Autonomous robotic system for thermographic detection of defects in upper layers of carbon fiber reinforced polymers

Carbon Fiber Reinforced Polymers (CFRPs) are composites whose interesting properties, like high strength-to-weight ratio and rigidity, are of interest in many industrial fields. Many defects affecting their production process are due to the wrong distribution of the thermosetting polymer in the upper layers. In this work, they are effectively and efficiently detected by automatically analyzing the thermographic images obtained by Pulsed Phase Thermography (PPT) and comparing them with a defect-free reference. The flash lamp and infrared camera needed by PPT are mounted on an industrial robot so that surfaces of CFRP automotive components, car side blades in our case, can be inspected in a series of static tests. The thermographic image analysis is based on local contrast adjustment via UnSharp Masking (USM) and takes also advantage of the high level of knowledge of the entire system provided by the calibration procedures. This system could replace manual inspection leading to a substantial increase in efficiency

Semantic models of scenes and objects for service and industrial robotics

What may seem straightforward for the human perception system is still challenging for robots. Automatically segmenting the elements with highest relevance or salience, i.e. the semantics, is non-trivial given the high level of variability in the world and the limits of vision sensors. This stands up when multiple ambiguous sources of information are available, which is the case when dealing with moving robots. This thesis leverages on the availability of contextual cues and multiple points of view to make the segmentation task easier. Four robotic applications will be presented, two designed for service robotics and two for an industrial context. Semantic models of indoor environments will be built enriching geometric reconstructions with semantic information about objects, structural elements and humans. Our approach leverages on the importance of context, the availability of multiple source of information, as well as multiple view points showing with extensive experiments on several datasets that these are all crucial elements to boost state-of-the-art performances. Furthermore, moving to applications with robots analyzing object surfaces instead of their surroundings, semantic models of Carbon Fiber Reinforced Polymers will be built augmenting geometric models with accurate measurements of superficial fiber orientations, and inner defects invisible to the human-eye. We succeeded in reaching an industrial grade accuracy making these models useful for autonomous quality inspection and process optimization. In all applications, special attention will be paid towards fast methods suitable for real robots like the two prototypes presented in this thesis

Non-Destructive Techniques for the Condition and Structural Health Monitoring of Wind Turbines: A Literature Review of the Last 20 Years

A complete surveillance strategy for wind turbines requires both the condition monitoring (CM) of their mechanical components and the structural health monitoring (SHM) of their load-bearing structural elements (foundations, tower, and blades). Therefore, it spans both the civil and mechanical engineering fields. Several traditional and advanced non-destructive techniques (NDTs) have been proposed for both areas of application throughout the last years. These include visual inspection (VI), acoustic emissions (AEs), ultrasonic testing (UT), infrared thermography (IRT), radiographic testing (RT), electromagnetic testing (ET), oil monitoring, and many other methods. These NDTs can be performed by human personnel, robots, or unmanned aerial vehicles (UAVs); they can also be applied both for isolated wind turbines or systematically for whole onshore or offshore wind farms. These non-destructive approaches have been extensively reviewed here; more than 300 scientific articles, technical reports, and other documents are included in this review, encompassing all the main aspects of these survey strategies. Particular attention was dedicated to the latest developments in the last two decades (2000–2021). Highly influential research works, which received major attention from the scientific community, are highlighted and commented upon. Furthermore, for each strategy, a selection of relevant applications is reported by way of example, including newer and less developed strategies as well

NASA patent abstracts bibliography: A continuing bibliography. Section 1: Abstracts (supplement 38)

Abstracts are provided for 132 patents and patent applications entered into the NASA scientific and technical information system during the period July 1990 through December 1990. Each entry consists of a citation, an abstract, and in most cases, a key illustration selected from the patent or patent application

Magnetic polyamide 6 nanocomposites for increasing damage tolerance through self-healing of composite structures.

