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A New Method of Health Monitoring for Press Processing Using AE Sensor

음향방출센서를 이용한 프레스공정에서의 새로운 건전성 평가 연구

  • Jeong, Soeng-Min (Department of Future Convergence Engineering, Kongju National University) ;
  • Kim, JunYoung (Department of Future Convergence Engineering, Kongju National University) ;
  • Jeon, Kyung Ho (Department of Future Convergence Engineering, Kongju National University) ;
  • Hong, SeokMoo (Division of Mechanical & Automotive Engineering, Kongju National University) ;
  • Oh, Jong-Seok (Division of Mechanical & Automotive Engineering, Kongju National University)
  • 정성민 (공주대학교 미래융합공학과) ;
  • 김준영 (공주대학교 미래융합공학과) ;
  • 전경호 (공주대학교 미래융합공학과) ;
  • 홍석무 (공주대학교 기계자동차공학부) ;
  • 오종석 (공주대학교 기계자동차공학부)
  • Received : 2020.10.06
  • Accepted : 2020.11.20
  • Published : 2020.11.28

Abstract

This study developed the health monitoring method of press process using the acoustic emission (AE) sensor and high-pass filter. Also, the AE parameters such as ring-down count and peak amplitude are used. Based on this AE signal, the AE parameters were acquired and was utilized to detect the crack of the specimen. Since the defect detection is difficult due to noise and low magnitude of signal, the signal noise and press operation frequency were checked through the Short Time Fourier Transform(STFT) and damped. High-pass Filtering data was applied to AE parameters to select effective parameters. By using this signal processing techniques, the proposed AE parameters could improve the performance of defect detection in the press process.

본 연구에서는 프레스 시험 중 시편에서 발생하는 음향방출 신호와 신호필터링을 통해 시편의 건전성을 평가하는 연구를 진행하였으며, 실험결과를 통해 음향방출 진동횟수와 최대진폭 두 개의 음향방출 파라미터를 프레스 시편 건전성 판단에 적용하고자 한다. 프레스 장치를 이용한 구멍확장시험 중에는 시편에서 탄성파가 발생하며, 탄성파를 음향방출 센서를 통해 수집하였다. 이 신호를 바탕으로 음향방출 파라미터를 획득한 뒤, 시편의 크랙을 감지하는 연구를 진행하였다. 명확한 건전성 판단을 위해 STFT(Short Time Fourier Transform)와 고주파수 통과 필터(High-Pass Filter)를 이용하였다. 향후 본 연구에서 제안하는 신호 처리 기법 및 해당 파라미터를 활용한다면 프레스공정에서의 시편 건전성 평가 성능을 향상시킬 수 있을 것이라 생각된다.

Keywords

References

  1. D. H. Kim & W. K. Lee. (2010). A Judgment Algorithm of the Acoustic Signal for the Automatic Defective Manufactures Detection in Press Process. Journal of the Korean Society of Manufacturing Process Engineering, 9(3), 76-82.
  2. D. H. Kim, S. M. Park & W. K. Lee. (2010). Analysis of Various Acoustic Emission Signal for the Automatic Detection of Defective Manufactures in Press Process. Journal of the Korean Society of Manufacturing Process Engineering, 9(4), 14-25.
  3. E. Agletdinov, D. Merson & A. Vinogradov. (2019). A New Method of Low Amplitude Signal Detection and Its Application in Acoustic Emission. Applied Sciences, 10(1), 73. https://doi.org/10.3390/app10010073
  4. S. M. Jeong & J. S. Oh. (2020). Principle of AE sensor using piezoelectric material and its application to defect detection. Korean Society for Noise and Vibration Engineering(KSNVE), 30(2), 17-21.
  5. Jo. O. Lee, H. S. Ji & N. H. Ju. (2009). Principle and Application of Acoustic Emission Test. Korea Institute of Materials Science, 21(2), 156-164.
  6. J. K. Lee, Y. C. Park, S. P. Lee & J. H. Lee. (2006). Evaluation on Damage Behavior of Smart Composite using Elastic Wave. The Korean Society of Mechanical Engineers, 1124-1129.
  7. R. J. Comstock, D. K. Scherrer & R. D. Adamczyk. (2006). Hole expansion in a variety of sheet steels. Journal of materials engineering and performance, 15(6), 675-683. https://doi.org/10.1361/105994906X150830
  8. S. S. Han & H. Y. Lee. (2019). Study on Deformation Characteristics of Hole Expansion Test and Its Applicability. Transactions of Materials Processing, 28(3), 154-158 https://doi.org/10.5228/KSTP.2019.28.3.154
  9. C. Eun & Y. C. Lee. (2016). Compensation of the Non-linearity of the Audio Power Amplifier Converged with Digital Signal Processing Technic. Journal of the Korea Convergence Society, 7(3), 77-85. https://doi.org/10.15207/JKCS.2016.7.3.077
  10. G. W. Jin. (2017). A Study on the BGA Package Measurement using Noise Reduction Filters. Journal of the Korea Convergence Society, 8(11), 15-20. https://doi.org/10.15207/JKCS.2017.8.11.015
  11. S. W. Jo, S. K. Jung & H. T. Kim. (2020). Development of Battery Monitoring System Using the Extended Kalman Filter. Journal of the Korea Convergence Society, 11(6), 7-14. https://doi.org/10.15207/JKCS.2020.11.6.007
  12. C. Lu, P. Ding & Z. Chen. (2011). Time-frequency analysis of acoustic emission signals generated by tension damage in CFRP. Procedia Engineering, 23, 210-215. https://doi.org/10.1016/j.proeng.2011.11.2491
  13. D. Griffin & J. Lim. (1984). Signal estimation from modified short-time Fourier transform. IEEE Transactions on Acoustics, Speech, and Signal Processing, 32(2), 236-243. https://doi.org/10.1109/TASSP.1984.1164317
  14. H. K. Kwok & D. L. Jones. (2000). Improved instantaneous frequency estimation using an adaptive short-time Fourier transform. IEEE transactions on signal processing, 48(10), 2964-2972. https://doi.org/10.1109/78.869059
  15. M. A. Hamstad & J. Gary. (2002). A wavelet transform applied to acoustic emission signals: part 2: source location. In Journal of Acoustic Emission.
  16. J. K. Lee, Y. C. Park, S. P. Lee & J. H. Lee. (2006). Evaluation on Damage Behavior of Smart Composite using Elastic Wave: The Korean Society of Mechanical Engineers, 1124-1129.