• 제목/요약/키워드: NON-DESTRUCTIVE DETECTION

검색결과 286건 처리시간 0.024초

구조물의 비접촉 비파괴 검사를 위한 레이저 초음파법 적용 (Laser-Ultrasonics Application for Non-Contact and Non-destructive Evaluation of Structure)

  • 김재열;송경석;양동조
    • 한국공작기계학회논문집
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    • 제14권4호
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    • pp.49-54
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    • 2005
  • Measuring defects on the inside and on the surface of a steel structure is very important technology in order to predict the life span of the structure. In particular, a place with a high probability that it may contain defects is a welded part and it is very important to check defects in the part, absence/presence of non-uniform substances, its shape, and the location. Many non-destructive tests can be applied, but the ultrasonic flow detection test is widely used with some advantages. The ultrasonic flow detection test, however, cannot be applied when there is a problem by a contact medium between PZT and a specimen, in case of a small and complicated shape or a moving object or when the specimen is hot. In this study, to solve the problems of the contact ultrasonic flow detection test, the non-contact ultrasonic flow detection test for sending/receiving ultrasonic waves using lasers was described. I intended to develop a non-destructive detection system applying the laser application ultrasonic test to a steel structure by detecting the defects inside of and on the surface of the specimen.

A Review on Meat Quality Evaluation Methods Based on Non-Destructive Computer Vision and Artificial Intelligence Technologies

  • Shi, Yinyan;Wang, Xiaochan;Borhan, Md Saidul;Young, Jennifer;Newman, David;Berg, Eric;Sun, Xin
    • 한국축산식품학회지
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    • 제41권4호
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    • pp.563-588
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    • 2021
  • Increasing meat demand in terms of both quality and quantity in conjunction with feeding a growing population has resulted in regulatory agencies imposing stringent guidelines on meat quality and safety. Objective and accurate rapid non-destructive detection methods and evaluation techniques based on artificial intelligence have become the research hotspot in recent years and have been widely applied in the meat industry. Therefore, this review surveyed the key technologies of non-destructive detection for meat quality, mainly including ultrasonic technology, machine (computer) vision technology, near-infrared spectroscopy technology, hyperspectral technology, Raman spectra technology, and electronic nose/tongue. The technical characteristics and evaluation methods were compared and analyzed; the practical applications of non-destructive detection technologies in meat quality assessment were explored; and the current challenges and future research directions were discussed. The literature presented in this review clearly demonstrate that previous research on non-destructive technologies are of great significance to ensure consumers' urgent demand for high-quality meat by promoting automatic, real-time inspection and quality control in meat production. In the near future, with ever-growing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.

Flaw Detection in Ceramics using Hough transform and Least squares

  • Hong, Dong-Jin;Cha, Eui-Young
    • 한국컴퓨터정보학회논문지
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    • 제20권10호
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    • pp.23-29
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    • 2015
  • In this paper, we suggest a method of detecting defects by applying Hough transform and least squares on ceramic images obtained from non-destructive testing. In the ceramic images obtained from non-destructive testing, the background area, where the defect does not exist, commonly show gradual change of luminosity in vertical direction. In order to extract the background area which is going to be used in the detection of defects, Hough transform is performed to rotate the ceramic image in a way that the direction of overall luminosity change lies in the vertical direction as much as possible. Least squares are then applied on the rotated image to approximate the contrast value of the background area. The extracted background area is used for extracting defects from the ceramic images. In this paper we applied this method on ceramic images acquired from non-destructive testing. It was confirmed that extracted background area could be effectively applied for searching the section where the defect exists and detecting the defect.

