Results for “3D Inspection” — Page 2

DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗

NASA NTRSDate not supplied

A Markov Random Field Model for Texture-based Segmentation of Small Cracks in Thin InconelTubes

Markov random fields have been used for image segmentation since their introduction in the1980s. This work applies a method from Principal Component Thermography to enhance thecontrast in damage regions in 3D images derived from X-ray computed tomography (CT)inspections. The developed method is applied to sizing of small cracks in thin Inconel tubes designed as probability of detection (POD) samples for radiographic inspection.Misclassification errors arising from artifacts due to beam-hardening are reduced by fitting the boundary of the segmented damage region with the arc of an ellipse. Results are comparedagainst those obtained through manual inspection.

Image segmentation↗

NASA NTRS2006

Overview of High-Resolution Nondestructive Inspection of the Space Shuttle External Tank (ET) Spray-on-Foam Insulation (SOFI) and Acreage Heat tiles using Focused, Synthetic and Holographical Millimeter Wave Techniques

Space Shuttle Columbia's catastrophic failure has been attributed to a piece of spray-on-foam insulation (SOFI) that was dislodged from the external tank (ET) and struck the leading edge of the left wing. A piece of SOFI was also dislodged in the recent Space Shuttle Discovery's flight. From immediately after the Columbia accident, microwave and millimeter wave nondestructive testing methods were considered as potential effective inspection tools for evaluating the integrity of the SOFI. To this end and as a result of these efforts, both real-focused, synthetic focusing and holographical techniques, at a wide range of frequencies covering 24 GHz to 150 GHz, have been developed for this purpose. Images of various complex SOFI panels with a wide range of embedded anomalies (representing real potential defects) have been produced using these techniques, including relatively small anomalies located near complex structural features representative of the external tank. These real-focused and 3D holographical images have effectively demonstrated the utility of these methods for SOFI inspection as being viable, robust, repeatable, simple, portable and relatively inexpensive (tens of $K as opposed to hundreds of $K). In addition, the potential viability of these methods for inspecting acreage heat tiles have has been demonstrated. This paper presents an overview of these activities, representative images of these panels using all of the imaging techniques used and a discussion of the practical attributes of these inspection methods.

Kharkovsky, S.↗

NASA NTRSDate not supplied

Infrared Thermography of Concept M1 3D Printer

Explore the source record for details and available documents.

additive manufacturing↗

NASA NTRSDate not supplied

Results from Two Full-Scale Hawker 4000 Fuselage Drop Tests

In the spring of 2022, NASA Langley Research Center (LaRC) conducted two full-scale drop tests on a Hawker 4000 partial fuselage structure for the evaluation of composite material response under dynamic impact loading conditions. The specific objectives of the tests were to induce dynamic composite damage initiation and progression and in primary structure and to understand the nature of the failure modes. The tests were conducted via dividing the fuselage hardware into three smaller sections. Dynamic drop tests were conducted on the forward and aft portions of the fuselage under different dynamic loading conditions, while the middle section was reserved for materials testing. Both tests were conducted by dropping the test articles from a height of 14 feet with significant amounts of pitch, which was added to initiate damage in specific regions of the structure. The test articles were ballasted then instrumented with accelerometers at various locations and speckle-coated on both exterior sides with a black and white stochastic pattern for use with three-dimensional digital image correlation (3D-DIC). In addition, the interior belly portion of the forward section test article was also speckle-coated, which was intended to capture deformations on the belly of the test article from the interior at impact. The interior of the aft section test article was not speckle-coated. Prior to testing, bow-tie markers were applied at various locations for use in marker tracking, to measure impact conditions such as vertical impact velocity and pitch. In this report, a partial summary of the data collected from the tests is presented. The data was primarily in the form of accelerometers to measure impact acceleration and 3D-DIC to measure deformation and failure onset and propagation. Post-test inspections revealed the primary damage mechanism was fiber cracking and delamination primarily in and around the area that contacted the impact surface. Acceleration pulse shapesin the ballast locations were trapezoidal in nature and ranged between 10 g and 40 g, depending on the location and test.

