Fault determination method and system for variable pitch system of wind turbine generator

Abstract

The invention relates to a fault determination method and system for a variable pitch system of a wind turbine generator. The fault determination method comprises the following steps of obtaining a variable pitch system dynamical model; according to the variable pitch system dynamical model, obtaining data after the fan variable pitch system breaks down; training a convolutional neural network according to the data after the fault occurs, and determining a trained convolutional neural network; obtaining a current pitch angle, a current pitch angle measurement value, a current main transmission shaft torque, a current actual rotating speed of a generator rotor and a current rotating speed measurement value of the generator; determining a currently predicted pitch angle according to the current pitch angle measurement value, the current main transmission shaft torque, the current actual rotating speed of the generator rotor, the current rotating speed measurement value of the generator and the trained convolutional neural network; and determining a fault diagnosis result of the fan variable pitch system according to the currently predicted pitch angle and the current pitch angle. According to the fault determination method and system for the variable pitch system of the wind turbine generator, the fault can be accurately and effectively detected and determined, and meanwhile, the change of the fault amplitude is accurately and effectively predicted.

Description

technical field [0001] The invention relates to the field of fault prediction of key equipment of wind turbines, in particular to a method and system for determining a fault of a pitch system of a wind turbine. Background technique [0002] In recent years, wind energy is currently the most concerned clean and renewable energy. The global wind energy is about 2.74×109MW. As far as China's exploitable wind energy reserves are concerned, the onshore wind energy reserves are about 2.53×109kW, and the offshore wind energy reserves are about 7.5×109kW, totaling 1010kW. Wind power generation is one of the most important forms of effectively utilizing wind energy. Due to the special installation of wind power equipment, for example, wind turbines are often installed in harsh environments such as mountains and seasides, and are vulnerable to pollution such as sand, dust, water mist, and freezing; on the other hand, wind power systems are often installed at high altitudes. Operatio...

AI Technical Summary

Problems solved by technology

[0004] The existing fault diagnosis methods cannot accurately predict the fault signals of the pitch angle sensor and the actuator of the pitch system in real time.

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