Designing periodic and aperiodic structures for nanophotinic devices.

330 p.Future all--optical networks will require to substitute the present electronic integrated circuitry by optical analogous devices that satisfy the compactness, throughput, latency and high transmission efficiency requirements in nanometer scale dimensions, outperforming the functionality of current networks. Thereby, existing dielectric materials do not confine light in a sufficiently small scale and so the physical size of these links and devices becomes unacceptable. In fact, if the optical chip does not exist in the liking of the electronic chip, photonic crystals have recently led to great hopes for a large-scale integration of optoelectronic components. Two-dimensional photonic crystals slabs obtained through periodic structuring of a planar optical waveguide, feature many characteristics which bring them closer to electronic micro-and nanostructures. This thesis explores non-trivial periodic and aperiodic dielectric nano-structures and to do so, we pose a photonic crystal design process guided by non-convex combinatory optimization techniques. In addition, this thesis proposes some novel coupling devices optimized to minimize insertion losses between silicon-on-insulator integrated waveguides and single mode optical fibers. Last but not least, this thesis explores periodic arrangements from a new perspective and reports on the first experimental evidence of topologically protected waveguiding in silicon. Furthermore, we propose and demonstrate that, in a system where topological and trivial defect modes coexist, we can probe them independently. Tuning the configuration of the interface, we observe the transition between a single topological defect and a compound trivial defect state

Designing periodic and aperiodic structures for nanophotinic devices.

330 p.Future all--optical networks will require to substitute the present electronic integrated circuitry by optical analogous devices that satisfy the compactness, throughput, latency and high transmission efficiency requirements in nanometer scale dimensions, outperforming the functionality of current networks. Thereby, existing dielectric materials do not confine light in a sufficiently small scale and so the physical size of these links and devices becomes unacceptable. In fact, if the optical chip does not exist in the liking of the electronic chip, photonic crystals have recently led to great hopes for a large-scale integration of optoelectronic components. Two-dimensional photonic crystals slabs obtained through periodic structuring of a planar optical waveguide, feature many characteristics which bring them closer to electronic micro-and nanostructures. This thesis explores non-trivial periodic and aperiodic dielectric nano-structures and to do so, we pose a photonic crystal design process guided by non-convex combinatory optimization techniques. In addition, this thesis proposes some novel coupling devices optimized to minimize insertion losses between silicon-on-insulator integrated waveguides and single mode optical fibers. Last but not least, this thesis explores periodic arrangements from a new perspective and reports on the first experimental evidence of topologically protected waveguiding in silicon. Furthermore, we propose and demonstrate that, in a system where topological and trivial defect modes coexist, we can probe them independently. Tuning the configuration of the interface, we observe the transition between a single topological defect and a compound trivial defect state

Novel Light Coupling Systems Devised Using a Harmony Search Algorithm Approach

We report a critical assessment of the use of an Inverse Design (ID) approach steamed by an improved Harmony Search (IHS) algorithm for enhancing light coupling to densely integrated photonic integratic circuits (PICs) using novel grating structures. Grating couplers, performing as a very attractive vertical coupling scheme for standard silicon nano waveguides are nowadays a custom component in almost every PIC. Nevertheless, their efficiency can be highly enhanced by using our ID methodology that can deal simultaneously with many physical and geometrical parameters. Moreover, this method paves the way for designing more sophisticated non-uniform gratings, which not only match the coupling efficiency of conventional periodic corrugated waveguides, but also allow to devise more complex components such as wavelength or polarization splitters, just to cite some

A methodology and experimental implementation for industrial robot health assessment via torque signature analysis

This manuscript focuses on methodological and technological advances in the field of health assessment and predictive maintenance for industrial robots. We propose a non-intrusive methodology for industrial robot joint health assessment. Torque sensor data is used to create a digital signature given a defined trajectory and load combination. The signature of each individual robot is later used to diagnose mechanical deterioration. We prove the robustness and reliability of the methodology in a real industrial use case scenario. Then, an in depth mechanical inspection is carried out in order to identify the root cause of the failure diagnosed in this article. The proposed methodology is useful for medium and long term health assessment for industrial robots working in assembly lines, where years of almost uninterrupted work can cause irreversible damage

Optical Dual Laser Based Sensor Denoising for OnlineMetal Sheet Flatness Measurement Using Hermite Interpolation

Flatness sensors are required for quality control of metal sheets obtained from steel coils by roller leveling and cutting systems. This article presents an innovative system for real-time robust surface estimation of flattened metal sheets composed of two line lasers and a conventional 2D camera. Laser plane triangulation is used for surface height retrieval along virtual surface fibers. The dual laser allows instantaneous robust and quick estimation of the fiber height derivatives. Hermite cubic interpolation along the fibers allows real-time surface estimation and high frequency noise removal. Noise sources are the vibrations induced in the sheet by its movements during the process and some mechanical events, such as cutting into separate pieces. The system is validated on synthetic surfaces that simulate the most critical noise sources and on real data obtained from the installation of the sensor in an actual steel mill. In the comparison with conventional filtering methods, we achieve at least a 41% of improvement in the accuracy of the surface reconstruction

