Aerial image analysis using spiking neural networks with application to power line corridor monitoring

Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

Reactive image-based collision avoidance system for unmanned aircraft systems

Approximately 20 years have passed now since the NTSB issued its original recommendation to expedite development, certification and production of low-cost proximity warning and conflict detection systems for general aviation [1]. While some systems are in place (TCAS [2]), ¡¨see-and-avoid¡¨ remains the primary means of separation between light aircrafts sharing the national airspace. The requirement for a collision avoidance or sense-and-avoid capability onboard unmanned aircraft has been identified by leading government, industry and regulatory bodies as one of the most significant challenges facing the routine operation of unmanned aerial systems (UAS) in the national airspace system (NAS) [3, 4]. In this thesis, we propose and develop a novel image-based collision avoidance system to detect and avoid an upcoming conflict scenario (with an intruder) without first estimating or filtering range. The proposed collision avoidance system (CAS) uses relative bearing ƒÛ and angular-area subtended ƒê , estimated from an image, to form a test statistic AS C . This test statistic is used in a thresholding technique to decide if a conflict scenario is imminent. If deemed necessary, the system will command the aircraft to perform a manoeuvre based on ƒÛ and constrained by the CAS sensor field-of-view. Through the use of a simulation environment where the UAS is mathematically modelled and a flight controller developed, we show that using Monte Carlo simulations a probability of a Mid Air Collision (MAC) MAC RR or a Near Mid Air Collision (NMAC) RiskRatio can be estimated. We also show the performance gain this system has over a simplified version (bearings-only ƒÛ ). This performance gain is demonstrated in the form of a standard operating characteristic curve. Finally, it is shown that the proposed CAS performs at a level comparable to current manned aviations equivalent level of safety (ELOS) expectations for Class E airspace. In some cases, the CAS may be oversensitive in manoeuvring the owncraft when not necessary, but this constitutes a more conservative and therefore safer, flying procedures in most instances.

Determination of stress-strain characteristics of railhead steel using image analysis

True stress-strain curve of railhead steel is required to investigate the behaviour of railhead under wheel loading through elasto-plastic Finite Element (FE) analysis. To reduce the rate of wear, the railhead material is hardened through annealing and quenching. The Australian standard rail sections are not fully hardened and hence suffer from non-uniform distribution of the material property; usage of average properties in the FE modelling can potentially induce error in the predicted plastic strains. Coupons obtained at varying depths of the railhead were, therefore, tested under axial tension and the strains were measured using strain gauges as well as an image analysis technique, known as the Particle Image Velocimetry (PIV). The head hardened steel exhibit existence of three distinct zones of yield strength; the yield strength as the ratio of the average yield strength provided in the standard (σyr=780MPa) and the corresponding depth as the ratio of the head hardened zone along the axis of symmetry are as follows: (1.17 σyr, 20%), (1.06 σyr, 20%- 80%) and (0.71 σyr, > 80%). The stress-strain curves exhibit limited plastic zone with fracture occurring at strain less than 0.1.

Gaussian process models for sensor-centric robot localisation

This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment

Volume estimation from multiplanar 2D ultrasound images using a remote electromagnetic position and orientation sensor

A system is described for calculating volume from a sequence of multiplanar 2D ultrasound images. Ultrasound images are captured using a video digitising card (Hauppauge Win/TV card) installed in a personal computer, and regions of interest transformed into 3D space using position and orientation data obtained from an electromagnetic device (Polbemus, Fastrak). The accuracy of the system was assessed by scanning 10 water filled balloons (13-141 ml), 10 kidneys (147  200 ml) and 16 fetal livers (8  37 ml) in water using an Acuson 128XP/10 (5 MHz curvilinear probe). Volume was calculated using the ellipsoid, planimetry, tetrahedral and ray tracing methods and compared with the actual volume measured by weighing (balloons) and water displacement (kidneys and livers). The mean percentage error for the ray tracing method was 0.9 ± 2.4%, 2.7 ± 2.3%, 6.6 ± 5.4% for balloons, kidneys and livers, respectively. So far the system has been used clinically to scan fetal livers and lungs, neonate brain ventricles and adult prostate glands.

Gas sensing characteristics of Fe-doped tungsten oxide thin films

This study reports on the gas sensing characteristics of Fe-doped (10 at.%) tungsten oxide thin films of various thicknesses (100–500 nm) prepared by electron beam evaporation. The performance of these films in sensing four gases (H2, NH3, NO2 and N2O) in the concentration range 2–10,000 ppm at operating temperatures of 150–280 °C has been investigated. The results are compared with the sensing performance of a pure WO3 film of thickness 300 nm produced by the same method. Doping of the tungsten oxide film with 10 at.% Fe significantly increases the base conductance of the pure film but decreases the gas sensing response. The maximum response measured in this experiment, represented by the relative change in resistance when exposed to a gas, was ΔR/R = 375. This was the response amplitude measured in the presence of 5 ppm NO2 at an operating temperature of 250 °C using a 400 nm thick WO3:Fe film. This value is slightly lower than the corresponding result obtained using the pure WO3 film (ΔR/R = 450). However it was noted that the WO3:Fe sensor is highly selective to NO2, exhibiting a much higher response to NO2 compared to the other gases. The high performance of the sensors to NO2 was attributed to the small grain size and high porosity of the films, which was obtained through e-beam evaporation and post-deposition heat treatment of the films at 300 °C for 1 h in air.

