 ◽  
Author(s):  
Hiroshi Abe ◽  
Tetsuo Yoshida ◽  
Toshihiro Ishikawa ◽  
Noriko Miyazaki ◽  
Hiroshi Watanabe
Keyword(s):  
Piezoelectric Ceramic ◽  
Ceramic Plate ◽  
Vibratory Gyroscopes

scholarly journals Image-Based Scratch Detection by Fuzzy Clustering and Morphological Features

2020 ◽  
Vol 10 (18) ◽  
pp. 6490
Author(s):  
Zhiying Tan ◽  
Yan Ji ◽  
Zhongwen Fei ◽  
Xiaobin Xu ◽  
Baolai Zhao
Keyword(s):  
Piezoelectric Ceramic ◽  
Interpolation Method ◽  
Morphological Features ◽  
Visual Features ◽  
Ceramic Plate ◽  
Textured Surfaces ◽  
Fuzzy C Means ◽  
Training Images ◽  
Fuzzy C Means Clustering ◽  
Scratch Detection

Detection of scratch defects on randomly textured surfaces remains challenging due to their unnoticeable visual features. In this paper, an algorithm for piezoelectric ceramic plate surface scratch defects based on the combination of fuzzy c-means clustering and morphological features is proposed. Foreground membership of each gray value is calculated firstly on a reference set of training images by fuzzy c-means clustering and the interpolation method, then an enhanced image is obtained by multiplying the foreground membership function and gray image. The location relationship between regions and the gradient direction of regions is extracted from the binary image of the enhanced image. Based on the morphological features, isolated non-scratched defects are filtered out and the intermittent scratches are merged. Experiments show that the algorithm can be used to detect scratch defects on the surface of a piezoelectric ceramics plate with randomly textured surfaces.

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