Abstract: With the purpose of improving the intelligent level of power plant monitoring, this paper introduces an intelligent auxiliary monitoring system based on big data mining and rule engine, supported by big data technology and relying on various advanced machine learning algorithms. The system establishes the early warning model of all kinds of systems and equipment in power generation enterprises, which can accurately detect abnormal status of parameters and equipment, and reduce the monitoring pressure of operators. Early warning should be carried out in the early stage of equipment failure, and fault identification and troubleshooting guidance should be given to the early warning. The test results show that the system is beneficial to realize more comprehensive monitoring of equipment status in power plant, and it can further improve the operation level of units and the health level of equipment.

Key words: big data technology, machine learning, intelligent auxiliary monitoring, fault identification and troubleshooting guidance