제조 부품 타격 음향신호 인식형 비파괴 품질 검사법
The Non-destructive Quality Test Method based on Acoustic Signal Recognition of the Tapping Object Parts
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초록
본 연구에서, 우리는 음향신호 인식을 기반으로 한 새로운 비파괴 전수검사 기법을 새로이 제안하였다. 이 기법은 각종 기계부품 제조업 분야에서 피검사물의 정상/불량을 판별하는 데 기여한다. 또한 가진기를 통해 검사 대상물의 표면을 일정 강도로 타격 후 발생하는 타격음 측정치의 공진 주파수 분석과 음향신호에 응용 가능한 패턴인식 알고리즘을 적용하였다. 제안한 방식에 의한 검사 실험에서 획득한 데이터를 수치해석으로 계산하여 제품의 불량 유/무 결과를 얻음으로써 보다 객관적이고 정확하며 신뢰성 있는 검사능력을 확인할 수 있었다. 향후 본 기술의 국산화에 관한 연구를 계속할 계획이다.
Abstract
The resonant acoustic method is a volumetric resonant inspection technique that measures the structural integrity of each part to detect defects, anomalies and inconsistencies on a component level. This technique automates easily. It eliminates human errors and subjectivity with fast throughput. Also it provides cost-effective inspection by minimal disruption to production and successes on the production lines of powder metal and cast parts. Resonant inspection measures the structural response of a part and evaluates it against the statistical variation from a control set of good parts to screen defects. Its volumetric approach tests the whole part, both for external and internal structural flaws or deviations, providing objective and quantitative results. This structural response is a unique and measurable signature defined by a component’s mechanical resonances. In this research, we propose a new method of the non-destructive quality test based on acoustic signal recognition. It helps to determine whether inspection object parts are defective and normal. It uses pattern recognition algorithm applicable to acoustic signal and resonant frequency analysis of the tapping sound measurement value, following of trippet tapping the surface of the inspection object parts with constant strength. We verified that it has inspection ability of the improve performance, accuracy, objective and reliability of the products through the numerical analysis processing method to the obtained data.
참고문헌 (15)
- K. G. Boving, "Non-destructive examination methods for condition monitoring" (2014), Elsevier Science
- A. Katunin, "Damage identification in aircraft composite structures: A case study using various non-destructive testing techniques" (2015), Elsevier Science
- R. I. Haque, "Optimization of capacitive acoustic resonant sensor using numerical simulation and design of experiment", Sensors, 15(4), pp.8945~8967 (2015)
- R. M. Hendrix, "Bending induced tuning of the resonant response of a flexible THz metamaterial device", 39th International Conference on Infrared (2014)
- V. Fokin, "Method for retrieving effective properties of locally resonant acoustic metamaterials", Physics Review B, 76(5), pp.144302~144305 (2007)
- H. Zhang, "Micromachined acoustic resonant mass sensor", Journal of Microelectromechanical Systems, 14(4), pp.699~706 (2005)
- Z. Fang, "Topology optimization for minimizing the resonant response of plates with constrained layer damping treatment", Shock and Vibration (2015)
- M. Xu, "HMM-based audio keyword generation, Advances in Multimedia Information Processing", PCM 2004: 5th Pacific Rim Conference on Multimedia (2004)
- M. Sahidullah, "Design, analysis and experimental evaluation of block based transformation in MFCC computation for speaker recognition", Speech Communication, 54(4), pp.543~565 (2012)
- D. L. Farley, "Implementation of a high-speed FPGA and DSP based FFT processor for improving strain demodulation" (2016), Bibliogov
- M. Gang, "Speech reconstruction from MFCC based on nonnegative and sparse priors", IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2015)
- 김지은, "MFCC를 이용한 GMM 기반의 음성", 혼합 신호 분류, 2013, pp.50(2), 185~192[DOI]
- M. N. Do, "Multidimensional filter banks and multiscale geometric representations", Signal Processing, 5(3), pp.157~264 (2012)
- L. Zhang, "Multidimensional perfect reconstruction filter banks: an approach of algebraic geometry", Multidimensional Systems and Signal Processing, 20(1) (2009)
- Y. M. Lu, "Multidimensional directional filter banks and surfacelets", IEEE Transactions on Image Processing, 16(4), pp.918~931 (2007)
