272 resultados para infrared sensing


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The chief challenge facing persistent robotic navigation using vision sensors is the recognition of previously visited locations under different lighting and illumination conditions. The majority of successful approaches to outdoor robot navigation use active sensors such as LIDAR, but the associated weight and power draw of these systems makes them unsuitable for widespread deployment on mobile robots. In this paper we investigate methods to combine representations for visible and long-wave infrared (LWIR) thermal images with time information to combat the time-of-day-based limitations of each sensing modality. We calculate appearance-based match likelihoods using the state-of-the-art FAB-MAP [1] algorithm to analyse loop closure detection reliability across different times of day. We present preliminary results on a dataset of 10 successive traverses of a combined urban-parkland environment, recorded in 2-hour intervals from before dawn to after dusk. Improved location recognition throughout an entire day is demonstrated using the combined system compared with methods which use visible or thermal sensing alone.

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In this thesis, the author proposed and developed gas sensors made of nanostructured WO3 thin film by a thermal evaporation technique. This technique gives control over film thickness, grain size and purity. The device fabrication, nanostructured material synthesis, characterization and gas sensing performance have been undertaken. Three different types of nanostructured thin films, namely, pure WO3 thin films, iron-doped WO3 thin films by co-evaporation and Fe-implanted WO3 thin films have been synthesized. All the thin films have a film thickness of 300 nm. The physical, chemical and electronic properties of these films have been optimized by annealing heat treatment at 300ºC and 400ºC for 2 hours in air. Various analytical techniques were employed to characterize these films. Atomic Force Microscopy and Transmission Electron Microscopy revealed a very small grain size of the order 5-10 nm in as-deposited WO3 films, and annealing at 300ºC or 400ºC did not result in any significant change in grain size. X-ray diffraction (XRD) analysis revealed a highly amorphous structure of as-deposited films. Annealing at 300ºC for 2 hours in air did not improve crystallinity in these films. However, annealing at 400ºC for 2 hours in air significantly improved the crystallinity in pure and iron-doped WO3 thin films, whereas it only slightly improved the crystallinity of iron-implanted WO3 thin film as a result of implantation. Rutherford backscattered spectroscopy revealed an iron content of 0.5 at.% and 5.5 at.% in iron-doped and iron-implanted WO3 thin films, respectively. The RBS results have been confirmed using energy dispersive x-ray spectroscopy (EDX) during analysis of the films using transmission electron microscopy (TEM). X-ray photoelectron spectroscopy (XPS) revealed significant lowering of W 4f7/2 binding energy in all films annealed at 400ºC as compared with the as-deposited and 300ºC annealed films. Lowering of W 4f7/2 is due to increase in number of oxygen vacancies in the films and is considered highly beneficial for gas sensing. Raman analysis revealed that 400ºC annealed films except the iron-implanted film are highly crystalline with significant number of O-W-O bonds, which was consistent with the XRD results. Additionally, XRD, XPS and Raman analyses showed no evidence of secondary peaks corresponding to compounds of iron due to iron doping or implantation. This provided an understanding that iron was incorporated in the host WO3 matrix rather than as a separate dispersed compound or as catalyst on the surface. WO3 thin film based gas sensors are known to operate efficiently in the temperature range 200ºC-500 ºC. In the present study, by optimizing the physical, chemical and electronic properties through heat treatment and doping, an optimum response to H2, ethanol and CO has been achieved at a low operating temperature of 150ºC. Pure WO3 thin film annealed at 400ºC showed the highest sensitivity towards H2 at 150ºC due to its very small grain size and porosity, coupled with high number of oxygen vacancies, whereas Fe-doped WO3 film annealed at 400ºC showed the highest sensitivity to ethanol at an operating temperature of 150ºC due to its crystallinity, increased number of oxygen vacancies and higher degree of crystal distortions attributed to Fe addition. Pure WO3 films are known to be insensitive to CO, but iron-doped WO3 thin film annealed at 300ºC and 400ºC showed an optimum response to CO at an operating temperature of 150ºC. This result is attributed to lattice distortions produced in WO3 host matrix as a result of iron incorporation as substitutional impurity. However, iron-implanted WO3 thin films did not show any promising response towards the tested gases as the film structure has been damaged due to implantation, and annealing at 300ºC or 400ºC was not sufficient to induce crystallinity in these films. This study has demonstrated enhanced sensing properties of WO3 thin film sensors towards CO at lower operating temperature, which was achieved by optimizing the physical, chemical and electronic properties of the WO3 film through Fe doping and annealing. This study can be further extended to systematically investigate the effects of different Fe concentrations (0.5 at.% to 10 at.%) on the sensing performance of WO3 thin film gas sensors towards CO.