full scale testing↗

NASA NTRSDate not supplied

Results from Two Full-Scale Hawker 4000 Fuselage Drop Tests

In the spring of 2022, NASA Langley Research Center (LaRC) conducted two full-scale drop tests on a Hawker 4000 partial fuselage structure for the evaluation of composite material response under dynamic impact loading conditions. The specific objectives of the tests were to induce dynamic composite damage initiation and progression and in primary structure and to understand the nature of the failure modes. The tests were conducted via dividing the fuselage hardware into three smaller sections. Dynamic drop tests were conducted on the forward and aft portions of the fuselage under different dynamic loading conditions, while the middle section was reserved for materials testing. Both tests were conducted by dropping the test articles from a height of 14 feet with significant amounts of pitch, which was added to initiate damage in specific regions of the structure. The test articles were ballasted then instrumented with accelerometers at various locations and speckle-coated on both exterior sides with a black and white stochastic pattern for use with three-dimensional digital image correlation (3D-DIC). In addition, the interior belly portion of the forward section test article was also speckle-coated, which was intended to capture deformations on the belly of the test article from the interior at impact. The interior of the aft section test article was not speckle-coated. Prior to testing, bow-tie markers were applied at various locations for use in marker tracking, to measure impact conditions such as vertical impact velocity and pitch. In this report, a partial summary of the data collected from the tests is presented. The data was primarily in the form of accelerometers to measure impact acceleration and 3D-DIC to measure deformation and failure onset and propagation. Post-test inspections revealed the primary damage mechanism was fiber cracking and delamination primarily in and around the area that contacted the impact surface. Acceleration pulse shapesin the ballast locations were trapezoidal in nature and ranged between 10 g and 40 g, depending on the location and test.

full scale testing↗

NASA NTRS2012

3D X-ray CT for BGA/CGA Workmanship Defect Detection

Commercial-off-the-shelf (COTS) advanced microelectronic technologies in high-reliability versions are now being considered for use in a number of National Aeronautics and Space Administration (NASA) electronic systems. One of the key drawbacks of advanced electronic packages with hidden solder joint interconnections, such as the column grid array (CGA), is that inspection can be challenging—whether visually or using X-rays. In general, inspection for solder joint integrity is poor, except for identifying shorts. The new, advanced X-ray systems, especially the 3D computer tomography version, may be able to provide the three-dimensional features that are extremely difficult to resolve under the 2D systems.This report presents both 2D and 3D X-ray images along with their representative optical photomicrographs for a number of advanced electronics package assemblies including 3D stack and CGA assemblies before and after thermal cycling.

Ghaffarian, Reza↗

NASA NTRS2010

Reconstituted Three-Dimensional Interactive Imaging

A method combines two-dimensional images, enhancing the images as well as rendering a 3D, enhanced, interactive computer image or visual model. Any advanced compiler can be used in conjunction with any graphics library package for this method, which is intended to take digitized images and virtually stack them so that they can be interactively viewed as a set of slices. This innovation can take multiple image sources (film or digital) and create a "transparent" image with higher densities in the image being less transparent. The images are then stacked such that an apparent 3D object is created in virtual space for interactive review of the set of images. This innovation can be used with any application where 3D images are taken as slices of a larger object. These could include machines, materials for inspection, geological objects, or human scanning. Illuminous values were stacked into planes with different transparency levels of tissues. These transparency levels can use multiple energy levels, such as density of CT scans or radioactive density. A desktop computer with enough video memory to produce the image is capable of this work. The memory changes with the size and resolution of the desired images to be stacked and viewed.

Hamilton, Joseph↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

NASA NTRSDate not supplied

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

DOE OSTI2024

Tip-Induced 3D Printing on the Nanoscale with Field Emission Scanning Probes

3D printing down to the nanoscale remains a significant challenge. In this paper, the study explores the use of scanning probes that emit low-energy electrons (<100 eV) coupled with the localized injection and electron-induced decomposition of precursor molecules, for the precise localized deposition of 3D nanostructures. The experiments are performed inside the chamber of a scanning electron microscope (SEM), enabling the use of the in-built gas injector system (GIS) with gaseous naphthalene precursor for carbon deposition, as well as immediate inspection of the deposits by SEM. Substrate materials are planar fused silica with thin conductive coatings and non-planar copper wedges. After investigation of the deposition process parameters, various 2D and 3D carbon deposits are grown. Vertical nanowires several microns in length with a diameter <100 nm are achieved and 3D deposits with a high degree of nanoscale branching are also obtained, presumably due to a charging effect. High aspect ratio carbon nanostructures such as those demonstrated here can be employed as miniaturized electrodes or field emitters. The tip-based approach presented thus paves the way toward 3D nanoscale printing of various materials and functional nanostructures.

