DOI QR코드

DOI QR Code

비정상 AE 진동감시 신호의 에너지 분포특성과 시간-주파수 해석

Energy Distribution Characteristics of Nonstationary Acoustic Emission Burst Signal Using Time-frequency Analysis

  • 정태건 (건국대학교 기계공학부)
  • 투고 : 2012.02.08
  • 심사 : 2012.03.02
  • 발행 : 2012.03.20

초록

Conventional Fourier analysis can give only limited information about the dynamic characteristics of nonstationary signals. Instead, time-frequency analysis is widely used to investigate the nonstationary signal in detail. Several time-frequency analysis methods are compared for a typical acoustic emission burst generated during the impact between a ferrite ceramic and aluminum plate. This AE burst is inherently nonstationary and random containing many frequency contents, which leads to severe interference between cross terms in bilinear convolution type distributions. The smoothing and reassignment processes can improve the readability and resolution of the results. Spectrogram and scalogram of the AE burst are obtained and compared to get the characteristics information. Renyi entropies are computed for various bilinear time-frequency transforms to evaluate the randomness. These bilinear transforms are reassigned by using the improved algorithm in discrete computation.

키워드

참고문헌

  1. Feng, Y. and Schlindwein, F. S., 2009, Normalized Wavelet Packets Quantifiers for Condition Monitoring, Mechanical Systems and Signal Processing, Vol. 23, pp. 712-723. https://doi.org/10.1016/j.ymssp.2008.07.002
  2. Ebersbach, S. and Peng, Z., 2008, Expert System Development for Vibration Analysis in Machine Condition Monitoring, Expert Systems with Applications, Vol. 34, pp. 291-299. https://doi.org/10.1016/j.eswa.2006.09.029
  3. Peng, Z. K. and Chu, F. L., 2004, Application of the Wavelet Transform in Machine Condition Monitoring and Fault Diagnostics: A Review with Bibliography, Mechanical Systems and Signal Processing, Vol. 18, pp. 199-221. https://doi.org/10.1016/S0888-3270(03)00075-X
  4. Zhang, J., Li, R. X., Han, P., Wang, D. F. and Yin, X. C., 2003, Wavelet Packet Feature Extraction for Vibration Monitoring and Fault Diagnosis of Turbo-generator, Proceedings of the Second International Conference on Machine Learning and Cybernetics, pp. 76-80.
  5. Jeong, T. G., 2006, Study on the Nonstationary Behavior of Slider Air Bearing Using Reassigned Time-frequency Analysis, Transactions of the Korean Society for Noise and Vibration Engineering, Vol. 16, No. 3, pp. 255-262. https://doi.org/10.5050/KSNVN.2006.16.3.255
  6. Jeong, T. G., 2007, Study on the Nonlinearity of the Nonstationary Impulse Signal Using Rea- ssigned Time-frequency Analysis, Lecture Notes in Computer Science, Vol. 4706, Part II, pp. 873-882.
  7. Kodera, K., De Villedary, C. and Gendrin, R., 1976, A New Method for the Numerical Analysis of Nonstationary Signals, Physics of the Earth and Planetary Interiors, Vol. 12, pp. 142-150. https://doi.org/10.1016/0031-9201(76)90044-3
  8. Papandreou-Suppappola, A., 2003, Applications in Time-frequency Signal Processing, CRC Press, Florida.