Predictive maintenance of power plant equipment driven by “cloud+client” big data

Abstract

Abstract:

Guarantee for the stability of power plant equipment is very important for power generation enterprises. An architecture of a predictive maintenance system for power plant equipment is proposed,which can collect, process and computing data on the client side,and aggregate, store, batch process and realtime process data on the cloud side. The key technologies of writing, parallel processing of massive sensor data, and predictive maintenance for the system based on HBase cloud database were analyzed.The architecture not only saved frontend resources, but also showed the potential value of the massive sensor data. Through predicting fault based on massive sensor data, the maintenance on the equipment could be done timely according to actual situations, which helped personnel in decisionmaking and making countermeasures in advance.Preventing and controlling the potential fault will ensure the reliability and stability of power plants.

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WANG Jiazi1，WANG Guiling2.

Predictive maintenance of power plant equipment driven by “cloud+client” big data [J]. Huadian Technology, 2019, 41(11): 40-45.

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Predictive maintenance of power plant equipment driven by “cloud+client” big data

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