Infrared thermography and NDT : 2050 horizon

Society is changing fast, new technologies and materials have been developed which require new inspection approaches. Infrared thermography (IRT) has emerged in the recent years as an attractive and reliable technique to address complex non-destructive testing (NDT) problems. Companies are now providing turn-key IRT-NDT systems, but the question we ask now is ‘What is next?’. Even though the future is elusive, we can consider the possible future developments in IR NDT. Our analysis shows that new developments will take place in various areas such as: acquisition, stimulation, processing and obviously an always enlarging range of applications with new materials which will have particular inspection requirements. This paper presents the various developments in the field of IRT which have evolved to lead to the current situation, and then examines the potential future trend in IRT-NDT

Custom Integrated Circuits

Contains table of contents for Part III, table of contents for Section 1 and reports on eleven research projects.IBM CorporationMIT School of EngineeringNational Science Foundation Grant MIP 94-23221Defense Advanced Research Projects Agency/U.S. Army Intelligence Center Contract DABT63-94-C-0053Mitsubishi CorporationNational Science Foundation Young Investigator Award Fellowship MIP 92-58376Joint Industry Program on Offshore Structure AnalysisAnalog DevicesDefense Advanced Research Projects AgencyCadence Design SystemsMAFET ConsortiumConsortium for Superconducting ElectronicsNational Defense Science and Engineering Graduate FellowshipDigital Equipment CorporationMIT Lincoln LaboratorySemiconductor Research CorporationMultiuniversity Research IntiativeNational Science Foundatio

Principal Component Analysis based Image Fusion Routine with Application to Stamping Split Detection

This dissertation presents a novel thermal and visible image fusion system with application in online automotive stamping split detection. The thermal vision system scans temperature maps of high reflective steel panels to locate abnormal temperature readings indicative of high local wrinkling pressure that causes metal splitting. The visible vision system offsets the blurring effect of thermal vision system caused by heat diffusion across the surface through conduction and heat losses to the surroundings through convection. The fusion of thermal and visible images combines two separate physical channels and provides more informative result image than the original ones. Principal Component Analysis (PCA) is employed for image fusion to transform original image to its eigenspace. By retaining the principal components with influencing eigenvalues, PCA keeps the key features in the original image and reduces noise level. Then a pixel level image fusion algorithm is developed to fuse images from the thermal and visible channels, enhance the result image from low level and increase the signal to noise ratio. Finally, an automatic split detection algorithm is designed and implemented to perform online objective automotive stamping split detection. The integrated PCA based image fusion system for stamping split detection is developed and tested on an automotive press line. It is also assessed by online thermal and visible acquisitions and illustrates performance and success. Different splits with variant shape, size and amount are detected under actual operating conditions

On Small Satellites for Oceanography: A Survey

The recent explosive growth of small satellite operations driven primarily from an academic or pedagogical need, has demonstrated the viability of commercial-off-the-shelf technologies in space. They have also leveraged and shown the need for development of compatible sensors primarily aimed for Earth observation tasks including monitoring terrestrial domains, communications and engineering tests. However, one domain that these platforms have not yet made substantial inroads into, is in the ocean sciences. Remote sensing has long been within the repertoire of tools for oceanographers to study dynamic large scale physical phenomena, such as gyres and fronts, bio-geochemical process transport, primary productivity and process studies in the coastal ocean. We argue that the time has come for micro and nano satellites (with mass smaller than 100 kg and 2 to 3 year development times) designed, built, tested and flown by academic departments, for coordinated observations with robotic assets in situ. We do so primarily by surveying SmallSat missions oriented towards ocean observations in the recent past, and in doing so, we update the current knowledge about what is feasible in the rapidly evolving field of platforms and sensors for this domain. We conclude by proposing a set of candidate ocean observing missions with an emphasis on radar-based observations, with a focus on Synthetic Aperture Radar.Comment: 63 pages, 4 figures, 8 table

“Design, Development and Characterization of a Thermal Sensor Brick System for Modular Robotics

