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USE OF SEQUENTIAL CLUSTERING FOR INSTANCE SELECTION IN MACHINE CONDITION MONITORING
USE OF SEQUENTIAL CLUSTERING FOR INSTANCE SELECTION IN MACHINE CONDITION MONITORING
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机译:顺序聚类在机器状态监测中的即时选择中的应用
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摘要
A method is provided for selecting a representative set of training data for training a statistical model in a machine condition monitoring system. The method reduces the time required to choose representative samples from a large data set by using a nearest-neighbor sequential clustering technique in combination with a kd-tree. A distance threshold is used to limit the geometric size the clusters. Each node of the kd-tree is assigned a representative sample from the training data, and similar samples are subsequently discarded.
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