다변량 로지스틱 회귀분석을 이용한 증기발생기 전열관 ODSCC의 POD곡면 분석 (Evaluation of the Probability of Detection Surface for ODSCC in Steam Generator Tubes Using Multivariate Logistic Regression)

  • 이재봉;박재학;김홍덕;정한섭
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회A
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    • pp.250-255
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    • 2007
  • Steam generator tubes play an important role in safety because they constitute one of the primary barriers between the radioactive and non-radioactive sides of the nuclear power plant. For this reason, the integrity of the tubes is essential in minimizing the leakage possibility of radioactive water. The integrity of the tubes is evaluated based on NDE (non-destructive evaluation) inspection results. Especially ECT (eddy current test) method is usually used for detecting the flaws in steam generator tubes. However, detection capacity of the NDE is not perfect and all of the "real flaws" which actually existing in steam generator tunes is not known by NDE results. Therefore reliability of NDE system is one of the essential parts in assessing the integrity of steam generators. In this study POD (probability of detection) of ECT system for ODSCC in steam generator tubes is evaluated using multivariate logistic regression. The cracked tube specimens are made using the withdrawn steam generator tubes. Therefore the cracks are not artificial but real. Using the multivariate logistic regression method, continuous POD surfaces are evaluated from hit (detection) and miss (no detection) binary data obtained from destructive and non-destructive evaluation of the cracked tubes. Length and depth of cracks are considered in multivariate logistic regression and their effects on detection capacity are evaluated.

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비파괴 검사를 이용한 항공 갑판의 결함 검출 (Detection of Flaws in Air Deck using Non-Destructive Testing)

  • 김광백;조재현
    • 한국정보통신학회논문지
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    • 제15권9호
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    • pp.1865-1870
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    • 2011
  • 본 논문에서는 비파괴 검사를 통하여 얻어진 항공 갑판 영상에서, 조직의 결함의 정도를 자동으로 검출하는 방법을 제안한다. 먼저 비파괴 검사를 통하여 얻어진 항공 갑판 영상에서 감마상관 변환과 7${\times}$7 소벨 마스크와 13${\times}$13 소벨 마스크를 각각 적용하여 윤곽선을 추출하고 추출된 윤곽선 영역을 평활화와 평균 이진화 기법을 적용하여 영상을 보정한다. 마지막으로 보정된 영상에서 침식 연산과 팽창 연산을 이용하여 잡음을 제거한 후, 라벨링 기법을 적용하여 항공 갑판의 결함 영역을 추출한다. 실험 결과에서, 항공 갑판에서 결함을 추출하는데 기존의 방법보다 효과적인 것을 확인하였다.

A non-destructive method for elliptical cracks identification in shafts based on wave propagation signals and genetic algorithms

  • Munoz-Abella, Belen;Rubio, Lourdes;Rubio, Patricia
    • Smart Structures and Systems
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    • 제10권1호
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    • pp.47-65
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    • 2012
  • The presence of crack-like defects in mechanical and structural elements produces failures during their service life that in some cases can be catastrophic. So, the early detection of the fatigue cracks is particularly important because they grow rapidly, with a propagation velocity that increases exponentially, and may lead to long out-of-service periods, heavy damages of machines and severe economic consequences. In this work, a non-destructive method for the detection and identification of elliptical cracks in shafts based on stress wave propagation is proposed. The propagation of a stress wave in a cracked shaft has been numerically analyzed and numerical results have been used to detect and identify the crack through the genetic algorithm optimization method. The results obtained in this work allow the development of an on-line method for damage detection and identification for cracked shaft-like components using an easy and portable dynamic testing device.

Detection of Subsurface Defects in Metal Materials Using Infrared Thermography; Image Processing and Finite Element Modeling

  • Ranjit, Shrestha;Kim, Won Tae
    • 비파괴검사학회지
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    • 제34권2호
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    • pp.128-134
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    • 2014
  • Infrared thermography is an emerging approach to non-contact, non-intrusive, and non-destructive inspection of various solid materials such as metals, composites, and semiconductors for industrial and research interests. In this study, data processing was applied to infrared thermography measurements to detect defects in metals that were widely used in industrial fields. When analyzing experimental data from infrared thermographic testing, raw images were often not appropriate. Thus, various data analysis methods were used at the pre-processing and processing levels in data processing programs for quantitative analysis of defect detection and characterization; these increased the infrared non-destructive testing capabilities since subtle defects signature became apparent. A 3D finite element simulation was performed to verify and analyze the data obtained from both the experiment and the image processing techniques.

