Fuel level sensor based on polymer optical fiber Bragg gratings for aircraft applications

Safety in civil aviation is increasingly important due to the increase in flight routes and their more challenging nature. Like other important systems in aircraft, fuel level monitoring is always a technical challenge. The most frequently used level sensors in aircraft fuel systems are based on capacitive, ultrasonic and electric techniques, however they suffer from intrinsic safety concerns in explosive environments combined with issues relating to reliability and maintainability. In the last few years, optical fiber liquid level sensors (OFLLSs) have been reported to be safe and reliable and present many advantages for aircraft fuel measurement. Different OFLLSs have been developed, such as the pressure type, float type, optical radar type, TIR type and side-leaking type. Amongst these, many types of OFLLSs based on fiber gratings have been demonstrated. However, these sensors have not been commercialized because they exhibit some drawbacks: low sensitivity, limited range, long-term instability, or limited resolution. In addition, any sensors that involve direct interaction of the optical field with the fuel (either by launching light into the fuel tank or via the evanescent field of a fiber-guided mode) must be able to cope with the potential build up of contamination-often bacterial-on the optical surface. In this paper, a fuel level sensor based on microstructured polymer optical fiber Bragg gratings (mPOFBGs), including poly (methyl methacrylate) (PMMA) and TOPAS fibers, embedded in diaphragms is investigated in detail. The mPOFBGs are embedded in two different types of diaphragms and their performance is investigated with aviation fuel for the first time, in contrast to our previous works, where water was used. Our new system exhibits a high performance when compared with other previously published in the literature, making it a potentially useful tool for aircraft fuel monitoring.

Apports de la texture multibande dans la classification orientée-objets d'images multisources (optique et radar).

Résumé : La texture dispose d’un bon potentiel discriminant qui complète celui des paramètres radiométriques dans le processus de classification d’image. L’indice Compact Texture Unit (CTU) multibande, récemment mis au point par Safia et He (2014), permet d’extraire la texture sur plusieurs bandes à la fois, donc de tirer parti d’un surcroît d’informations ignorées jusqu’ici dans les analyses texturales traditionnelles : l’interdépendance entre les bandes. Toutefois, ce nouvel outil n’a pas encore été testé sur des images multisources, usage qui peut se révéler d’un grand intérêt quand on considère par exemple toute la richesse texturale que le radar peut apporter en supplément à l’optique, par combinaison de données. Cette étude permet donc de compléter la validation initiée par Safia (2014) en appliquant le CTU sur un couple d’images optique-radar. L’analyse texturale de ce jeu de données a permis de générer une image en « texture couleur ». Ces bandes texturales créées sont à nouveau combinées avec les bandes initiales de l’optique, avant d’être intégrées dans un processus de classification de l’occupation du sol sous eCognition. Le même procédé de classification (mais sans CTU) est appliqué respectivement sur : la donnée Optique, puis le Radar, et enfin la combinaison Optique-Radar. Par ailleurs le CTU généré sur l’Optique uniquement (monosource) est comparé à celui dérivant du couple Optique-Radar (multisources). L’analyse du pouvoir séparateur de ces différentes bandes à partir d’histogrammes, ainsi que l’outil matrice de confusion, permet de confronter la performance de ces différents cas de figure et paramètres utilisés. Ces éléments de comparaison présentent le CTU, et notamment le CTU multisources, comme le critère le plus discriminant ; sa présence rajoute de la variabilité dans l’image permettant ainsi une segmentation plus nette, une classification à la fois plus détaillée et plus performante. En effet, la précision passe de 0.5 avec l’image Optique à 0.74 pour l’image CTU, alors que la confusion diminue en passant de 0.30 (dans l’Optique) à 0.02 (dans le CTU).

Low-altitude signatures of the cusp and flux transfer events

The usual interpretation of a flux transfer event (FTE) at the magnetopause, in terms of time-dependent and possibly patchy reconnection, demands that it generate an ionospheric signature. Recent ground-based observations have revealed that auroral transients in the cusp/cleft region have all the characteristics required of FTE effects. However, signatures in the major available dataset, namely that from low-altitude polar-orbiting satellites, have not yet been identified. In this paper, we consider a cusp pass of the DE-2 spacecraft during strongly southward IMF. The particle detectors show magnetosheath ion injection signatures. However, the satellite motion and convection are opposed, and we discuss how the observed falling energy dispersion of the precipitating ions can have arisen from a static, moving or growing source. The spatial scale of the source is typical of an FTE. A simple model of the ionospheric signature of an FTE reproduces the observed electric and magnetic field perturbations. Precipitating electrons of peak energy ∼100eV are found to lie on the predicted boundary of the newly-opened tube, very similar to those found on the edges of FTEs at the magnetopause. The injected ions are within this boundary and their dispersion is consistent with its growth as reconnection proceeds. The reconnection potential and the potential of the induced ionospheric motion are found to be the same (≃25kV). The scanning imager on DE-1 shows a localised transient auroral feature around DE-2 at this time, similar to the recent optical/radar observations of FTEs.

