The invention relates to the field of
new energy wind power generation systems, in particular to a method for early warning and diagnosis of the temperature of a
main bearing of a wind
turbine generator. The method comprises the following steps that firstly,
wind power plant monitoring data is acquired; secondly, parameters related to the temperature of the
main bearing of the wind
turbine generator are obtained; thirdly, a normal temperature model of the
main bearing of the wind
turbine generator is established; fourthly, the theoretical value of the real-time normal temperature of the main bearing of the wind turbine generator is calculated, wherein the real-time values of the parameters related to the temperature of the main bearing of the wind turbine generator in the second step are selected from the real-
time data collected in the first step, the real-time values of the related parameters are input into a neural network trained in the third step, and the normal temperature valueof the main bearing of the wind turbine generator is generated; fifthly, whether the real-time temperature of the main bearing of the wind turbine generator is normal or not is judged. By means of themethod, faults of the main bearing of the wind turbine generator are effectively judged in advance, an extra sensor does not need to be installed, and the diagnosis precision and the diagnosis time advance are remarkably improved.