2results about How to "Overcoming Application Limitations" patented technology

The invention relates to a wind power plant active yaw control method suitable for a field group situation, and the method comprises the steps: obtaining the wind turbine data of each wind turbine in a target wind power plant and a surrounding wind power plant, and the wind turbine data comprises the coordinate position information; acquiring inflow data of current inflow air every preset time, wherein the inflow data comprises wind speed information, wind direction information and turbulence intensity; calculating the relative position relation between the wind turbine i and the downwind wind turbine j based on the coordinate position information in combination with the wind direction information of the inlet wind; based on the relative position relation and a preset wake flow expansion rate threshold value, whether the wind turbine j is within the wake flow influence range of the wind turbine i or not is judged; the yaw angle of the free wind turbine in the target wind power plant is set to be 0, the yaw angles of the other wind turbines except the free wind turbine in the target wind power plant serve as optimization variables, the maximization of the output power of the target wind power plant serves as an optimization target, and the yaw angles of all the wind turbines in the target wind power plant under the current inflow wind are determined.

A kind of ship power condenser system fault detection method based on multiscale feature fusion, the present application relates to ship power condenser system fault detection method based on multiscale feature fusion, belongs to ship power system fault diagnosis and safety monitoring field.The present application aims to solve the problem of insufficient detection accuracy and high false alarm rate of traditional fault diagnosis method.Process is as follows:step one, obtain the input and output information of condenser system;Step two, construct multiscale feature extraction model;Step three, obtain trained multiscale feature extraction model and parameters;Step four, input the online data of condenser system into trained multiscale feature extraction model, and trained multiscale feature extraction model outputs the predicted value of condenser liquid level and vacuum degree;Residual generator obtains online prediction error signal based on predicted value;Step five, fault diagnosis based on online prediction error.