Eric R. Burke

Thermal imaging for assessment of electron-beam freeform fabrication (EBF3) additive manufacturing deposits

Additive manufacturing is a rapidly growing field where 3-dimensional parts can be produced layer by layer. NASA’s electron beam freeform fabrication (EBF3) technology is being evaluated to manufacture metallic parts in a space environment. The benefits of EBF3 technology are weight savings to support space missions, rapid prototyping in a zero gravity environment, and improved vehicle readiness. The EBF3 system is composed of 3 main components: electron beam gun, multi-axis position system, and metallic wire feeder. The electron beam is used to melt the wire and the multi-axis positioning system is used to build the part layer by layer. To insure a quality deposit, a near infrared (NIR) camera is used to image the melt pool and solidification areas. This paper describes the calibration and application of a NIR camera for temperature measurement. In addition, image processing techniques are presented for deposit assessment metrics.

Thermography inspection for early detection of composite damage in structures during fatigue loading

Advanced composite structures are commonly tested under controlled loading. Understanding the initiation and progression of composite damage under load is critical for validating design concepts and structural analysis tools. Thermal nondestructive evaluation (NDE) is used to detect and characterize damage in composite structures during fatigue loading. A difference image processing algorithm is demonstrated to enhance damage detection and characterization by removing thermal variations not associated with defects. In addition, a one-dimensional multilayered thermal model is used to characterize damage. Lastly, the thermography results are compared to other inspections such as non-immersion ultrasonic inspections and computed tomography X-ray.

Thermographic imaging of the space shuttle during re-entry using a near-infrared sensor

High resolution calibrated near infrared (NIR) imagery of the Space Shuttle Orbiter was obtained during hypervelocity atmospheric re-entry of the STS-119, STS-125, STS-128, STS-131, STS-132, STS-133, and STS-134 missions. This data has provided information on the distribution of surface temperature and the state of the airflow over the windward surface of the Orbiter during descent. The thermal imagery complemented data collected with onboard surface thermocouple instrumentation. The spatially resolved global thermal measurements made during the Orbiters hypersonic re-entry will provide critical flight data for reducing the uncertainty associated with present day ground-to-flight extrapolation techniques and current state-of-the-art empirical boundary-layer transition or turbulent heating prediction methods. Laminar and turbulent flight data is critical for the validation of physics-based, semi-empirical boundary-layer transition prediction methods as well as stimulating the validation of laminar numerical chemistry models and the development of turbulence models supporting NASAs next-generation spacecraft. In this paper we provide details of the NIR imaging system used on both air and land-based imaging assets. The paper will discuss calibrations performed on the NIR imaging systems that permitted conversion of captured radiant intensity (counts) to temperature values. Image processing techniques are presented to analyze the NIR data for vignetting distortion, best resolution, and image sharpness.

Large Area Nondestructive Evaluation of a Fatigue Loaded Composite Structure

Large area nondestructive evaluation (NDE) inspections are required for fatigue testing of composite structures to track damage initiation and growth. Of particular interest is the progression of damage leading to ultimate failure to validate damage progression models. In this work, passive thermography and acoustic emission NDE were used to track damage growth up to failure of a composite three-stringer panel. Fourteen acoustic emission sensors were placed on the composite panel. The signals from the array were acquired simultaneously and allowed for acoustic emission location. In addition, real time thermal data of the composite structure were acquired during loading. Details are presented on the mapping of the acoustic emission locations directly onto the thermal imagery to confirm areas of damage growth leading to ultimate failure. This required synchronizing the acoustic emission and thermal data with the applied loading. In addition, processing of the thermal imagery which included contrast enhancement, removal of optical barrel distortion and correction of angular rotation before mapping the acoustic event locations are discussed.

In-Process Thermal Imaging of the Electron Beam Freeform Fabrication Process

Researchers at NASA Langley Research Center have been developing the Electron Beam Freeform Fabrication (EBF3) metal additive manufacturing process for the past 15 years. In this process, an electron beam is used as a heat source to create a small molten pool on a substrate into which wire is fed. The electron beam and wire feed assembly are translated with respect to the substrate to follow a predetermined tool path. This process is repeated in a layer-wise fashion to fabricate metal structural components. In-process imaging has been integrated into the EBF3 system using a near-infrared (NIR) camera. The images are processed to provide thermal and spatial measurements that have been incorporated into a closed-loop control system to maintain consistent thermal conditions throughout the build. Other information in the thermal images is being used to assess quality in real time by detecting flaws in prior layers of the deposit. NIR camera incorporation into the system has improved the consistency of the deposited material and provides the potential for real-time flaw detection which, ultimately, could lead to the manufacture of better, more reliable components using this additive manufacturing process.

Summary of NDE of Additive Manufacturing Efforts in NASA

One of the major obstacles slowing the acceptance of parts made by additive manufacturing (AM) in NASA applications is the lack of a broadly accepted materials and process quality systems; and more specifically, the lack of adequate nondestructive evaluation (NDE) processes integrated into AM. Matching voluntary consensus standards are also needed to control the consistency of input materials, process equipment, process methods, finished part properties, and how those properties are characterized. As for nondestructive characterization, procedures are needed to interrogate features unique to parts made by AM, such as fine-scale porosity, deeply embedded flaws, complex part geometry, and intricate internal features. The NDE methods developed must be tailored to meet materials, design and test requirements encountered throughout the part life cycle, whether during process optimization, real-time process monitoring, finished part qualification and certification (especially of flight hardware), or in situ hea...

Segmenting delaminations in carbon fiber reinforced polymer composite CT using convolutional neural networks

Nondestructive evaluation (NDE) utilizes a variety of techniques to inspect various materials for defects without causing changes to the material. X-ray computed tomography (CT) produces large volumes of three dimensional image data. Using the task of identifying delaminations in carbon fiber reinforced polymer (CFRP) composite CT, this work shows that it is possible to automate the analysis of these large volumes of CT data using a machine learning model known as a convolutional neural network (CNN). Further, tests on simulated data sets show that with a robust set of experimental data, it may be possible to go beyond just identification and instead accurately characterize the size and shape of the delaminations with CNNs.

Real Time Fatigue Damage Growth Assessment of a Composite Three-Stringer Panel Using Passive Thermography

Fatigue testing of advanced composite structures is critical to validate both structural designs and damage prediction models. In-situ inspection methods are necessary to track damage onset and growth as a function of load cycles. Passive thermography is a large area, noncontact inspection technique that is used to detect composite damage onset and growth in real time as a function of fatigue cycles. The thermal images are acquired in synchronicity to the applied compressive load using a dual infrared camera acquisition system for full (front and back) coverage. Image processing algorithms are investigated to increase defect contrast areas. The thermal results are compared to non-immersion ultrasound inspections and acoustic emission data.

Combining Passive Thermography and Acoustic Emission for Large Area Fatigue Damage Growth Assessment of a Composite Structure

Passive thermography and acoustic emission data were obtained for improved real time damage detection during fatigue loading. A strong positive correlation was demonstrated between acoustic energy event location and thermal heating, especially if the structure under load was nearing ultimate failure. An image processing routine was developed to map the acoustic emission data onto the thermal imagery. This required removing optical barrel distortion and angular rotation from the thermal data. The acoustic emission data were then mapped onto thermal data, revealing the cluster of acoustic emission event locations around the thermal signatures of interest. By combining both techniques, progression of damage growth is confirmed and areas of failure are identified. This technology provides improved real time inspections of advanced composite structures during fatigue testing.