Hydroelectric equipment monitoring and fault diagnosis system based on big data technology

Abstract

The invention discloses a hydroelectric equipment monitoring and fault diagnosis system based on the big data technology. The hydroelectric equipment monitoring and fault diagnosis system comprises a visualization display module, an alarm management module, a query and statistics module and a fault diagnosis nodule. The visualization display module collects to-be-monitored information of a substation through a state access controller and uploads the information to a data uploading server through the state access controller, in this way, the data uploading server module can upload the equipment monitoring data to an Hbase database, query and statistics can be conducted on relevant information, and equipment monitoring information and equipment-related statistical information can be displayed. The alarm management module generates an alarm record through configuration of combined alarm conditions of an equipment monitoring point. The query and statistics module is used for achieving the functions for history query of the equipment monitoring data and general information query of equipment-related accounts. The fault diagnosis nodule adopts various fault diagnosis models or prediction models for conducting equipment fault diagnosis and early warning. By the adoption of the hydroelectric equipment monitoring and fault diagnosis system based on the big data technology, equipment diagnosis efficiency can be improved, the equipment diagnosis level can be increased, the basis is provided for equipment condition-based maintenance, the maintenance cost is reduced, and power supply reliability is improved.

Description

technical field [0001] The invention relates to equipment monitoring and fault diagnosis application technology, in particular to a hydropower equipment monitoring and fault diagnosis system based on big data technology, which is suitable for monitoring and fault diagnosis of hydropower equipment at the group level and in a large centralized mode. Background technique [0002] In recent years, in the field of hydropower stations and pumped storage power stations, a mature system for equipment monitoring and fault diagnosis has not yet formed, and equipment monitoring and fault diagnosis still remain in the fixed value alarm analysis mode of a single system of equipment manufacturers. Existing hydropower plant equipment systems are highly integrated complete systems, and the monitoring, diagnosis and analysis of a single equipment and a single data dimension can no longer meet the needs of daily production and operation. Therefore, it has become an inevitable trend to establi...

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Problems solved by technology

[0005] At present, in order to improve the safe operation of equipment, some hydropower stations have installed some equipment status monitoring systems. In the same power station, each equipment status monitoring system operates independently, operates in isolation, diagnoses in isolation, and resources cannot be shared. The comprehensive utilization of equipment information cannot be realized. Equipment status diagnosis and auxiliary decision-making; at the same time, the content of information collected by the online monitoring system of each manufacturer is different, the technical means used are different, and the technical standards followed are also different, lacking a unified information collection specification

Therefore, the fragmented online monitoring system is extremely unfavorable to the centralized management of online monitoring and fault diagnosis of hydropower stations.

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