Abstract
Aiming at the data stream obtained in the energy control system of a cigarette factory, a data stream pattern analysis method is proposed which provides support for anomaly detection and other applications by detecting and tracking the pattern and extracting the evolution between the patterns. In this paper, the concept and definition of pattern tracking method for data streams are proposed, as well as the measurement criteria of pattern similarity. On this basis, the paper introduces in detail how to generate and cluster the hypercube grids, store the grid, generate the pattern and track the pattern on the real-time data stream. The paper also defines and describes the dynamic process of the generating, retreating, mutating, dividing and merging of the data stream pattern. The algorithm in this paper is applied to the real data stream collected in the energy control system of Ningbo cigarette factory, identifying and analyzing various feature of the data stream pattern, which can effectively describe the physical changes of the energy system.
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