웨이브렛 평면 AR 모델을 이용한 초음파 비파괴 검사의 스펙클 잡음 감소 및 결함 검출 (Speckle Noise Reduction and Flaw Detection of Ultrasonic Non-destructive Testing Based on Wavelet Domain AR Model)

  • 이영석;임래묵;김덕영;신동환;김성환
    • Journal of Welding and Joining
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    • 제17권6호
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    • pp.100-107
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    • 1999
  • In this paper, we deal with the speckle noise reduction and parameter estimation of ultrasonic NDT(non-destructive test) signals obtained during weld inspection of piping. The overall approach consists of three major steps, namely, speckle noise analysis, proposition of wavelet domain AR(autoregressive) model and flaw detection by proposed model parameter. The data are first processed whereby signals obtained using vertical and angle beam transducer. Correlation properties of speckle noise are then analyzed using multiresolution analysis in wavelet domain. The parameter estimation curve obtained using the proposed model is classified a flaw in weld region where is contaminated by severe speckle noise and also clear flaw signal is obtained through CA-CFAR threshold estimator that is a nonlinear post-processing method for removing the noise from reconstructed ultrasonic signal.

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풍력 발전용 블레이드 접합부의 결함 검출을 위한 일정가압 메커니즘 설계 및 실험 (A Design and Experiment of Pressure and Shape Adaptive Mechanism for Detection of Defects in Wind Power Blade)

  • 임선;임승환;정예찬;지수정;남문호
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제17권3호
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    • pp.224-235
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    • 2017
  • Purpose: Reliability is the most important factor to detect defects as wind turbines are deployed in large blades. The methods of detecting defects are various, such as non-destructive inspection and thermal imaging inspection. We propose the phased array ultrasonic testing method of non-destructive testing. Methods: We propose the active pressure mechanism for wind power blade. The phase array ultrasonic inspection method is used for fault detection inner blade surface. Controlled pressure of mechanism with respect to z-axis is important for guarantee the result of phase array ultrasonic inspection. The model based control and proposed mechanism are utilized for overall system stability and effectiveness of system. Result: The result of proposed pressure mechanism B is more stable than A. Convergence speed is also faster than A. Conclusion: We confirmed the performance of the proposed constant pressure mechanism through experiments. Non-destructive testing was applied to the specimen to confirm the reliability of detecting defects.

Ultrasonic Flaw Detection in Composite Materials Using SSP-MPSD Algorithm

  • Benammar, Abdessalem;Drai, Redouane
    • Journal of Electrical Engineering and Technology
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    • 제9권5호
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    • pp.1753-1761
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    • 2014
  • Due to the inherent inhomogeneous and anisotropy nature of the composite materials, the detection of internal defects in these materials with non-destructive techniques is an important requirement both for quality checks during the production phase and in service inspection during maintenance operations. The estimation of the time-of-arrival (TOA) and/or time-of-flight (TOF) of the ultrasonic echoes is essential in ultrasonic non-destructive testing (NDT). In this paper, we used split-spectrum processing (SSP) combined with matching pursuit signal decomposition (MPSD) to develop a dedicated ultrasonic detection system. SSP algorithm is used for Signal-to-Noise Ratio (SNR) enhancement, and the MPSD algorithm is used to decompose backscattered signals into a linear expansion of chirplet echoes and estimate the chirplet parameters. Therefore, the combination of SSP and MPSD (SSP-MPSD) presents a powerful technique for ultrasonic NDT. The SSP algorithm is achieved by using Gaussian band pass filters. Then, MPSD algorithm uses the Maximum Likelihood Estimation. The good performance of the proposed method is experimentally verified using ultrasonic traces acquired from three specimens of carbon fibre reinforced polymer multi-layered composite materials (CFRP).