基于BPNN的封严涂层孔隙分布均匀性超声表征

doi:10.7527/S1000-6893.2021.25294

Abstract

Abstract: The propagation behavior of ultrasonic wave is complex in multi-phase heterogeneous abradable seal coating, so it is difficult to extract effective ultrasonic characteristics and describe the relationship between the characteristics and microstructure distribution uniformity. The BP Neural Network (BPNN) combined with wavelet transform is proposed to quantitatively characterize pore distribution uniformity of abradable seal coating through the ultrasonic testing technique. Based on the statistical method and the random medium theory, random multiphase medium models for AlSi-Polyester (AlSi-PHB) seal coating were established, whose pore distributions were adjusted by varying autocorrelation lengths. Two uniformity parameters, absolute slope, and uniformity length were extracted to quantitatively describe pore distribution uniformity using the multi-scale analysis of area fraction. The time domain, frequency domain, and time-frequency domain attenuation coefficients were extracted from simulated ultrasonic signals. Correlations between absolute slope, uniformity length and the attenuation coefficients were explored. The BPNN with attenuation coefficients as the inputs was applied for training and prediction of absolute slope and uniformity length. The results show that when porosity was 5%, as autocorrelation lengths increased from 11 μm to 26 μm, absolute slope decreased from 0.86 to 0.76 and uniformity length increased from 550 μm to 6 785 μm, which indicates that the pore distribution uniformity gets worse. The time-frequency domain attenuation coefficients and the uniformity parameters were the most correlative, and the determination coefficients of the predicted absolute slope and uniformity length through BPNN were 0.97 and 0.98, respectively, which are the most accurate among the prediction results of three kinds of attenuation coefficients. The proposed method provides an effective way for quantitative characterization of distribution uniformity of multi-phase heterogeneous coatings.

Key words: seal coating, pore, distribution uniformity, ultrasonic quantitative characterization, BP neural network

CLC Number:

V257
TB553

DONG Zhenyi, LIN Li, LEI Mingkai, MA Zhiyuan. Ultrasonic quantitative characterization of pore distribution uniformity of seal coating based on BPNN[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2022, 43(5): 425294-425294.

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Ultrasonic quantitative characterization of pore distribution uniformity of seal coating based on BPNN

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