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There is a need for an accurate real-time quantitative system that would enhance decision-making in the treatment of osteoarthritis. To achieve this objective, significant research is required that will enable articular cartilage properties to be measured and categorized for health and functionality without the need for laboratory tests involving biopsies for pathological evaluation. Such a system would provide the capability of access to the internal condition of the cartilage matrix and thus extend the vision-based arthroscopy that is currently used beyond the subjective evaluation of surgeons. The system required must be able to non-destructively probe the entire thickness of the cartilage and its immediate subchondral bone layer. In this thesis, near infrared spectroscopy is investigated for the purpose mentioned above. The aim is to relate it to the structure and load bearing properties of the cartilage matrix to the near infrared absorption spectrum and establish functional relationships that will provide objective, quantitative and repeatable categorization of cartilage condition outside the area of visible degradation in a joint. Based on results from traditional mechanical testing, their innovative interpretation and relationship with spectroscopic data, new parameters were developed. These were then evaluated for their consistency in discriminating between healthy viable and degraded cartilage. The mechanical and physico-chemical properties were related to specific regions of the near infrared absorption spectrum that were identified as part of the research conducted for this thesis. The relationships between the tissue's near infrared spectral response and the new parameters were modeled using multivariate statistical techniques based on partial least squares regression (PLSR). With significantly high levels of statistical correlation, the modeled relationships were demonstrated to possess considerable potential in predicting the properties of unknown tissue samples in a quick and non-destructive manner. In order to adapt near infrared spectroscopy for clinical applications, a balance between probe diameter and the number of active transmit-receive optic fibres must be optimized. This was achieved in the course of this research, resulting in an optimal probe configuration that could be adapted for joint tissue evaluation. Furthermore, as a proof-of-concept, a protocol for obtaining the new parameters from the near infrared absorption spectra of cartilage was developed and implemented in a graphical user interface (GUI)-based software, and used to assess cartilage-on-bone samples in vitro. This conceptual implementation has been demonstrated, in part by the individual parametric relationship with the near infrared absorption spectrum, the capacity of the proposed system to facilitate real-time, non-destructive evaluation of cartilage matrix integrity. In summary, the potential of the optical near infrared spectroscopy for evaluating articular cartilage and bone laminate has been demonstrated in this thesis. The approach could have a spin-off for other soft tissues and organs of the body. It builds on the earlier work of the group at QUT, enhancing the near infrared component of the ongoing research on developing a tool for cartilage evaluation that goes beyond visual and subjective methods.

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Thermal-infrared imagery is relatively robust to many of the failure conditions of visual and laser-based SLAM systems, such as fog, dust and smoke. The ability to use thermal-infrared video for localization is therefore highly appealing for many applications. However, operating in thermal-infrared is beyond the capacity of existing SLAM implementations. This paper presents the first known monocular SLAM system designed and tested for hand-held use in the thermal-infrared modality. The implementation includes a flexible feature detection layer able to achieve robust feature tracking in high-noise, low-texture thermal images. A novel approach for structure initialization is also presented. The system is robust to irregular motion and capable of handling the unique mechanical shutter interruptions common to thermal-infrared cameras. The evaluation demonstrates promising performance of the algorithm in several environments.

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Carbon nanotubes (CNTs) have excellent electrical, mechanical and electromechanical properties. When CNTs are incorporated into polymers, electrically conductive composites with high electrical conductivity at very low CNT content (often below 1% wt CNT) result. Due to the change in electrical properties under mechanical load, carbon nanotube/polymer composites have attracted significant research interest especially due to their potential for application in in-situ monitoring of stress distribution and active control of strain sensing in composite structures or as strain sensors. To sucessfully develop novel devices for such applications, some of the major challenges that need to be overcome include; in-depth understanding of structure-electrical conductivity relationships, response of the composites under changing environmental conditions and piezoresistivity of different types of carbon nanotube/polymer sensing devices. In this thesis, direct current (DC) and alternating current (AC) conductivity of CNT-epoxy composites was investigated. Details of microstructure obtained by scanning electron microscopy were used to link observed electrical properties with structure using equivalent circuit modeling. The role of polymer coatings on macro and micro level electrical conductivity was investigated using atomic force microscopy. Thermal analysis and Raman spectroscopy were used to evaluate the heat flow and deformation of carbon nanotubes embedded in the epoxy, respectively, and related to temperature induced resistivity changes. A comparative assessment of piezoresistivity was conducted using randomly mixed carbon nanotube/epoxy composites, and new concept epoxy- and polyurethane-coated carbon nanotube films. The results indicate that equivalent circuit modelling is a reliable technique for estimating values of the resistance and capacitive components in linear, low aspect ratio-epoxy composites. Using this approach, the dominant role of tunneling resistance in determining the electrical conductivity was confirmed, a result further verified using conductive-atomic force microscopy analysis. Randomly mixed CNT-epoxy composites were found to be highly sensitive to mechanical strain and temperature variation compared to polymer-coated CNT films. In the vicinity of the glass transition temperature, the CNT-epoxy composites exhibited pronounced resistivity peaks. Thermal and Raman spectroscopy analyses indicated that this phenomenon can be attributed to physical aging of the epoxy matrix phase and structural rearrangement of the conductive network induced by matrix expansion. The resistivity of polymercoated CNT composites was mainly dominated by the intrinsic resistivity of CNTs and the CNT junctions, and their linear, weakly temperature sensitive response can be described by a modified Luttinger liquid model. Piezoresistivity of the polymer coated sensors was dominated by break up of the conducting carbon nanotube network and the consequent degradation of nanotube-nanotube contacts while that of the randomly mixed CNT-epoxy composites was determined by tunnelling resistance between neighbouring CNTs. This thesis has demonstrated that it is possible to use microstructure information to develop equivalent circuit models that are capable of representing the electrical conductivity of CNT/epoxy composites accurately. New designs of carbon nanotube based sensing devices, utilising carbon nanotube films as the key functional element, can be used to overcome the high temperature sensitivity of randomly mixed CNT/polymer composites without compromising on desired high strain sensitivity. This concept can be extended to develop large area intelligent CNT based coatings and targeted weak-point specific strain sensors for use in structural health monitoring.

