Detection Of Artificial Defects Research Articles

High precision detection of artificial defects in additively manufactured Ti6Al4V alloy via laser ultrasonic testing

Laser powder bed fusion (LPBF) is a cutting-edge metal additive manufacturing technology with promising applications in aerospace, biomedicine, and industrial automation. Its ability to fabricate intricate geometric shapes, achieve high surface precision, and deliver comprehensive results renders it highly advantageous. In LPBF process, several factors such as the interference of laser processing fluctuations, rapid cooling rate, and environmental gas, contribute to the initiation and expansion of defects including pores and cracks, limiting the application of LPBF components. Laser ultrasonic testing (LUT) is a promising non-destructive evaluation method that can accurately detected defects in LPBF manufactured components by non-contact generation and detection. In this paper, a multi-physical field LUT model for the pores and cracks in LPBF additively manufactured Ti6Al4V alloy is proposed. The interaction of ultrasound with defects produces defect reflection echo wave, diffracted wave, and transmission wave. The transmission and diffraction phenomena occur in the longitudinal sound waves at defects. Furthermore, the echo wave reflected at crack exhibited enhanced prominence and an irregular shape. Clear differences were observed in the effects of laser ultrasonic detection on different defect types, pore depths and sizes. Finally, the LUT technology achieved the detection of 90 μm pore defects in LPBF manufactured Ti6Al4V alloy.

Automatic estimation of surface and probe location for 3D imaging with bidimensional arrays

Ultrasound imaging for Non Destructive Testing is frequently performed in an immersion setup, where water is used as coupling medium between the probe and the component under test. For the computation of the time delays needed for beam-forming, the shape of the component surface and probe location and orientation (PLO) must be known. In this work we develop methods for the automatic detection of the surface and the estimation of PLO for 2D array probes. In particular, the methods developed apply to three types of elementary surfaces which are usually found in industrial and structural components: planes, cylinders and spheres. The methods use the measured surface echoes Time of Flight (TOF) to fit parametric models based on ray propagation and reflection on the surface, giving the coordinates and Euler angles that define the PLO relative to the component under test. Validation experiments with four test specimens representing the three types of surfaces are presented . The accuracy and precision of estimated PLO coordinates and angles are analyzed, and a Total Focusing Method (TFM) imaging example is shown achieving a correct detection of artificial defects in the component for a different PLOs.

Temperature and geometry impact on defect detection and sizing

Increasing requirements to minimize the frequency and duration of shutdowns of nuclear power plants have led to the need to address the implementation of ultrasonic testing of welded pipe connections at operating temperature. In practice, the pipes are made of carbon and stainless steel. Laboratory ultrasound tests were performed on two types of test pieces with different geometry and with homogeneous and heterogenous welds. The measurement was done within a temperature range of 50°C to 200°C in increment of 50°C. The aim of the performed measurements was to verify the detection of artificial defects created by electric discharge machining (EDM) in the root area of the weld on the carbon steel side by a selected test system and an impact of the change in focal laws (FLs) due to temperature on sizing. Together with this was evaluated the influence of elevated temperature on the determination of defect dimensions and impact of the test system, including ultrasonic, cooling, and handling subsystems for detection, sizing and using in the limited space of nuclear power plants. An inspection procedure and a safe workflow were created ss part of the testing. Both procedures were necessary for testing at elevated temperatures from the point of view of occupational safety and for carrying out individual test steps to maintain the repeatability of testing. The inspection procedure was subsequently qualified.

Non-contact ultrasonic inspection by Gas-Coupled Laser Acoustic Detection (GCLAD)

Gas-Coupled Laser Acoustic Detection (GCLAD) is an ultrasonic, non-contact detection technique that has been recently proven to be applicable to the inspection of mechanical components. GCLAD response raises as the intersection length between the probe laser beam and the acoustic wavefront propagating in the air increases; such feature differentiates the GCLAD device from other optical detection instruments, making it a line detection system rather than a point detector. During the inspection of structures mainly extending in two dimensions, the capability to evidence presence of defects in whichever point over a line would enable moving the emitter and the detector along a single direction: this translates in the possibility to decrease the overall required time for interrogation of components compared to point detectors, as well as generating simpler automated monitoring layouts. Based on this assumption, the present study highlights the possibility of employing the GCLAD device as a line inspection tool. To this end, preliminary concepts are provided allowing maximization of the GCLAD response for the non-destructive testing of components which predominantly extend in two dimensions. Afterwards, the GCLAD device is employed in pulse-echo mode for the detection of artificial defects machined on a 12 mm-thick steel plate: the GCLAD probe laser beam is inclined to be perpendicular to the propagation direction of the airborne ultrasound, generated by surface acoustic waves (SAWs) in the solid which are first reflected by the defect flanks and subsequently refracted in the air. Numerical results are provided highlighting the SAW reflection patterns, originated by 3 mm deep surface and subsurface defects, that the GCLAD should interpret. The subsequent experimental campaign highlights that the GCLAD device can identify echoes associated with surface and subsurface defects, located in eight different positions on the plate. B-scan of the component ultimately demonstrates the GCLAD performance in accomplishing the inspection task.

