TY - GEN
T1 - A multi-structuring elements edge detection method based on gray-scale morphology of parameter image for rotating machinery
AU - Zhang, Ying
AU - Su, Xianzhang
AU - Liu, Zhansheng
PY - 2010
Y1 - 2010
N2 - The study subject of this paper is rotating mechanical parameter image, multi-structuring elements edge detection method based on gray-scale morphology, and edge detection operator is brought forward, which is suit to detect parameter image for rotating machinery. The 3d vibration parameter image are obtained from rotor's normal state, fault of unbalance, misalignment, steam exciting vibration and bearing pedestal looseness which are examined on the modeling of 600 MW turbine rotor experimental bench. These 3d image of different faults are pretreated and transformed to 2d gray-scale image, then their edge are detected with multi-structuring elements edge detection operator constructed in this paper. The result shows that this method can effectively filter out the noise of parameter image and obtain high-quality edge features from the failure image.
AB - The study subject of this paper is rotating mechanical parameter image, multi-structuring elements edge detection method based on gray-scale morphology, and edge detection operator is brought forward, which is suit to detect parameter image for rotating machinery. The 3d vibration parameter image are obtained from rotor's normal state, fault of unbalance, misalignment, steam exciting vibration and bearing pedestal looseness which are examined on the modeling of 600 MW turbine rotor experimental bench. These 3d image of different faults are pretreated and transformed to 2d gray-scale image, then their edge are detected with multi-structuring elements edge detection operator constructed in this paper. The result shows that this method can effectively filter out the noise of parameter image and obtain high-quality edge features from the failure image.
KW - Edge detection
KW - Gray-scale morphology
KW - Multi-structuring elements
KW - Rotating machinery
KW - Vibration parameter image
UR - https://www.scopus.com/pages/publications/78650565747
U2 - 10.1109/CISP.2010.5646907
DO - 10.1109/CISP.2010.5646907
M3 - 会议稿件
AN - SCOPUS:78650565747
SN - 9781424465149
T3 - Proceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
SP - 1067
EP - 1071
BT - Proceedings - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
T2 - 2010 3rd International Congress on Image and Signal Processing, CISP 2010
Y2 - 16 October 2010 through 18 October 2010
ER -