This thesis presents the work on thermal imaging sensor brick (TISB) system for modular robotics. The research demonstrates the design, development and characterization of the TISB system. The TISB system is based on the design philosophy of sensor bricks for modular robotics. In under vehicle surveillance for threat detection, which is a target application of this work we have demonstrated the advantages of the TISB system over purely vision-based systems. We have highlighted the advantages of the TISB system as an illumination invariant threat detection system for detecting hidden threat objects in the undercarriage of a car. We have compared the TISB system to the vision sensor brick system and the mirror on a stick. We have also illustrated the operational capability of the system on the SafeBot under vehicle robot to acquire and transmit the data wirelessly. The early designs of the TISB system, the evolution of the designs and the uniformity achieved while maintaining the modularity in building the different sensor bricks; the visual, the thermal and the range sensor brick is presented as part of this work. Each of these sensor brick systems designed and implemented at the Imaging Robotics and Intelligent Systems (IRIS) laboratory consist of four major blocks: Sensing and Image Acquisition Block, Pre-Processing and Fusion Block, Communication Block, and Power Block. The Sensing and Image Acquisition Block is to capture images or acquire data. The Pre-Processing and Fusion Block is to work on the acquired images or data. The Communication Block is for transferring data between the sensor brick and the remote host computer. The Power Block is to maintain power supply to the entire brick. The modular sensor bricks are self-sufficient plug and play systems. The SafeBot under vehicle robot designed and implemented at the IRIS laboratory has two tracked platforms one on each side with a payload bay area in the middle. Each of these tracked platforms is a mobility brick based on the same design philosophy as the modular sensor bricks. The robot can carry one brick at a time or even multiple bricks at the same time. The contributions of this thesis are: (1) designing and developing the hardware implementation of the TISB system, (2) designing and developing the software for the TISB system, and (3) characterizing the TISB system, where this characterization of the system is the major contribution of this thesis. The analysis of the thermal sensor brick system provides the user and future designers with sufficient information on parameters to be considered to make the right choice for future modifications, the kind of applications the TISB could handle and the load that the different blocks of the TISB system could manage. Under vehicle surveillance for threat detection, perimeter / area surveillance, scouting, and improvised explosive device (IED) detection using a car-mounted system are some of the applications that have been identified for this system

Compact Survey and Inspection Day/Night Image Sensor Suite for Small Unmanned Aircraft Systems (EyePod)

EyePod is a compact survey and inspection day/night imaging sensor suite for small unmanned aircraft systems (UAS). EyePod generates georeferenced image products in real-time from visible near infrared (VNIR) and long wave infrared (LWIR) imaging sensors and was developed under the ONR funded FEATHAR (Fusion, Exploitation, Algorithms, and Targeting for High-Altitude Reconnaissance) program. FEATHAR is being directed and executed by the Naval Research Laboratory (NRL) in conjunction with the Space Dynamics Laboratory (SDL) and FEATHAR’s goal is to develop and test new tactical sensor systems specifically designed for small manned and unmanned platforms (payload weight \u3c 50 lbs). The EyePod suite consists of two VNIR/LWIR (day/night) gimbaled sensors that, combined, provide broad area survey and focused inspection capabilities. Each EyePod sensor pairs an HD visible EO sensor with a LWIR bolometric imager providing precision geo-referenced and fully digital EO/IR NITFS output imagery. The LWIR sensor is mounted to a patent-pending jitter-reduction stage to correct for the high-frequency motion typically found on small aircraft and unmanned systems. Details will be presented on both the wide-area and inspection EyePod sensor systems, their modes of operation, and results from recent flight demonstrations

A Low-cost Normalized Difference Vegetation Index (NDVI) Payload for Cubesats and Unmanned Aerial Vehicles (UAVs)

The focus of this research has been the design and fabrication of a Normalized Difference Vegetation Index (NDVI) payload configuration. This unique payload employs low-cost commercial off-the-shelf (COTS) hardware and equipment to assess photosynthetic activity and vegetation health through remote sensing on Cubesat or Unmanned Aerial Vehicle (UAV) platforms. The proposed NDVI imaging payload is comprised of three main subsystems: an electrical system, a software system, and a hardware system. The electrical system includes a custom designed printed circuit board (PCB), a single cell 3.7 V lithium-polymer battery, voltage regulator circuitry components, and wiring harnesses and connectors. The software system employs a master and slave system that communicates through general purpose input/output (GPIO) pin responses. Raspberry Pi Zero computer boards serve as the central processing units (CPUs) of the hardware subsystem, which also consists of the Pi-Cam standard red/green/blue (RGB) and Pi No-IR near-infrared (NIR) camera modules. A PCB was designed to be compatible with the Cubesat standard and lightweight component selections make it a desirable option for UAV flights. Open-source GIMP image processing software was used to analyze results from ground-based testing and flight testing on a UAV and general aviation (GA) aircraft at various altitudes to validate proof of concept. Raw NDVI and NDVI color map images were created from GIMP post-processing. Analysis of the results suggests that the angle of incidence of the sun with respect to the view angle of the imaging payload is a significant factor in the resulting NDVI values. Terrain also appeared to have an effect on the results where shadows were cast from the sun at low angles of incidence. Therefore, in the northern hemisphere it is recommended that image collection is performed roughly within the hours of 10 AM and 2 PM between the vernal and autumnal equinoxes to ensure a solar altitude of at least 35°. For best results, it has been verified that image data should be collected at the local time of maximum solar altitude for a particular date and location of interest (typically around noon). The information gather by this research can be used by scientists and technologist to potentially provide a means of enhancing their research and further developing technologies of UAV applications and space-based systems