Very recently, we proposed a novel concept for a mid-infrared bandpass filter based on a single linearly chirped Bragg grating. [1] By its design, the filter structure features a large rejection bandwidth and can be used to create narrowband emitters in the mid-infrared region. Here we present results for a specific filter design for silicon waveguides, which features transmission wavelength and bandwidth well suited for carbon dioxide sensing.

Simulations were performed using Comsol Multiphysics® and the design was optimized for a central wavelength of 4.26 µm. Furthermore, we included real-world effects like the discrete resolution of the design grid as well as process specific fabrication tolerances. The devised structures were based on a photonic waveguide concept, which was developed recently for evanescent-field based sensing applications. [2] In short, a thick SiO₂ cladding layer and an intermediate thin Si₃N₄ layer with a thickness of 140 nm are deposited on a Si substrate. The waveguide itself consists of poly-silicon and it is deposited on top of the S₃N₄ layer with a height of 660 nm. Slab waveguides with gratings on top (with a modulation depth of 100 nm) as well as strip waveguides with sidewall gratings were investigated.

The concept and design are discussed in detail and very first results from the first fabrication run of test structures are presented.

[1] C. Ranacher, B. Jakoby, C. Consani, A. Tortschanoff, “Design of a Mid-Infrared Bandpass Filter With Large Rejection Bandwidth of Silicon Photonics,” J. of Lightwave Technology, vol. 37, no 15, pp. 3770-3776, 2019

[2] C. Ranacher, C. Consani, N. Vollert, A. Tortschanoff, M. Bergmeister, T. Grille, and B. Jakoby, “Characterization of evanescent field gas sensor structures based on silicon photonics,” IEEE Photonics Journal , vol. 10, no. 5, pp. 1–14, 2018

Greenhouse detection is important with respect to urban and rural planning, yield estimation and crop planning, sustainable development, natural resource management, risk analysis and damage assessment. The fast and accurate detection of greenhouses automaticaly from remote sensing imagery saves labour and time. The aim of this study is to detect greenhouse areas by using color and infrared orthophoto (RGB-NIR), topographic map and Digital Surface Model (DSM). The study was implemented in Kumluca district of Antalya, Turkey which includes intensive greenhouse areas. In this study, color and infrared orthophotos, normalized Digital Surface Model (nDSM), Normalized Difference Vegetation Index (NDVI) and Visible Red-based Built-up Index (VrNIR_BI) were used and the greenhouse areas were detected using Object Based Image Analysis (OBIA). In this process, the optimum scale parameter was determined automatically by the Estimation of Scale Parameter2 (ESP2) tool and Multi Resolution Segmentation (MRS) was used as the segmentation algorithm. In the classification stage, K-Nearest Neighbor (K-NN), Random Forest (RF) and Support Vector Machine (SVM) classification techniques were used and the accuracies of the classification results were compared. The classification with the highest accuracy was determined and the class numbers were reduced to two classes as greenhouse and non-greenhouse areas. Obtained results showed that greenhouse areas can be determined from color and infrared orthophoto and DSM data successfully by using the OBIA. The highest overall accuracy was obtained when the SVM classifier was used with 94.80%.

The results of investigation of the electrical resistivity of thin films Ga₂O₃:Si under the influence of oxygen in the range of O₂ from 9 to 100 vol. % and changes in the heating temperature of structures from 25 to 700 °C were presented. Thin films of Ga₂O₃ were obtained by RF magnetron sputtering. The possibility of developing of oxygen sensors based on thin films Ga₂O₃:Si with a temperature of maximum response 400 °C was shown. Oxygen influence leads to a reversible increase in the samples’ resistance due to the interaction between adsorbed oxygen particles and superstoichiometric Ga³⁺ atoms in the semiconductor’s near-surface part. The mechanism of Si influence on gas-sensitive properties of Ga₂O₃ was offered.

The paper describes development of algorithm robotic plug-in of charging system for mobile platform. In the first chapter, there is short overview of possibilities of automatic plug-in system, include proprietary industrial solution. In the main part, there is a description of system based on UR robot with build-in force torque sensors and Intel RealSense Camera. This camera combines IR depth lens with regular RGB camera and 6 DOF inertial sensor, which is used in our application too.

The conventional solution of this problem is usually based on RGB image processing in various state of art, from simple pattern matching, neural network or genetic algorithm to complex AI solution. The quality of the solution mostly depends on robustness of image processing.

In our cases, we use simple sensor fusion. Thanks to multiple information and constrain of values, we can assume, if algorithm is proceeding successfully or not. The system uses the internal parameters of the robotic arm, e.g. end-effector position and orientation and force-torque information in tool center point. The next information is RGB camera image and camera depth image, and the inertial unit build in camera. The other important information is location of CCS plug on the mobile platform, where the shape of mobile platform is considered as constrain for image processing.

The algorithm is written in Matlab, with support of Intel SDK for camera communication. For Universal Robot control is used TCP-IP communication and multithread program with subroutines and events for robot control is briefly mentioned in the paper too.

The system is validated only on physical model with CCS plug and socket, because the mobile platform is under construction by other team.

