Quayside Crane Hoist Motor State Recognition Based on Hierarchical Clustering Algorithm

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: LIV) 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.