Abnormal Pattern of Sensor Monitoring Data Analysis and Recognition

Abstract:

In order to solve the abnormal pattern recognition problem of the sensor monitoring data automatically, a set of method on the time series similarity measurement is used in this paper. Abnormal time series patterns clustering analysis based on the DTW distance is proposed firstly, thus the typical time series patterns can be obtained. From which the important shape indexes can be extracted and filtered based on piecewise shape measure method, then the shape index table can be established. With which a pattern recognition system can be designed used to recognize these abnormal patterns on real-time. As a case, this method has been used in a high gas coal mine and the important promotion application value has been proved in the sensor monitoring field.

• Periodical: Advanced Materials Research (Volumes 452-453)
• Pages: 863-867
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.452-453.863
• Online since: January 2012
• Authors: Shi Song Zhu, Fu Jing Zhu, Wen Hui Man
• Keywords: Abnormal Pattern, Clustering Analysis, Recognition, Shape Analysis

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