Wind turbine measurement and control system and measurement and control method based on edge computing and deep learning

Abstract

The invention discloses a wind turbine measurement and control system and measurement and control method based on edge computing and deep learning. The system includes a general server, an end sensor installed on the wind turbine, an end controller, an end server, and a main control of the wind turbine. The end sensor is located on the wind turbine. The position of the component to be monitored; the end controller is connected to the end sensor and the end server. The end controller stores the deep learning model. The processing results are stored in the end server and generate wind turbine control instructions; the end server is connected to the main server, and the main server is used to obtain the processing results through the end server and send the deep learning model to the end controller; the main control of the fan is connected to the end controller or the end server Obtain the fan control instruction and control the fan according to the instruction. The invention can control each blower fan in real time, quickly and independently, and the control of the wind turbine unit is more efficient and intelligent.

Description

technical field [0001] The invention relates to the technical field of wind power generation unit measurement and control, in particular to a wind power generation unit measurement and control system and measurement and control method based on edge computing and deep learning. Background technique [0002] During the development of wind turbines in the direction of intelligence, the requirements for condition monitoring of wind turbines are also continuously increasing. Compared with the past, the type and quantity of current wind turbine status monitoring points have increased significantly, and the installation of monitoring systems for blades, towers, foundations, bolts and other components has become very common. [0003] The current wind turbine monitoring system is mainly based on data collection and real-time status display. The next decision is made by manually reading the operating status. Although it can be operated remotely, it cannot be instant and fast. In addi...

AI Technical Summary

Problems solved by technology

[0003] The current wind turbine monitoring system is mainly based on data collection and real-time status display. The next decision is made by manually reading the operating status. Although it can be operated remotely, it cannot be instant and fast.

In addition, manual operation uses the same and single countermeasures for each unit, and it is impossible to coordinate the operation of the entire wind farm in combination with other wind turbines, which is likely to cause a certain loss of resources. Therefore, a more intelligent control method is needed to allow wind farms to operate reliably and efficiently, and to maximize the benefits of wind farms

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