A fault detection method based on dynamic peakvalley limit under the non-steady conditions

The multivariate statistical methods are commonly used to fault detection through a straight limit line given by the HotellingT². However, the traditional straight limit line is difficult to detect the fault effectively under the non-steady conditions, which the false alarm rate and missing alarm rate are high. For these problems above, a fault detection method based on dynamic peak-valley limit is proposed in this paper. The proposed method introduces relative principal component analysis to carry out the dimension reduction, and extracts principal components, then adopts moving least squares to preprocess PCs to obtain the fitting curve which is called peak-valley curve, finally uses peak and valley points to construct a control limit combined the traditional straight limit line. At the end, the proposed method is applied to wind power generation system, and the simulation results verify the effectiveness of the proposed method.