NDLI: State Recognition and Visualization of Hoisting Motor of Quayside Container Crane Based on SOFM

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State Recognition and Visualization of Hoisting Motor of Quayside Container Crane Based on SOFM

Content Provider	Scilit
Author	Yang, Z. Q. He, P. Tang, G. Hu, X.
Copyright Year	2017
Description	Journal: Journal of Physics: Conference Series The neural network structure and algorithm of self-organizing feature map (SOFM) are researched and analysed. The method is applied to state recognition and visualization of the quayside container crane hoisting motor. By using SOFM, the clustering and visualization of attribute reduction of data are carried out, and three kinds motor states are obtained with Root Mean Square(RMS), Impulse Index and Margin Index, and the simulation visualization interface is realized by MATLAB. Through the processing of the sample data, it can realize the accurate identification of the motor state, thus provide better monitoring of the quayside container crane hoisting motor and a new way for the mechanical state recognition.
Related Links	http://iopscience.iop.org/article/10.1088/1742-6596/870/1/012022/pdf
ISSN	17426588
e-ISSN	17426596
DOI	10.1088/1742-6596/870/1/012022
Journal	Journal of Physics: Conference Series
Volume Number	870
Language	English
Publisher	IOP Publishing
Publisher Date	2017-07-11
Access Restriction	Open
Subject Keyword	Journal: Journal of Physics: Conference Series Characterization and Testing of Materials State Recognition Hoisting Motor Network Structure Reduction of Data Simulation Visualization Quayside Container Crane
Content Type	Text
Resource Type	Article
Subject	Physics and Astronomy

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