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Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

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An important component of current models for interstellar and circumstellar evolution is the infrared (IR)spectral data collected from stellar outflows around oxygen-rich stars and from the general interstellar medium [1]. IR spectra from these celestial bodies are usually interpreted as showing the general properties of sub-micron sized silicate grains [2]. Two major features at 10 and 20 microns are reasonably attributed to amorphous olivine or pyroxene (e.g. Mg2Si04 or MgSi03) on the basis of comparisons with natural standards and vapor condensed silicates [3-6]. In an attempt to define crystallisation rates for spectrally amorphous condensates, Nuth and Donn [5] annealed experimentally produced amorphous magnesium silicate smokes at 1000K. On analysing these smokes at various annealing times, Nuth and Donn [5] showed that changes in crystallinity measured by bulk X-ray diffraction occured at longer annealing times (days) than changes measured by IR spectra (a few hours). To better define the onset of crystallinity in these magnesium silicates, we have examined each annealed product using a JEOL 1OOCX analytical electron microscope (AEM). In addition, the development of chemical diversity with annealing has been monitored using energy dispersive spectroscopy of individual grains from areas <20nm in diameter. Furthermore, the crystallisation kinetics of these smokes under ambient, room temperature conditions have been examined using bulk and fourier transform infrared (FTIR)spectra.

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Experimentally obtained Mg.SiO smokes were studied by analytical electron microscopy using the same samples that had been previously characterized by repeated infrared spectroscopy. Analytical electron microscopy shows that unannealed smokes contain some degree of microcrystallinity which increases with increased annealing for up to 30 hr. An SiO2 polymorph (tridymite) and MgO may form contemporaneously as a result of growth of forsterite (Mg2SiO4) microcrystallites in the initially nonstoichiometric smokes. After 4 hr annealing, forsterite and tridymite react to enstatite (MgSiO3). We suggest that infrared spectroscopy and X-ray diffraction analysis should be complemented by detailed analytical electron microscopy to detect budding crystallinity in vapor phase condensates.

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Zinc oxide (ZnO) nanopyramids were synthesized by a one-pot route in a non-aqueous and surfactantfree environment. The synthesized metal oxide was characterized using SEM, XRD, and TEM to investigate the surface morphology and crystallographic phase of the nanostructures. It was observed that the ZnO nanopyramids were of uniform size and symmetrical, with a hexagonal base and height of ∼100 nm. Gas sensing characterization of the ZnO nanopyramids when deposited as thin-film onto conductometric transducers were performed towards NOx and C2H5OH vapor of different concentrations over a temperature range of 22–350 ◦C. It was observed that the sensors responded towards NO2 (10 ppm) and C2H5OH(250 ppm) analytes best at temperatures of 200 and 260 ◦C with a sensor response of 14.5 and 5.72, respectively. The sensors showed satisfactory sensitivity, repeatability as well as fast response and recovery towards both the oxidizing and the reducing analyte. The good performance was attributed to the low amount of organic impurities, large surface-to-volume ratio and high crystallinity of the solvothermally synthesized ZnO nanopyramids.

