Construction and Application of Remote Intelligent Monitoring System for Hydropower Station Operation and Maintenance Based on Big Data
In order to address the challenges of operation and maintenance in remote mountainous hydropower stations,a remote intelligent monitoring system for hydropower station operation and maintenance is designed and developed based on big data,cloud services,sensors,and artificial intelligence technology.The system monitors on-site equipment through sensors and then decomposes and processes the complex vibration signals collected on-site using the Local Mean Decomposition(LMD)method.Finally,fault diagnosis is performed using the Elman neural network expert system,enabling remote monitoring,control,and fault diagnosis functions.Under the design condition of 100 concurrent users,the system has a CPU occupancy rate of only 11.7%and consumes 395.8GB of network traffic per month,well below the designed network traffic of 1000GB.The average response time is only 3.3ms.The system significantly reduces the workload of maintenance personnel,improves fault diagnosis efficiency,and reduces maintenance costs,achieving good application results in practical engineering.
operation and maintenance of hydropower stationremote intelligent monitoring systemlocal mean decomposition methodElman neural networkfault diagnosis
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