Self-healing materials have the ability to repeatedly repair damages that occur before complete failure of materials. The development of stimuli-responsive self-healing materials has been in demand recently for composite structures, since their failure is relatively uncertain and can result in major expenses. Using such materials can enhance damage tolerance, leading to greater asset reliability - it also limits expenditure and keeps the need for human interventions to a minimum. This work investigates Fe3O4 magnetic polymer nanocomposites that can be used to intrinsically heal composites through thermal stimuli, followed by self-healing of glass fibre reinforced polymer (GFRP) composites, which are fabricated by embedding the healable polymer nanocomposite as one of the sacrificial layered matrices. However, performance of nanocomposites depends on various parameters, including nanoscale dispersion of nanoparticles. Specifically, a lack of hierarchical dispersion of nanoparticles in three-dimensional polymer matrices prevents electron tunnelling and deteriorates the nanocomposites' ability to conduct heat stimuli or otherwise lead to pyrolysis. To address this issue, two functionalisation techniques - viz. silica (Stöber method for lower silica loading and tri-phasic reverse emulsion method for higher silica loading), and oleic acid (22%, 33%, 44%, and 55% w/w of nanoparticles) variations - were experimentally investigated as capable of changing hydrophobic characteristics for facilitating uniform dispersion of the Fe3O4 magnetic nanoparticles (MNPs). The main focus of the presented work is to understand the role of functionalisation routes in the particle-polymer interface in forming a uniformly dispersed and hierarchical network of MNPs in a polymer matrix. Emphasis was on understanding and optimising the role of activator and initiator proportions in controlling the in-situ polymerisation of PA6, capturing the MNPs dispersion state. The resulting dispersion state due to functionalised Fe3O4 MNPs determined the properties of magnetic PA6 nanocomposites (PMC) to help achieve a generic set of principles for designing the desired materials for stimuli-induced self-healing of GFRP composites. The method used to achieve this involved firstly undertaking anionic ring-opening in-situ polymerisation of PMC by experimental synthesis within the laboratory, with optimised EtMgBr (activator) and NACL (initiator) proportions for improved degree of crystallinity, and capturing the MNPs dispersion state attained by probe ultrasonication of the melt monomer & MNPs solution mixture. Based on this, 50% EtMgBr (activator) and 30% NACL (initiator) were assessed as the optimised proportions for giving the highest possible crystallinity amongst all the prepared PMC variations. Secondly, as per the functionalisation type of the MNPs, the prepared PMC samples were tested based on chemical, thermal, structural and magnetic characterisations, for the purpose of assessing their self-healing capability by microwave stimuli. The physical characterisation results were also used to train a simulation model to create the 3D dispersion state, for better studying the dispersion state and interaction region defined by the interaction radius (IR) of each MNP/agglomerate of the MNPs. Based on this overall comparison, the most suitable PMC of 22 w/w % OA loading was selected and formed into thin films. Sandwiched tensile testing samples were then prepared using this PMC film as a sacrificial layer between GFRP tapes. Both bare and modified Fe3O4 MNPs PMC exhibited paramagnetic behaviour, with average particle sizes ranging from 30-60 nm. The saturation magnetisation (Ms) of the unmodified MNPs PMC was around 65% and that of the selected PMC with 22 wt/wt % OA loading was 47%. The self-healing concept was demonstrated with the prepared composite samples' microwave induction heating, and the efficiencies based on strength recovery were calculated as 84%, 58% and 34% after first, second and third healing, respectively. This can essentially increase the life-cycle viability of the composite structure by over 175% (with 60% certainty) compared with that of an otherwise damaged structure, hence promising cost saving by extending the structural life

Cumulative index to NASA Tech Briefs, 1986-1990, volumes 10-14

Tech Briefs are short announcements of new technology derived from the R&D activities of the National Aeronautics and Space Administration. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This cumulative index of Tech Briefs contains abstracts and four indexes (subject, personal author, originating center, and Tech Brief number) and covers the period 1986 to 1990. The abstract section is organized by the following subject categories: electronic components and circuits, electronic systems, physical sciences, materials, computer programs, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences