Quayside-container-crane health condition monitoring systems result in huge numbers of condition data accumulated in databases. Finding out cranes' conditions changes from these data is actually valuable for equipments' securities. The paper presents a quantitative association rules approach to mine rules (patterns) among the condition data. Sequentially, the relationships between the rules and the crane's condition changes are discussed, and conclusions are made that the transformations of rules can assist in assessing the health conditions of cranes.
Mining Association Rules on Data of Crane Health-Condition Monitoring
First International Conference on Transportation Engineering ; 2007 ; Southwest Jiaotong University, Chengdu, China
2007-07-09
Conference paper
Electronic Resource
English
Mining Association Rules on Data of Crane Health-Condition Monitoring
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