Hybrid light-emitting diodes based on ZnO nanowires

ZnO is a wide band-gap semiconductor that has several desirable properties for optoelectronic devices. With its large exciton binding energy of ~60 meV, ZnO is a promising candidate for high stability, room-temperature luminescent and lasing devices [1]. Ultraviolet light-emitting diodes (LEDs) based on ZnO homojunctions had been reported [2,3], while preparing stable p-type ZnO is still a challenge. An alternative way is to use other p-type semiconductors, ether inorganic or organic, to form heterojunctions with the naturally n-type ZnO. The crystal structure of wurtzite ZnO can be described as Zn and O atomic layers alternately stacked along the [0001] direction. Because of the fastest growth rate over the polar (0001) facet, ZnO crystals tend to grow into one-dimensional structures, such as nanowires and nanobelts. Since the first report of ZnO nanobelts in 2001 [4], ZnO nanostructures have been particularly studied for their potential applications in nano-sized devices. Various growth methods have been developed for growing ZnO nanostructures, such as chemical vapor deposition (CVD), Metal-organic CVD (MOCVD), aqueous growth and electrodeposition [5]. Based on the successful synthesis of ZnO nanowires/nanorods, various types of hybrid light-emitting diodes (LEDs) were made. Inorganic p-type semiconductors, such as GaN, Si and SiC, have been used as substrates to grown ZnO nanorods/nanowires for making LEDs. GaN is an ideal material that matches ZnO not only in the crystal structure but also in the energy band levels. However, to prepare Mg-doped p-GaN films via epitaxial growth is still costly. In comparison, the organic semiconductors are inexpensive and have many options to select, for a large variety of p-type polymer or small-molecule semiconductors are now commercially available. The organic semiconductor has the limitation of durability and environmental stability. Many polymer semiconductors are susceptible to damage by humidity or mere exposure to oxygen in the air. Also the carrier mobilities of polymer semiconductors are generally lower than the inorganic semiconductors. However, the combination of polymer semiconductors and ZnO nanostructures opens the way for making flexible LEDs. There are few reports on the hybrid LEDs based on ZnO/polymer heterojunctions, some of them showed the characteristic UV electroluminescence (EL) of ZnO. This chapter reports recent progress of the hybrid LEDs based on ZnO nanowires and other inorganic/organic semiconductors. We provide an overview of the ZnO-nanowire-based hybrid LEDs from the perspectives of the device configuration, growth methods of ZnO nanowires and the selection of p-type semiconductors. Also the device performances and remaining issues are presented.

Titanium-oxide magneli phases in four chondritic porous interplanetary dust particles

Detailed analytical electron microscope analyses of four fine-grained chondritic porous interplanetary dust particles (IDPs)reveal the presence of titanium oxide Magneli phases, TinO2n-1 (n=4,5,6), and rare Ti-metal. The titanium minerals are indigenous to these chondritic IDPs. The association of Magneli phases, Ti-metal, and carbonaceous material in chondritic IDPs, along with the grain size distributions support in situ solid carbon gasification in these extraterrestrial particles. The active catalyst in this process is titanium metal that we infer may be of interstellar origin. This favorable catalysis uniquely leads to the formation of Magneli phases. As chondritic IDPs may be solid debris of short-period comets, our data indicate that nuclei of short-period comets may show distinctive chemical reactions that lead to Ti-mineral assemblages that typically include Magneli phases. The proposed model provides a plausible mechnism to explain the higher solid carbon content of chondritic IDPs relative to bulk carbon abundances typical for carbonaceous chondrite matrices that represent another type of more evolved, that is, metamorphosed, undifferentiated solar system bodies.

Oxide reduction in NiO-containing solid solution systems during transmission electron microscopy

The effects of electron irradiation on NiO-containing solid solution systems are described. Partially hydrated NiO solid solutions, e. g. , NiO-MgO, undergo surface reduction to Ni metal after examination by TEM. This surface layer results in the formation of Moire interference patterns.

