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.