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

2nd International Conference on Measurement Instrumentation and Electronics

物理学;无线电电子学

Yang, Z.Q.^1 ; He, P.^2 ; Tang, G.^1 ; Hu, X.^1

Logistics Engineering College, Shanghai Maritime University, 1550 Harbor Road, Pudong New Area, Shanghai

201306, China^1

Shanghai East Container Terminal, Shanghai

200137, China^2

关键词: Attribute reduction;    Margin index;    Mechanical state;    Neural network structures;    Quayside container cranes;    Root Mean Square;    Sample data;    State recognition;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/870/1/012022/pdf
DOI  :  10.1088/1742-6596/870/1/012022

来源: IOP

【 摘 要 】

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.