Automatic expert integrated fault diagnosis system and diagnosis method for wind turbine generator system

Abstract

The invention discloses an automatic expert comprehensive fault diagnosis system and a diagnosis method for wind turbines, which include: a data acquisition module that collects relevant data of a main control unit and a vibration signal acquisition unit and transmits it to a fault diagnosis module; a fault diagnosis module that comprehensively uses The neural network knowledge and expert system module use forward reasoning and compare the parameter fluctuation values ​​obtained in real time with the data in the fault sample knowledge base to generate fault information in real time; the fault diagnosis module passes the diagnosed fault information through the human-machine interface module for output. This invention uses the main control unit to read parameters such as instantaneous power, rotation speed, propeller angle, cabin temperature, wind speed, oil temperature, yaw status and other parameters of the wind turbine to improve the accuracy of fault diagnosis, and uses a neural network expert system based on wavelet packet analysis Carry out automatic analysis and give operation and maintenance suggestions through the expert diagnosis system.

Description

technical field [0001] The invention relates to the technical field of wind power generation, in particular to an automatic expert comprehensive fault diagnosis system and a diagnosis method for a wind turbine. Background technique [0002] With the increasing shortage of conventional energy, the development and utilization of renewable energy will undoubtedly become the main direction of energy development in the future. At present, wind power generation technology has matured, and the installed capacity of wind power continues to expand. By the end of 2015, the installed capacity of wind power in China had exceeded 145.1GW. The focus of the wind power industry. [0003] The working environment of wind turbines is harsh, the wind speed is highly unstable, and the components of the wind turbines are easily damaged. However, the wind turbines are installed in remote mountainous areas and are high above the ground, making maintenance inconvenient. The condition monitoring and...

AI Technical Summary

Problems solved by technology

[0005] In the existing real-time monitoring system of fan operation status, through the analysis and processing of unit vibration and related signals, it can be judged whether the unit operation status is normal, and realize danger alarm and chain protection, but it cannot predict the possibility of a certain failure. When an abnormal situation occurs, the cause of the failure of the unit cannot be pointed out

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