Thermal inspections of a structure typically utilize a flash or quartz lamp heat source located on the same side of an infrared camera. The heat source provides light energy for heating while the infrared camera measures the surface transient temperature response. The inspection can be difficult for low emissivity surfaces for several reasons. First, the high intensity light can reflect off the surface and cause “burn-in” to the camera’s detector. The “burn-in” can take time for the sensors to recover and potentially damage the detector. Secondly, the heat source after pulsing has a transient cool down component. The cool down component can be reflected and therefore superimposed over the structure’s thermal response, which can cause an error (false defect indications) in the inspection. Lastly, the heat source is spectrally broad and therefore while heating, infrared components of the heat source can produce non-uniformity in the measured temperature field. Typically for the inspection of low emissivity surfaces, paint or other emissivity enhancing coatings are applied before inspection. In this paper, a pulsed light emitting diodes (PLED) heat source is used. The PLED heat source is spectrally narrow, contained within the visible band, and therefore not detectable by the infrared camera. The PLED heat source is configured to reduce any transient cool down components that could produce false defect indications. The PLED thermal inspections are compared to flash thermography inspections on unpainted aluminum samples with simulated corrosion and an additively manufactured Ti-6AL-4V metal specimens.
Certification of additive manufactured metal parts requires nondestructive evaluation (NDE) to ensure build quality. NDE can be performed during the build process or post build. For large parts with complex geometries, post build NDE can be challenging. In-situ NDE potentially provides a way to perform the inspection layer by layer. This work explores the use of a high speed near infrared (NIR) camera that is focused in-line with a laser to obtain high spatial and temporal resolution thermal imagery of the melt pool and associated cooling areas. The thermal data is obtained during a laser melting process using a Ti-6Al-4V plate and of particular interest is the detection of keyhole porosity. Keyhole porosity can result from non-optimal build conditions, such as excessive laser power at a given laser scanning speed, that creates an entrapped bubble. The NIR measured melt pool and cooling areas are processed to detect keyhole porosity. The results are compared to X-ray computed tomography (CT) for validation. Keyhole pores buried deep were not detectable with this technique, however, some larger subsurface elongated pores and some open surface pores did show some promise for detectability.
Post processing X-ray computational tomography (CT) inspection data for additively manufactured (AM) components can induce deviations in defect quantification, affecting subsequent fatigue and failure predictions. To assess the influence and potential impact of segmentation-induced measurement deviations, this paper applies several segmentation techniques to X-ray CT data for powder bed fusion Ti-6Al-4V specimens exhibiting porosity conditions. X-ray CT reconstructions were segmented with varying techniques including Otsu’s thresholding, random forest, k-nearest neighbors, and the multilayer perceptron. Metrics such as pore size and global porosity were compared for internal validity. Then, top-down X-ray CT measurements of surface-breaking porosity were compared to optical profilometry for cross-validation.
Flash thermal diffusivity measurements were obtained on additively manufactured Ti-6Al-4V disk shaped specimens with various process parameters. For additively manufactured metal parts, processing parameters such as laser power and scanning speed are critical to ensure the desired microstructure. For this study, the laser powder bed fusion process parameters were changed at various angular sections on a 21 mm diameter and 3.0 mm thick disk. The measurement of thermal diffusivity was performed by fitting a 1-dimensional thermal model to the data pixel by pixel to produce an inspection image. The image revealed the detection of defects such as lack of fusion porosity and areas of aggregated porosity. The thermal diffusivity imagery was compared to immersion scan ultrasonic and X-ray computed tomography (CT) measurements for validation. Based on these results, additional samples were investigated using a single side thermal inspection technique to detect lack of fusion porosity and near surface voids.
Additive manufacturing (AM) is a rapidly growing technology. An area of major importance is the integrity and repeatability of AM parts. The goal is to reduce obstacles to certify AM built parts to allow for use in critical aerospace applications. In-situ nondestructive evaluation sensors can be used for build assessment and can potentially play a key role in certifying AM parts. For example, melt pool features are understood to have a strong correlation to microstructural defects and the use of a near infrared (NIR) camera can be used to record the melt pool, cooling areas, and temperature gradients during the build. This work explores the use of a low cost NIR camera to obtain single line track imagery of the Ti-6Al-4V melt pools for various processing parameters. The NIR camera is radiometrically calibrated and configured in-line with the laser source to obtain high resolution imagery of the melt pool shape and dynamics. The challenge to measure melt pool shapes is to identify the transition points between the metal solid to liquid phase. Factors for melt pool measurements such as thermal camera pixel resolution, surface emissivity, and blurring are discussed. Lastly, the melt pool imagery are compared to optical microscopy measurements for validation.
This paper describes the inline (coaxial to laser) near infrared (NIR) camera sensor on the Configurable Architecture Additive Testbed (CAAT). The CAAT is an instrument that provides the capability to investigate laser based additive manufacturing (AM) processes and is configured for the metal powder bed fusion process. A low cost NIR camera is radiometrically calibrated to obtain coaxial, inline, imagery of laser generated melt pools. The camera capabilities, system optical path, and the uncertainty in the temperature measurement from NIR surface area scans on a bare titanium alloy plate are presented and discussed. The surface radiance measurements are compared to optical microscopy images of the melt pool width and depth. A metallic additive manufacturing process thermal model is developed in order to predict thermal distributions during laser scanning. The predicted thermal distributions by the model for different configurations are compared to the coaxial NIR measurements and discussed.
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