Fog computing system and method for hydropower generation group wide-area monitoring diagnosis

Abstract

The invention discloses a fog computing system and method for hydropower generation group wide-area monitoring diagnosis. The system comprises an in-situ edge computing node, a data service private cloud, a diagnosis service public cloud and a terminal device, which are connected in sequence. A hydropower generation set on-line monitoring system stores the monitored hydropower generation set operation condition information to an in-situ data server; the in-situ edge computing node is connected with the in-situ data server, obtains monitoring data and carries out feature extraction on the monitoring data, calculates characteristic indexes capable of indicating key performance of each hydropower generation set and then, sends the characteristic data to the data service private cloud; the data service private cloud carries out summary storage on the data and carries out coding on the data in a unified manner and sends the data to the diagnosis service public cloud; and the diagnosis service public cloud carries out fault diagnosis analysis on the characteristic data of the hydropower generation set through an expert system thereon, and pushes the diagnosis result to an intelligent terminal device carried by power plant operation and maintenance personnel. The fog computing system and method relieve network congestion and improve diagnosis real-time performance.

Description

technical field [0001] The invention relates to the field of online monitoring and diagnosis of hydroelectric power generation systems, in particular to a fog computing system and method for wide-area monitoring and diagnosis of hydropower groups. Background technique [0002] The safe and stable operation of hydropower units plays a decisive role in ensuring the normal operation of the power system, improving the reliability of power consumption, and ensuring the economic benefits of hydropower plants. In order to ensure the safe and stable operation of hydroelectric units, most hydroelectric units are equipped with online monitoring systems, and how to carry out effective fault diagnosis and fault early warning through the monitoring system has become a key technical problem in this field. [0003] At present, although some large-scale hydropower units have deployed special fault diagnosis systems to provide effective fault diagnosis and early warning for the units, it is ...

AI Technical Summary

Problems solved by technology

[0006] In view of the above technical problems, the present invention discloses a fog computing system and method for wide-area monitoring and diagnosis of hydropower groups. The present invention has low cost and high fault diagnosis efficiency, and effectively solves the Problems of wide-area monitoring and diagnosis of small and medium hydropower groups

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