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Intelligent Transport Systems (ITS) resembles the infrastructure for ubiquitous computing in the car. It encompasses a) all kinds of sensing technologies within vehicles as well as road infrastructure, b) wireless communication protocols for the sensed information to be exchanged between vehicles (V2V) and between vehicles and infrastructure (V2I), and c) appropriate intelligent algorithms and computational technologies that process these real-time streams of information. As such, ITS can be considered a game changer. It provides the fundamental basis of new, innovative concepts and applications, similar to the Internet itself. The information sensed or gathered within or around the vehicle has led to a variety of context-aware in-vehicular technologies within the car. A simple example is the Anti-lock Breaking System (ABS), which releases the breaks when sensors detect that the wheels are locked. We refer to this type of context awareness as vehicle/technology awareness. V2V and V2I communication, often summarized as V2X, enables the exchange and sharing of sensed information amongst cars. As a result, the vehicle/technology awareness horizon of each individual car is expanded beyond its observable surrounding, paving the way to technologically enhance such already advanced systems. In this chapter, we draw attention to those application areas of sensing and V2X technologies, where the human (driver), the human’s behavior and hence the psychological perspective plays a more pivotal role. The focal points of our project are illustrated in Figure 1: In all areas, the vehicle first (1) gathers or senses information about the driver. Rather than to limit the use of such information towards vehicle/technology awareness, we see great potential for applications in which this sensed information is then (2) fed back to the driver for an increased self-awareness. In addition, by using V2V technologies, it can also be (3) passed to surrounding drivers for an increased social awareness, or (4), pushed even further, into the cloud, where it is collected and visualized for an increased, collective urban awareness within the urban community at large, which includes all city dwellers.

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This paper details the progress to date, toward developing a small autonomous helicopter. We describe system architecture, avionics, visual state estimation, custom IMU design, aircraft modelling, as well as various linear and neuro/fuzzy control algorithms. Experimental results are presented for state estimation using fused stereo vision and IMU data, heading control, and attitude control. FAM attitude and velocity controllers have been shown to be effective in simulation.

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In this research, we have used vibrational spectroscopy to study the phosphate mineral kosnarite KZr2(PO4)3. Interest in this mineral rests with the ability of zirconium phosphates (ZP) to lock in radioactive elements. ZP have the capacity to concentrate and immobilize the actinide fraction of radioactive phases in homogeneous zirconium phosphate phases. The Raman spectrum of kosnarite is characterized by a very intense band at 1,026 cm−1 assigned to the symmetric stretching vibration of the PO4 3− ν1 symmetric stretching vibration. The series of bands at 561, 595 and 638 cm−1 are assigned to the ν4 out-of-plane bending modes of the PO4 3− units. The intense band at 437 cm−1 with other bands of lower wavenumber at 387, 405 and 421 cm−1 is assigned to the ν2 in-plane bending modes of the PO4 3− units. The number of bands in the antisymmetric stretching region supports the concept that the symmetry of the phosphate anion in the kosnarite structure is preserved. The width of the infrared spectral profile and its complexity in contrast to the well-resolved Raman spectrum show that the pegmatitic phosphates are better studied with Raman spectroscopy.

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The mineral beryllonite has been characterized by the combination of Raman spectroscopy and infrared spectroscopy. SEM–EDX was used for the chemical analysis of the mineral. The intense sharp Raman band at 1011 cm-1, was assigned to the phosphate symmetric stretching mode. Raman bands at 1046, 1053, 1068 and the low intensity bands at 1147, 1160 and 1175 cm-1 are attributed to the phosphate antisymmetric stretching vibrations. The number of bands in the antisymmetric stretching region supports the concept of symmetry reduction of the phosphate anion in the beryllonite structure. This concept is supported by the number of bands found in the out-of-plane bending region. Multiple bands are also found in the in-plane bending region with Raman bands at 399, 418, 431 and 466 cm-1. Strong Raman bands at 304 and 354 cm-1 are attributed to metal oxygen vibrations. Vibrational spectroscopy served to determine the molecular structure of the mineral. The pegmatitic phosphate minerals such as beryllonite are more readily studied by Raman spectroscopy than infrared spectroscopy.

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Detailed investigation of an intermediate member of the reddingite–phosphoferrite series, using infrared and Raman spectroscopy, scanning electron microcopy and electron microprobe analysis, has been carried out on a homogeneous sample from a lithium-bearing pegmatite named Cigana mine, near Conselheiro Pena, Minas Gerais, Brazil. The determined formula is (Mn1.60Fe1.21Ca0.01Mg0.01)∑2.83(PO4)2.12⋅(H2O2.85F0.01)∑2.86 indicating predominance in the reddingite member. Raman spectroscopy coupled with infrared spectroscopy supports the concept of phosphate, hydrogen phosphate and dihydrogen phosphate units in the structure of reddingite-phosphoferrite. Infrared and Raman bands attributed to water and hydroxyl stretching modes are identified. Vibrational spectroscopy adds useful information to the molecular structure of reddingite–phosphoferrite.