Rail Surface Defect Detection and Analysis Using Multi-Channel Eddy Current Method Based Algorithm for Defect Evaluation

The railroad rail support trains and contributes to their operation. Internal and surface defects occur on the rail due to various combinations of causes including fatigue loading and cyclic tension and compression among others from the deterioration of the rail along with the temperature differences of seasonal changes. Surface defects such as head check, shelling, and squats start out in the rail head and become internal defects due to poor maintenance, ultimately resulting in rail failure. In order to prevent rail failure, it is important that defects are identified through nondestructive evaluation (NDE) in advance and to carry out maintenance techniques including grinding. NDE methods include MFL, EMAT, and ECT, and among these, the ECT method is a representative method with excellent detection sensitivity that nondestructively inspects metal surfaces such as rails and pipes using an electromagnetic field. Also, since the defect signal is obtained as an electrical signal, the depth, length, and width of defects can be assessed using a defect evaluation algorithm. This study investigated the field applicability and future practical use of the 16 channel eddy current testing equipment and defect evaluation algorithm developed in this study. Therefore, the field applicability of the equipment and defect evaluation algorithm was investigated through the detection of artificial defects with varying size and depth. Afterwards, future practical use was evaluated by inspection of areas of rail that are in use and with naturally occurring surface defects and analysis of their size (length, width), depth, and phenomena.

Diagnostic Performance and Repeatability of a Novel Game-Based Visual Field Test for Children.

To demonstrate utility of a game-based test ("Caspar's Castle") for the detection of visual field defects in children. A validity and reliability study was carried out at Manchester Royal Eye Hospital Pediatric Ophthalmology Outpatients Department. We recruited 108 children with no eye pathology (aged 4-12 years) and examined a single eye with the Caspar's Castle system using either normal thresholds or thresholds artificially adapted to recreate defects to assess diagnostic utility. Number of peripheral stimuli missed was used to determine sensitivity and specificity of artificial defect detection and to plot receiver-operator characteristic curves. A further 21 children (aged 4-16 years) with pathology were recruited and Caspar's fields compared qualitatively with established field testing. A total of 106 of the Caspar's Castle examinations were able to be performed twice and repeatability was determined through coefficient of repeatability and Bland-Altman chart. In diagnostic testing using children with no eye pathology, 45 children completed a test using normal thresholds and 43 with tests using artificial defects. Area under receiver-operator characteristic curves for artificial defect detection was 0.895. Of the 21 children with pathology, seven had completed standard Humphreys field testing and Caspar's Castle fields corresponded with each of these by expert opinion. Coefficient of repeatability for number of points missed across all cohorts of children (106 patients) was 6.9 (95% confidence interval: 6.16-8.07). The Caspar's Castle system of assessing visual fields using novel game-based strategies demonstrates encouraging levels of sensitivity, specificity, and reliability. It could help address current difficulties in perimetry in young children.

Hyperspectral imaging combined with multivariate analysis and band math for detection of common defects on peaches (Prunus persica)

Automatic detection of common defects on peaches by using imaging system is still a challenge due to the high variability of peach surface color, the similarity between the defects and stem, as well as the uneven distribution of lightness on peaches. In order to detect the common defects on peaches using hyperspectral imaging, defects were divided into two different types: artificial defects and non-artificial defects. For artificial defect detection, a two-step multivariate analysis method (Monte Carlo-Uninformative Variable Elimination and successful projections algorithm) was conducted in the spectral domain for the discriminant wavelength (DW) selection, and then minimum noise fraction (MNF) transform was conducted on the images at DWs for image processing and artificial defect detection. For the candidate non-artificial defect detection, a pair of two characteristic wavelengths at 925nm and 726nm was selected by analyzing the full spectra of sound and non-artificial defective regions, and then a band math equation was constructed for differentiating the non-artificial defect regions and stems from the sound and physical damage regions, and the candidate non-artificial defects (including non-artificial defects and stems) could be segmented by using a simple threshold method. In order to distinguish the stem from the segmented candidate non-artificial defect regions, another band math equation was constructed based on another pair of two characteristic wavelengths at 650nm and 675nm for stem identification. Additionally, the uneven lightness distribution in the spectral images was also investigated and eliminated by the band math methods. The overall classification accuracy of 93.3% for the 120 samples indicated that the selected DWs and proposed method were suitable and efficient for the common defect detection. The limitation of our research is the static inspection in one single view.

Detection of Artificial Defects Existing Near Surface of Aluminum Alloy Die-castings by Ultrasonic Measurement

Detection of Artificial Defects Existing Near Surface of Aluminum Alloy Die-castings by Ultrasonic Measurement

Eddy Current Technique Based on ${\rm HT}_{\rm c}$-SQUID and GMR Sensors for Non-Destructive Evaluation of Fiber/Metal Laminates

In this work we present non-destructive evaluation measurements on fiber/metal laminate specimen by using eddy current techniques employing HT <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> SQUID (superconductive quantum interference device) and giant magneto-resistive (GMR) sensors. Our aim is to compare the performance and the capability of HT <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> SQUID and GMR sensors to detect the presence of damage inside FML composite materials. Experimental results concerning the detection of artificial defects in aeronautical structures with high magnetic sensitivity by using HT <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> SQUID, and with high spatial resolution using GMR, will be presented and discussed.

OS6-2 ガイド波を用いた局所減肉検査における測定パラメータの検討(OS6 設備診断・運用保全技術,循環型社会における動力エネルギー技術)

In order to detect small local wall thinnings, it is strongly expected to excite guided waves with higher frequency. In this report, the analysis of wave propagation in a plate with thickness of 10mm is performed with the finite element method and is verified with a plate specimen with the same thickness, which shows that it is possible to excite guided waves to propagate in such a plate at the frequency of 2MHz when a shear oblique transducer with refraction angle of 45 degrees is used. The detection of artificial defects introduced in the plate specimen is performed by guided waves with frequency of 2MHz. The SN ratio of the reflected echo from these defects at the frequency of 2MHz is larger at least 5.6dB than that at the frequency of 0.3MHz reported previously, which results in detecting small defects easily that is difficult for guided waves with frequency of 0.3MHz.