Electric Power Equipment Condition Intelligent Monitoring by Using Data Mining Method

Dong Zhang; Yan Zheng; Jing Li

doi:10.4028/www.scientific.net/AMM.303-306.961

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 303-306Electric Power Equipment Condition Intelligent...

Electric Power Equipment Condition Intelligent Monitoring by Using Data Mining Method

Abstract:

Industrial equipment has large amount of historical operation data, and the real-time sampling data is massive and multi-dimensions. This paper proposes an equipment condition intelligent monitoring algorithm based on data mining. The algorithm firstly makes adaptive clustering analysis of historical data on the good running condition of equipment, builds the mathematical model of the equipment, and makes prediction of equipment operation state according to this model and the value of real-time state of equipment operation. This algorithm fully considers the actual demand of industrial application, automatically determines the number of clustering class, solves the problem of large cost and low efficiency of traditional clustering algorithm processing massive historical data, and ensures the efficiency of regression forecasting process.

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Periodical:

Applied Mechanics and Materials (Volumes 303-306)

Pages:

961-965

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.303-306.961

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Online since:

February 2013

Authors:

Dong Zhang, Yan Zheng, Jing Li

Keywords:

Data Mining (DM), Equipment Condition, Intelligent Monitoring

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