3D printing↗

NASA NTRS2019

NASA’s In-Space Manufacturing Project: Update on Manufacturing Technologies and Materials to Enable More Sustainable and Safer Exploration

NASA’s In-Space Manufacturing (ISM) project seeks to develop the materials, processes, and manufacturing technologies needed to provide an on-demand manufacturing capability for deep space exploration missions. The ability to manufacture and recycle some parts on demand rather than launch them from earth has the potential to reduce logistics requirements on long duration missions and enhance crew safety. With the launch of the first 3D printer (built and operated by Made in Space through a Small Business Innovative Research – SBIR -- contract) to the International Space Station (ISS) in 2014, the ISM project demonstrated the feasibility of operating an on-demand manufacturing system in a microgravity environment. This paper will provide an update on recent advancements in ISM under three key technology areas: manufacturing, recycling, and development of a design database. ISM continues to pursue development of manufacturing technologies for space applications and use the ISS as a critical test bed to prove out these technologies before deploying them on next generation exploration systems. Activities under this focus area include: characterization of materials manufactured using the Additive Manufacturing Facility (AMF), the second generation commercial 3D-printer on ISS, also owned and operated by Made in Space; development of prototype payloads for metal manufacturing through phase II SBIR contracts with Tethers Unlimited, Made in Space, and Ultra Tech Machinery; development of a multi-material fabrication laboratory capable of processing metals and providing inspection of manufactured parts through a Broad Agency Announcement (Techshot, Interlog, and Tethers Unlimited); an in-line sensing system for ISM platforms; and development of higher strength feedstocks for 3D polymer printers. In the area of recycling, the Tethers Unlimited Refabricator payload (an integrated 3D printer and recycler for ULTEM 9085) launched to ISS in November 2018 and began operating in early 2019. This payload represents the first demonstration of on-orbit recycling; down massed specimens will assess material degradation in the polymer over multiple recycling cycles to define limits on material re-use. Other work in the recycling area includes development of common use materials intended to be reused and recycled on space missions (Tethers Unlimited and Cornerstone Research Group) and a sterilization capability for multiple-use materials (ERASMUS from Tethers Unlimited). Concurrent with manufacturing technology and materials development work is creation of a design database, a curated list of parts that can be manufactured using the suite of In-Space Manufacturing capabilities.

Tracie Prater↗

NASA NTRS2014

Shell-NASA Vibration-Based Damage Characterization

This article describes collaborative research between Shell International Exploration and Production (IE&P) scientists and ISAG personnel to investigate the feasibility of ultrasonic-based characterization of spacecraft tile damage for in-space inspection applications. The approach was proposed by Shell personnel in a Shell-NASA "speed-matching" session in early 2011 after ISAG personnel described challenges inherent in the inspection of MMOD damage deep within spacecraft thermal protection system (TPS) tiles. The approach leveraged Shell's relevant sensor and analytical expertise. The research addressed the difficulties associated with producing 3D models of MMOD damage cavities under the surface of a TPS tile, given that simple image-based sensing is constrained by line of sight through entry holes that have diameters considerably smaller than the underlying damage cavities. Damage cavity characterization is needed as part of a vehicle inspection and risk reduction capability for long-duration, human-flown space missions. It was hoped that cavity characterization could be accomplished through the use of ultrasonic techniques that allow for signal penetration through solid material.