A novel microwave high-resolution near-field non-destructive testing technique is proposed and experimentally evaluated in reflectometry imaging scenarios involving planar metal surfaces. Traditionally, microwave reflectometry does not provide high dynamic contrast between the defect and background material in case of metal structures due to intrinsically high reflection magnitude from the metal surfaces masking defect microwave signature. A high-Q resonant sensor based on the loaded aperture is designed to interact very strongly even with small defects on the metal surface providing very high two-dimensional spatial resolution of approximately one tenth of a wavelength, λ, at λ/20-λ/10 standoff distance. Experimental results demonstrate defect-to-background contrast greater than 5 dB amplitude and 50° phase in raw microwave data. To further enhance the spatial resolution and defect contrast, two techniques are proposed and experimentally evaluated: 1) phase-modulated near field imaging is based on sharp variation of the reflection phase in the narrow frequency band, which essentially enables elimination of background microwave signature from the reflected signal; 2) numerical cross-correlation signal processing that allows for defect signature enhancement by numerical elimination of the background response. The proposed imaging technique should find applications in non-destructive surface testing and evaluation of metal and alloy structures and elements of construction.

This study aims to show the influences of the sensor installation interface on the industrial environment. This contribution is focused on analyzing the response behavior of piezoelectric transducers subjected to successive installations, using digital signal processing and non-destructive structural health monitoring (SHM) techniques. Tests were performed to simulate the installation conditions of a piezoelectric sensor, which was coupled to a holder carrying a steel body and submitted to successive reinstallations. Different signals were obtained for each installation, and the results can bring initial elucidations on the subject and pave the way for future studies.

The microstrip patch antenna sensor is a novel sensor used for structural health monitoring which can measure metal structure’s crack defects in a wireless manner. However, it is difficult to identify the reflected signal from the signal of antenna sensor. The radio-frequency identification (RFID) antenna sensor, which combines RFID technology and the microstrip patch antenna sensor, can solve the measurement problems that are difficult to the conventional wireless testing technologies. In this study, a dual-chip RFID antenna sensor was designed. The influence of the wireless testing method on the monitoring results of crack defects was investigated by tests, including the wireless tests of resonant frequency and the crack sensitivity tests. The tests results revealed that the antenna sensor had good wireless testing performance with regard to the metal structure’s crack defects. And the maximum of wireless identification distance reached 1.96 m.

Microgrids are one of the main drivers in achieving sustainable energy management in the context of Smart Cities and Smart Regions. In this way, multiple energy sources are employed and overall system performance is given by adequate information handling in terms of energy consumption requirements as well as user behavior profiles. This paper introduces a framework for a Wireless mesh communication, monitoring, and distributed energy management for domestic Microgrids. A communication scheme based on a combination of sensors which describe energy consumption profiles (i.e., current probes, power consumption level at different loads), environmental (temperature, humidity and illumination level) as well as user behavior profiles (presence sensor detectors) is employed in order to provide an interactive scenario in terms of management of multiple energy sources. Practical tests have been performed by using a XBee ZigBee network in a meshed configuration connected to an experimental microgrid implemented at UPNA. The system has been implemented in order to provide cloud enabled data gathering, sending the required information via web services to a private cloud. These initial results are being scaled with the aim of providing a multi-microgrid communication and control scheme.

Poly(vinylalcohol-co-vinylacetal)s were synthesized at mild reaction conditions in aqueous media at 30°C [1]. The copolymer composition was controlled by PVA-to-acetaldehyde molar ratio. Polymers thin films of varied copolymer composition were deposited on silicon substrate using water-methanol solution in a volume ratio of 80:20 and concentration of 1 wt%. Films were subjected to low (60^oC) and moderate (180^oC) temperature annealing in order to study the temperature influence on optical and humidity sensing properties. Refractive index, extinction coefficient along with thickness of the films were determined from reflectance spectra measured at normal light incidence and non-linear minimization of the goal function comprising measured and calculated spectra. The humidity sensing ability of the films was studied through reflectance measurements at different humidity levels in the range 5-95%RH. The influence of temperature annealing on optical and sensing properties is demonstrated and discussed.

References:

[1] D. Christova, S. Ivanova, G. Ivanova, Polymer Bulletin, 50, 367-372 (2003).

Acknowledgments: The financial support of Bulgarian National Science Fund, grant number DN08-15/14.12.2016 is highly appreciated. K. Lazarova and S. Bozhilova acknowledge the National Scientific Program for young scientists and postdoctoral fellows (РМС № 577 / 17.08.2018) for scholarship.

Rail inspection is required and aims at ensuring safety and preserving the availability of railway infrastructure. According to the statistics published by world railroad administrations, the transverse fissure appearing in railhead is the principal cause of rail accidents. These particular defects are initiated inside the railhead. Detection of these cracks has always been challenging to perform as defect signature remains mostly small until the defect size reaches a significant value. Early detection of transverse like defects constitutes then a real challenge to improve the security of railways and to prevent catastrophic failures. Most of the inspection techniques of rails relay on eddy currents, infrared thermography, and ultrasounds. Inspection tests have been conducted conventionally by using contact excitation probes that roll on the railhead. Modern inspection methods use contact-less devices such as those relying on laser excitation of the rail and air-coupled acoustic sensors for echo reception. The present work deals with the theoretical analysis of an integrated contact-less system for rail diagnosis, which is based on ultrasounds. The generation of these waves is performed through non-ablative laser sources. Rotational laser vibrometry was used to achieve the reception of the echoes. Detection of flaws in the rail was monitored by considering special ultrasound wave signal based indicators. Finite element modeling of the rail system was performed, and transverse defect detection of the rail was analyzed.