WIND TURBINE FAULT DETECTION METHOD BASED ON DYNAMIC NEIGHBORHOOD INDEX RECONSTRUCTION
The changeable working condition is one of the main causes of false and missing alarms in wind turbine fault detection.For this purpose,a fault detection method based on dynamic coordination of neighborhood scale and threshold is proposed.The reconstruction indexes of stepped neighbor and state separation degree are defined to evaluate the ability of fault separation,on this basis,the iterative correction strategy of dynamic neighborhood scale is constructed.A fusion method of static component and dynamic component for threshold is proposed to suppress the false positives and missing positives caused by the abrupt change of working condition through dynamic neighborhood size and dynamic threshold.Ten common faults of megawatt wind turbines are used in the experiments and verified the proposed method can more effectively separate the abnormal state from the normal state and reduce the false alarm rate and missing false rate.
wind turbinesfault detectionreconstructioncomplex working conditionsdynamic neighborhood sizedynamic threshold
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