Acoustic emission recognition using fuzzy entropy

Acoustic emission (AE) is a new approach to rub-impact recognition. The fuzzy entropy is introduced to analyze the effectiveness of the features, and the method of fuzzy comprehensive evaluation combining effectiveness analysis is proposed to acoustic emission recognition. Duration, average amplitude, maximum amplitude, dynamic range of amplitude and the first four nodes energies of the reconstructing signal by wavelet packet decomposition are chosen as the characteristic parameters of rub-impact AE, and then, the membership function of each characteristic parameter belonged to different rub-impact mode based on Gaussian model is obtained from the training samples respectively. The fuzzy relation matrix of characteristic parameters and modes is calculated with membership functions. According to different effectiveness in recognizing AE signal by the characteristic parameters, a algorithm based on fuzzy entropy is presented to calculate effectiveness coefficient. In the end, the integrated evaluate fuzzy sets is calculated with the new fuzzy relation matrix modified by effectiveness coefficient, and the mode which has the most degree of membership is chosen as the recognition results. The experiments indicate that the integrated fuzzy evaluation is effective in analysis and recognition of rub-impact AE.