A novel fractal method for fault diagnosis and signal measurements

In this work, a wavelet fractal method is proposed by combining the fractal theory with a wavelet decomposition. The proposed method along with the correlation dimension acquired from the generic programming method is applied to characterize the experimental signals under three different conditions. Both methods show the obvious advantages in extracting characteristics from the signals under different conditions. By comparing the statistical data of such two methods, it can be concluded that the characteristics obtained from the wavelet fractal method have shown a high accuracy and thus this method provides a powerful strategy in the fault diagnosis for the practical applications.