Power station auxiliary machine fault diagnosis method and system based on machine learning model

The embodiment of the invention provides a power station auxiliary machine fault diagnosis method and system based on a machine learning model. The method comprises the steps of determining an operation vector of a power station auxiliary machine based on a time window; based on the operation vector, judging whether a historical reference vector meeting a preset condition exists in a historical database corresponding to the power station auxiliary equipment or not; the preset condition is that the vector similarity between the operation vector and the historical reference vector is not lower than a preset threshold value; in response to existence of the historical reference vector meeting the preset condition, determining fault diagnosis information of the power station auxiliary machine based on the equipment operation information corresponding to the historical reference vector; in response to the situation that the historical reference vector meeting the preset condition does not exist, processing the oper