Rollins, John M.↗

DOE OSTI2026

Using 2.5D super-resolution to improve flaw detection in metal additive manufacturing parts

Industrial X-ray computed tomography (XCT) enables non-destructive inspection of additively manufactured (AM) parts, but high-resolution scanning requires long acquisition times and significant computational resources, limiting throughput in production environments. Super-resolution techniques can recover high-resolution information from low-resolution scans, but existing methods face a trade-off between 2D approaches that ignore inter-slice information and 3D methods that are computationally prohibitive for practical deployment. To address this trade-off, we propose a 2.5D deep learning-based super-resolution approach that uses seven neighbouring low-resolution slices to super-resolve the centre slice. This work evaluates the method on real XCT scans of steel AM parts, comparing reconstruction quality and flaw detection performance of 2D, 2.5D, and 3D ESRGAN-based super-resolution methods. Results demonstrate that 2.5D super-resolution significantly improves detection of small, process-induced flaws (e.g. porosity) compared to 2D methods, while avoiding the prohibitive computational burden of full 3D approaches. These findings provide initial evidence of 2.5D super-resolution as a practical, deployable solution for improving flaw detection in high-throughput industrial XCT inspection.

X-ray CT↗

DOE OSTI2026

Advancing Industry 4.0: Multimodal Sensor Fusion for AI-Based Fault Detection in 3D Printing

Additive manufacturing, particularly fused deposition modeling, is transforming modern production by enabling rapid prototyping and complex part fabrication. However, its layer-by-layer process remains vulnerable to faults such as nozzle clogging, filament runout, and layer misalignment, which compromise print quality and reliability. Traditional inspection methods are costly, time-intensive, and often limited to post-process analysis, making them unsuitable for real-time intervention. In this current study, the authors developed a novel, low-cost, and portable faultdetection system that leverages multimodal sensor fusion and artificial intelligence for real-time monitoring in FDM-based 3D printing. The system integrates acoustic, vibration, and thermal sensing into a non-intrusive architecture, capturing complementary data streams that reflect both mechanical and process-related anomalies. Acoustic and thermal sensors operate in a fully contactless manner, while the vibration sensor requires minimal attachment such that it will not interfere with printer hardware, thereby preserving portability and ease of deployment. The multimodal signals are processed into spectrograms and time-frequency features, which are classified using convolutional neural networks for intelligent fault detection. The proposed system advances Industry 4.0 objectives by offering an affordable, scalable, and practical monitoring solution that improves faultdetection accuracy, reduces waste, and supports sustainable, adaptive manufacturing.

42 ENGINEERING↗

NASA NTRS2003

NASA Tech Briefs, June 2003

Topics covered include: Nulling Infrared Radiometer for Measuring Temperature; The Ames Power Monitoring System; Hot Films on Ceramic Substrates for Measuring Skin Friction; Probe Without Moving Parts Measures Flow Angle; Detecting Conductive Liquid Leaking from Nonconductive Pipe; Adaptive Suppression of Noise in Voice Communications; High-Performance Solid-State W-Band Power Amplifiers; Microbatteries for Combinatorial Studies of Conventional Lithium-Ion Batteries; Correcting for Beam Aberrations in a Beam-Waveguide Antenna; Advanced Rainbow Solar Photovoltaic Arrays; Metal Side Reflectors for Trapping Light in QWIPs; Software for Collaborative Engineering of Launch Rockets; Software Assists in Extensive Environmental Auditing; Software Supports Distributed Operations via the Internet; Software Estimates Costs of Testing Rocket Engines; yourSky: Custom Sky-Image Mosaics via the Internet; Software for Managing Inventory of Flight Hardware; Lower-Conductivity Thermal-Barrier Coatings; Process for Smoothing an Si Substrate after Etching of SiO2; Flexible Composite-Material Pressure Vessel; Treatment to Destroy Chlorohydrocarbon Liquids in the Ground; Noncircular Cross Sections Could Enhance Mixing in Sprays; Small, Untethered, Mobile Roots for Inspecting Gas Pipes; Paint-Overspray Catcher; Preparation of Regular Specimens for Atom Probes; Inverse Tomo-Lithography for Making Microscopic 3D Parts; Predicting and Preventing Incipient Flameout in Combustors; MEMS-Based Piezoelectric/Electrostatic Inchworm Actuator; Metallized Capillaries as Probes for Raman Spectroscopy; Adaptation of Mesoscale Weather Models to Local Forecasting; Aerodynamic Design using Neural Networks; Combining Multiple Gyroscope Outputs for Increased Accuracy; and Improved Collision-Detection Method for Robotic Manipulator.

Source record↗