The health of the hydroelectric generator determines the safe, stable, and reliable operation of the hydropower station. In order to keep the hydroelectric generator in a better state of health and avoid accidents, it is crucial to detect its faults. In recent years, fault detection methods based on sound and vibration signals have gradually become research hotspots due to their high sensitivity, achievable continuous dynamic monitoring, and easy adaptation to complex environments. Therefore, this paper is a supplement to the existing state monitoring and fault diagnosis system of the hydroelectric generator; it divides the hydroelectric generator into two significant parts: hydro-generator and hydro-turbine, and summarizes the research and application of fault detect technology based on sound signal vibration in hydroelectric generator and introduces some new technology developments in recent years, and puts forward the existing problems in the current research and future development directions, and it is expected to provides some reference for the research on fault diagnosis of the hydroelectric generator.
In this paper, a mixed H 2 /H ∞ robust control strategy that considers the weights of the H 2 and H ∞ norm in the optimization process is proposed, and it is used to solve the load frequency control (LFC) problem of the micro-grid (MG). The MG load frequency model established in this paper includes battery energy storage system (BESS), fuel cell (FC), wind turbine (WT), photo-voltaic (PV), and diesel engine generator (DEG). The optimal mixed H 2 /H ∞ robust controller takes the minimum square integral of the system's frequency fluctuation as the goal of control optimization by integrating the robust performance expressed by the H 2 /H ∞ two norms. The hybrid particle swarm optimization and gravitational search algorithm with chaotic map algorithm (CPSOGSA) is used to optimize the weight value reflecting the H 2 and H ∞ performance of the system and the evaluation function's weighting matrix of the output performance so that the controller can reach the optimum under the constraints. Simulation experiments show that the robust controller designed by the proposed method has better dynamic performance when compared with H ∞ robust controller, H 2 robust controller, and traditional H 2 /H ∞ robust controller, and the results are very satisfactory.INDEX TERMS Load-frequency control, Islanded micro-grid, Intelligent H 2 /H ∞ robust control, Intelligent optimization algorithm
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