Lidar observation campaign of sugar cane fires and industrial emissions in the State of São Paulo, Brazil

Brazil has an important role in the biomass burning, with the detection of approximately 100,000 burning spots in a single year (2007). Most of these spots occur in the southern part of the Amazon basin during the dry season (from August to november) and these emissions reach the southeast of the country, a highly populated region and with serious urban air pollution problems. With the growing demand on biofuels, sugarcane is considerably expanding in the state of São Paulo, being a strong contributor to the bad air quality in this region. In the state of São Paulo, the main land use are pasture and sugarcane crop, that covers around 50% and 10% of the total area, respectively. Despite the aerosol from sugarcane burning having reduced atmospheric residence time, from a few days to some weeks, they might get together with those aerosol which spread over long distances (hundreds to thousands of kilometers). In the period of June through February 2010 a LIDAR observation campaign was carried in the state of São Paulo, Brazil, in order to observe and characterize optically the aerosols from two distinct sources, namely, sugar cane biomass burning and industrial emissions. For this purpose 2 LIDAR systems were available, one mobile and the other placed in a laboratory, both working in the visible (532 nm) and additionally the mobile system had a Raman channel available (607 nm). Also this campaign counted with a SODAR, a meteorological RADAR specially set up to detect aerosol echoes and gas-particle analyzers. To guarantee a good regional coverage 4 distinct sites were available to deploy the instruments, 2 in the near field of biomass burning activities (Rio Claro and Bauru), one for industrial emissions (Cubatão) and others from urban sources (São Paulo). The whole campaign provide the equivalent of 30 days of measurements which allowed us to get aerosol optical properties such as backscattering/extinction coefficients, scatter and LIDAR ratios, those were used to correlate with air quality and meteorological indicators and quantities. In this paper we should focus on the preliminary results of the Raman LIDAR system and its derived aerosol optical quantities. © 2010 Copyright SPIE - The International Society for Optical Engineering.

Remote Sensing Detection of atmospheric pollutants using Lidar, Sodar and correlation with air quality data in an industrial area

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of São Paulo, in the city of Cubatão, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar. © 2011 SPIE.

Initial analysis from a Lidar observation campaign of sugar cane fires in the central and western portion of the S̃ao Paulo State - Brazil

The central and western portion of the S̃ao Paulo State has large areas of sugar cane plantations, and due to the growing demand for biofuels, the production is increasing every year. During the harvest period some plantation areas are burnt a few hours before the manual cutting, causing significant quantities of biomass burning aerosol to be injected into the atmosphere. During August 2010, a field campaign has been carried out in Ourinhos, situated in the south-western region of S̃ao Paulo State. A 2-channel Raman Lidar system and two meteorological S-Band Doppler Radars are used to indentify and quantify the biomass burning plumes. In addiction, CALIPSO Satellite observations were used to compare the aerosol optical properties detected in that region with those retrieved by Raman Lidar system. Although the campaign yielded 30 days of measurements, this paper will be focusing only one case study, when aerosols released from nearby sugar cane fires were detected by the Lidar system during a CALIPSO overpass. The meteorological radar, installed in Bauru, approximately 110 km northeast from the experimental site, had recorded echoes (dense smoke comprising aerosols) from several fires occurring close to the Raman Lidar system, which also detected an intense load of aerosol in the atmosphere. HYSPLIT model forward trajectories presented a strong indication that both instruments have measured the same air masss parcels, corroborated with the Lidar Ratio values from the 532 nm elastic and 607 nm Raman N2 channel analyses and data retrieved from CALIPSO have indicated the predominance of aerosol from biomass burning sources. © 2011 SPIE.

Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

Boston, Massachusetts Region LIDAR First Return Elevation Data, 2002

LIDAR (LIght Detection And Ranging) first return elevation data of the Boston, Massachusetts region from MassGIS at 1-meter resolution. This LIDAR data was captured in Spring 2002. LIDAR first return data (which shows the highest ground features, e.g. tree canopy, buildings etc.) can be used to produce a digital terrain model of the Earth's surface. This dataset consists of 74 First Return DEM tiles. The tiles are 4km by 4km areas corresponding with the MassGIS orthoimage index. This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). The area of coverage corresponds to the following MassGIS orthophoto quads covering the Boston region (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001 and was used to produce the MassGIS dataset: Boston, Massachusetts, 2-Dimensional Building Footprints with Roof Height Data (from LIDAR data), 2002 [see cross references].