Quayside Crane Hoist Motor State Recognition Based on Hierarchical Clustering Algorithm

2018 2nd International Conference on Artificial Intelligence Applications and Technologies

计算机科学

Li, Y.J.^1 ; Tang, G.^1 ; Hu, X.^1

Logistics Engineering College, Shanghai Maritime University, Shanghai

201306, China^1

关键词: Dynamic performance;    Hierarchical clustering algorithms;    Lower limits;    Motor state;    Sensor location;    Upper limits;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/435/1/012011/pdf
DOI  :  10.1088/1757-899X/435/1/012011

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

To analyze the dynamic performance of quayside crane, Hierarchical Clustering Algorithm is applied to recognise the different states of Quayside Crane Hoist Motor. The experiment is based on the data collected by NetCMAS (Condition Monitoring & Assessing System on Network). Provided that without knowing the dynamic performance of quayside crane, the vibratory intensity of hoist motor output to the left of quayside crane (sensor location: L1V) is divided into four different states: starting status, lightly vibrating status, moderate vibrating status and severe vibrating status, meanwhile, the floating upper limit and lower limit could be observed.