Depth Data Denoising in Optical Laser Based Sensors for Metal Sheet Flatness Measurement: A Deep Learning Approach

Surface flatness assessment is necessary for quality control of metal sheets manufactured from steel coils by roll leveling and cutting. Mechanical-contact-based flatness sensors are being replaced by modern laser-based optical sensors that deliver accurate and dense reconstruction of metal sheet surfaces for flatness index computation. However, the surface range images captured by these optical sensors are corrupted by very specific kinds of noise due to vibrations caused by mechanical processes like degreasing, cleaning, polishing, shearing, and transporting roll systems. Therefore, high-quality flatness optical measurement systems strongly depend on the quality of image denoising methods applied to extract the true surface height image. This paper presents a deep learning architecture for removing these specific kinds of noise from the range images obtained by a laser based range sensor installed in a rolling and shearing line, in order to allow accurate flatness measurements from the clean range images. The proposed convolutional blind residual denoising network (CBRDNet) is composed of a noise estimation module and a noise removal module implemented by specific adaptation of semantic convolutional neural networks. The CBRDNet is validated on both synthetic and real noisy range image data that exhibit the most critical kinds of noise that arise throughout the metal sheet production process. Real data were obtained from a single laser line triangulation flatness sensor installed in a roll leveling and cut to length line. Computational experiments over both synthetic and real datasets clearly demonstrate that CBRDNet achieves superior performance in comparison to traditional 1D and 2D filtering methods, and state-of-the-art CNN-based denoising techniques. The experimental validation results show a reduction in error than can be up to 15% relative to solutions based on traditional 1D and 2D filtering methods and between 10% and 3% relative to the other deep learning denoising architectures recently reported in the literature.This work was partially supported by by FEDER funds through MINECO project TIN2017-85827-P, and ELKARTEK funded projects ENSOL2 and CODISAVA2 (KK-202000077 and KK-202000044) supported by the Basque Governmen

Designing periodic and aperiodic structures for nanophotinic devices.

330 p.Future all--optical networks will require to substitute the present electronic integrated circuitry by optical analogous devices that satisfy the compactness, throughput, latency and high transmission efficiency requirements in nanometer scale dimensions, outperforming the functionality of current networks. Thereby, existing dielectric materials do not confine light in a sufficiently small scale and so the physical size of these links and devices becomes unacceptable. In fact, if the optical chip does not exist in the liking of the electronic chip, photonic crystals have recently led to great hopes for a large-scale integration of optoelectronic components. Two-dimensional photonic crystals slabs obtained through periodic structuring of a planar optical waveguide, feature many characteristics which bring them closer to electronic micro-and nanostructures. This thesis explores non-trivial periodic and aperiodic dielectric nano-structures and to do so, we pose a photonic crystal design process guided by non-convex combinatory optimization techniques. In addition, this thesis proposes some novel coupling devices optimized to minimize insertion losses between silicon-on-insulator integrated waveguides and single mode optical fibers. Last but not least, this thesis explores periodic arrangements from a new perspective and reports on the first experimental evidence of topologically protected waveguiding in silicon. Furthermore, we propose and demonstrate that, in a system where topological and trivial defect modes coexist, we can probe them independently. Tuning the configuration of the interface, we observe the transition between a single topological defect and a compound trivial defect state

Phase-shifted imaging on multi-directional induction thermography

Abstract A novel multi-directional eddy current thermography (ECT) system is presented generating sets of directional phase images that have been fused with a processing pipeline allowing for an improved probability of detection (POD). Inhomogeneous electromagnetic Joule heating derived from the diversion of induced eddy currents provoked by cracks, altering its path around as well as under its bottom, is the principal phenomenon enabling its usage as a non-destructive-evaluation (NDE) technique. Most induction thermography systems employ inductors derived from old designs, optimized for localized heating with a fixed magnetic field direction. This provokes a directional detection blind-spot for surfaces with random crack orientations. In this paper we have observed that the pattern associated with the thermal response distribution can be geometrically correlated to the relative orientation of the magnetic field regarding the crack, conforming to a rotating feature that has not been described before. Extracting the apparent motion as an optical flow, with a phase-shifting interpolation of the intermediate orientations, generates a signal that enables a robust segmentation of a wide variety of defects in ferritic and austenitic alloys. Its performance has been evaluated with two ‘Hit/Miss’ POD studies TIG welds Inconel 718 and Haynes 282 alloys. Results show an increased detectability regarding the manual labelling of the defects in the same directional set, employing the same input