Multidisciplinary design and flight testing of a remote gas/particle airborne sensor system

The main objective of this paper is to describe the development of a remote sensing airborne air sampling system for Unmanned Aerial Systems (UAS) and provide the capability for the detection of particle and gas concentrations in real time over remote locations. The design of the air sampling methodology started by defining system architecture, and then by selecting and integrating each subsystem. A multifunctional air sampling instrument, with capability for simultaneous measurement of particle and gas concentrations was modified and integrated with ARCAA’s Flamingo UAS platform and communications protocols. As result of the integration process, a system capable of both real time geo-location monitoring and indexed-link sampling was obtained. Wind tunnel tests were conducted in order to evaluate the performance of the air sampling instrument in controlled nonstationary conditions at the typical operational velocities of the UAS platform. Once the remote fully operative air sampling system was obtained, the problem of mission design was analyzed through the simulation of different scenarios. Furthermore, flight tests of the complete air sampling system were then conducted to check the dynamic characteristics of the UAS with the air sampling system and to prove its capability to perform an air sampling mission following a specific flight path.

Hydrogen sensing properties of Pt/Lanthanum oxide- molybdenum oxide nanoplatelet/SiC based Schottky diode

An investigation of the electrical and hydrogen sensing properties of a novel Schottky diode based on a nanostructured lanthanum oxide-molybdenum oxide compound is presented herein. Molybdenum oxide (MoO3) nanoplatelets were grown on SiC substrates via thermal evaporation which was then subsequently coated with lanthanum oxide (La2O3) by RF sputtering. The current-voltage characteristics and hydrogen sensing performance (change in barrier height and sensitivity as well as the dynamic response) were examined from 25 to 300°C. At 180°C, a voltage shift of 2.23V was measured from the sensor while exposed to 1% hydrogen gas under a 100 μA constant reverse bias current. The results indicate that the presence of a La2O3 thin layer substantially improves the hydrogen sensitivity of the MoO3 nanoplatelets.

Pt/Graphene Nano-sheet Based Hydrogen Gas Sensor

In this paper, we present gas sensing properties of Pt/graphene-like nano-sheets towards hydrogen gas. The graphene-like nano-sheets were produced via the reduction of spray-coated graphite oxide deposited on SiC substrates by hydrazine vapor. Structural and morphological characterizations of the graphene sheets were analyzed by scanning electron and atomic force microscopy. Current-voltage and dynamic responses of the sensors were investigated towards different concentrations of hydrogen gas in a synthetic air mixture at 100°C. A voltage shift of 100 mV was recorded at 1 mA reverse bias current.

Image based visual servo control for fixed wing UAVs tracking linear infrastructure in wind

This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

Fabrication and characterisation of graphene oxide-epoxy nanocomposite

Adequate amount of graphene oxide (GO) was firstly prepared by oxidation of graphite and GO/epoxy nanocomposites were subsequently prepared by typical solution mixing technique. X-ray diffraction (XRD) pattern, X-ray photoelectron (XPS), Raman and Fourier transform infrared (FTIR) spectroscopy indicated the successful preparation of GO. Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM) images of the graphite oxide showed that they consist of a large amount of graphene oxide platelets with a curled morphology containing of a thin wrinkled sheet like structure. AFM image of the exfoliated GO signified that the average thickness of GO sheets is ~1.0 nm which is very similar to GO monolayer. Mechanical properties of as prepared GO/epoxy nanocomposites were investigated. Significant improvements in both Young’s modulus and tensile strength were observed for the nanocomposites at very low level of GO loading. The Young’s modulus of the nanocomposites containing 0.5 wt% GO was 1.72 GPa, which was 35 % higher than that of the pure epoxy resin (1.28 GPa). The effective reinforcement of the GO based epoxy nanocomposites can be attributed to the good dispersion and the strong interfacial interactions between the GO sheets and the epoxy resin matrices.

Fabrication and mechanical and thermal behaviour of graphene oxide/epoxy nanocomposites

Bulk amount of graphite oxide was prepared by oxidation of graphite using the modified Hummers method and its ultrasonication in organic solvents yielded graphene oxide (GO). X-ray diffraction (XRD) pattern, X-ray photoelectron (XPS), Raman and Fourier transform infrared (FTIR) spectroscopy indicated the successful preparation of GO. XPS survey spectrum of GO revealed the presence of 66.6 at% C and 30.4 at% O. Scanning electron microscopy (SEM) and Transmission electron microscopy (TEM) images of the graphene oxide showed that they consist of a large amount of graphene oxide platelets with a curled morphology containing of a thin wrinkled sheet like structure. AFM image of the exfoliated GO signified that the average thickness of GO sheets is ~1.0 nm which is very similar to GO monolayer. GO/epoxy nanocomposites were prepared by typical solution mixing technique and influence of GO on mechanical and thermal properties of nanocomposites were investigated. As for the mechanical behaviour of GO/epoxy nanocomposites, 0.5 wt% GO in the nanocomposite achieved the maximum increase in the elastic modulus (~35%) and tensile strength (~7%). The TEM analysis provided clear image of microstructure with homogeneous dispersion of GO in the polymer matrix. The improved strength properties of GO/epoxy nanocomposites can be attributed to inherent strength of GO, the good dispersion and the strong interfacial interactions between the GO sheets and the polymer matrix. However, incorporation of GO showed significant negative effect on composite glass transition temperature (Tg). This may arise due to the interference of GO on curing reaction of epoxy.