Fault Warning And Diagnosis Research Of Wind Turbine Based On Order Analysis

As the global dwindling fossil resources and the worsening environment, the demand for renewable clean energy is growing as well as the development of new energy. In recent years, wind power has become the world’s fastest growing new energy. The problem of large-scale wind power planning process is large increase fault of wind power plant, and the extension of wind field location to the beach and sea results in more forms failure of wind machine. At the same time, the wind power enterprise investment return expectations index of wind turbines are also rising. So, the timely and effective fault analysis and diagnosis of wind turbines is imminent.For volatility, intermittent operation characteristics of wind turbines, the paper uses order analysis technology, transforms the signal of different intervals of time domain into the uniformly-spaced angle domain, checks and balances the nonlinear signal caused by the unit operation instability, analysis and calculates the domain signal through dimensionless factors including kurtosis index, skewness factor, repetitive factor, conducts chain code editor according to the change trend of each dimensionless factor value, makes fault early warning analysis and finds out failure of wind turbines, makes Fourier transform of the domain data signals, analysis the relationship of signal amplitude and order of each working condition, diagnosis unit fault mode accurately, develops integrated wind turbine condition monitoring equipment based on technical theory, gets the correct effect with application of power plant, achieves the purpose of condition monitoring and fault diagnosis of wind power unit in the true sense.The paper embarks from the practical problems, overcomes the objective problem of wind turbines through effective theory and method, ensures the safe operation of the unit to the greatest extent. In ensuring accurate diagnosis of real failure, the paper achieves function of the prediction of unit early failure, avoids further deterioration of the unit failure, improves the operational capacity of wind farm to a certain extent, reduces unnecessary economic losses.