Calculation method applied to multi-parameter fault prediction and judgment indexes of wind generating set

Abstract

The invention relates to a calculation method applied to a multi-parameter fault prediction and judgment indexes of a wind generating set, belonging to the technical field wind power generation. The method comprises the following steps: (1) collecting and processing of historical operation data of the wind generating set; (2) carrying out fault characteristic selection of the wind generating set, namely carrying out characteristic selection on faults of key components of the wind generating set, and reasonably selecting a fault characteristic quantity according to the weights of various related parameters; (3) modeling by a nonlinear method, namely carrying out modeling by the nonlinear method and determining a fault prediction model; and (4) carrying out combination of judgment indexes and fault prediction. According to the method provided by the invention, multiple characteristic parameters are combined again according to the linear proportion of the weights to obtain the fault prediction and comprehensive judgment indexes, so that the fault prediction accuracy is improved.

Description

technical field [0001] The invention relates to a fault prediction method for a wind power generating set, in particular to a calculation method for a multi-parameter fault prediction judgment index applied to a wind generating set. It belongs to the technical field of wind power generation. Background technique [0002] As an emerging clean energy power generation method, wind power generation is not yet mature in technology, and frequent failures of wind turbines seriously affect its safe and reliable operation. [0003] In order to discover the potential failures of the unit in time and formulate a reasonable maintenance and repair plan, the fault prediction technology of wind turbines has gradually entered the research field of scholars. [0004] Due to the complex working conditions and strong fluctuations of wind turbines, it is difficult to approximate and describe them through specific functional forms in the modeling process. Therefore, nonlinear mapping methods ar...

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Problems solved by technology

[0014] Although this method takes the weight into account, the model has many uncertainties: first, the working parameters and thresholds are obtained based on experience, and there is no definite standard, and deviations will inevitably occur; in addition, the calculation method of the weight is mainly based on the working parameters in The amount of change when a fault occurs, due to the large number of wind turbine components, complex structure and function, there is a delay in the change of parameters, and the delay time is different, so there is a large error in the weight calculation; at the same time, this weight calculation method lacks rigorous Theoretical basis, which affects the accuracy of the fault early warning model

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