Empirical Mode Decomposition Method And Its Application Research On Transformer's Condition Monitoring

At present, the requirement of failure information processing technique is growing gradually with the rapid development of electric power automatization. However the traditional signal processing technique has limitation in accuracy and veracity, truthless characteristic hampers the research on on-line condition monitoring and fault diagnosis for electrical equipment. So condition monitoring and fault diagnosis system based on modern signal processing plays more and more important role in accident prevention and stable operation of power system.In this dissertation, empirical mode decomposition method is studied. Besides, condition evaluation and fault diagnosis for electrical equipment using empirical mode decomposition method is discussed. The major contents are shown as follows:1 A new method of obtaining local characteristic of data based on empirical mode decomposition(EMD) is introduced. EMD separates the time series into a finite and small number of intrinsic mode functions(IMF), which is directly decomposed from time series and could reflect the intrinsic physical property of signal more clearly. Applying the Hilbert transform to IMF, the time-frequency-energy distribution is got. By comparing with wavelet transform, the power of this method is demonstrated.2 A method of forecasting non-stationary signal by model is developed, empirical mode decomposing data is extended using this method. According to nothing but the extrema inside observation data, envelope fitting can be got with error on the borders. The end effects will be serious along with empirical mode decomposition. Data extending method for handling the end effects of EMD is effective.3 A new method of envelope fitting for empirical mode decomposing databased on non-uniform B-spline curve is developed. Firstly, select cumulative chord length parameterization and computing the knots of B-spline. Secondly, determine control vertexes and control polygon. Then, B-spline interpolation curves are obtained. Envelope fitting based on non-uniform B-spline curve handles the incomplete envelope effects of EMD.4 The vibration mechanism of transformer body is discussed. Faults of the winding and core mostly lead to transformer accident, especially delitescent faults would lead to casualty with cumulating result of vibration when transformers are operating. Through research on the relationship between the conditions of winding and core and their vibration, a new method of obtaining the connection between the energy distribution characteristic and the conditions of transformer's core and winding based on EMD is developed. Associating with forecasting vibration data beyond observation series by model, envelope fitting of data inside and outside observation series based on non-uniform B-spline curve is got. EMD can use this envelope for obtaining intrinsic mode functions. EMD based on forecasting model and B-spline interpolation curves is good for evaluating conditions and diagnosing failures of power transformers.