| The internal stator winding fault of synchronous generator, which is common and destructive, greatly affects the security of the generator and the power network. Therefore, it is important to detect the fault very effectively. While the detection for the internal stator winding fault in synchronous generator is always difficult. This paper has tried to apply a new method, i.e. fractal method and wavelet transform for the analysis of the fault.Fractal dimension is one of main factors of Fractal and characterizes the complicated degree and filling spatial degree of researched object. Wavelet transform has excellent localization nature in time and frequency domain, and it can change the time and frequency windows according to variation of signals'frequency. When a fault takes place in the internal stator winding of synchronous generator, the transient waves of voltage and current are different from the wave of normal signal. The variable trend of fractal dimension of a signal is related with its composition, which takes on shape-V. So it can clearly show whether there is fault. While different kind of fault maybe has many common characteristics each other, such as the internal stator winding fault of synchronous generator happens in different embranchment of one phase and in different phase. All kinds of fault cannot effectively be identified only by that result of fractal dimension.A signal transformed by wavelet has two different results. One is frequency analysis in different channels. The other is energy reduction with the increasing of scale. These are related to two factors of fractal dimension (the complicated degree and filling spatial degree). The fractal dimension of all kinds of signal transformed by wavelet is different. The different variable trend of fractal dimension can identify all kinds of fault in internal stator winding of synchronous generator after the fault signal is transformed by wavelet.
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