All-fibre twist sensor system based on 45° and 8° tilted fibre gratings

We experimentally demonstrated a highly sensitive twist sensor system based on a 45° and an 81° tilted fibre grating (TFG). The 81°-TFG has a set of dual-peaks that are due to the birefringence induced by its extremely tilted structure. When the 81°-TFG subjected to twist, the coupling to the two peaks would interchange from each other, providing a mechanism to measure and monitor the twist. We have investigated the performance of the sensor system by three interrogation methods (spectral, power-measurement and voltage-measurement). The experimental results clearly show that the 81°-TFG and the 45°-TFG could be combined forming a full fibre twist sensor system capable of not just measuring the magnitude but also recognising the direction of the applied twist.

Fibre laser torsion sensor system using an excessively tilted fibre grating and low-cost time domain demodulation

In this paper, we report a simple fibre laser torsion sensor system using an intracavity tilted fibre grating as a torsion encoded loss filter. When the grating is subjected to twist, it induces loss to the cavity, thus affecting the laser oscillation build-up time. By measuring the build-up time, both twist direction and angle on the grating can be monitored. Using a low-cost photodiode and a two-channel digital oscilloscope, we have characterised the torsion sensing capability of this fibre laser system and obtained a torsion sensitivity of ~412µs/(rad/m) in the dynamic range from -150° to +150°.

High performance liquid level monitoring system based on polymer fiber Bragg gratings embedded in silicone rubber diaphragm

Liquid-level sensing technologies have attracted great prominence, because such measurements are essential to industrial applications, such as fuel storage, flood warning and in the biochemical industry. Traditional liquid level sensors are based on electromechanical techniques; however they suffer from intrinsic safety concerns in explosive environments. In recent years, given that optical fiber sensors have lots of well-established advantages such as high accuracy, costeffectiveness, compact size, and ease of multiplexing, several optical fiber liquid level sensors have been investigated which are based on different operating principles such as side-polishing the cladding and a portion of core, using a spiral side-emitting optical fiber or using silica fiber gratings. The present work proposes a novel and highly sensitive liquid level sensor making use of polymer optical fiber Bragg gratings (POFBGs). The key elements of the system are a set of POFBGs embedded in silicone rubber diaphragms. This is a new development building on the idea of determining liquid level by measuring the pressure at the bottom of a liquid container, however it has a number of critical advantages. The system features several FBG-based pressure sensors as described above placed at different depths. Any sensor above the surface of the liquid will read the same ambient pressure. Sensors below the surface of the liquid will read pressures that increase linearly with depth. The position of the liquid surface can therefore be approximately identified as lying between the first sensor to read an above-ambient pressure and the next higher sensor. This level of precision would not in general be sufficient for most liquid level monitoring applications; however a much more precise determination of liquid level can be made by linear regression to the pressure readings from the sub-surface sensors. There are numerous advantages to this multi-sensor approach. First, the use of linear regression using multiple sensors is inherently more accurate than using a single pressure reading to estimate depth. Second, common mode temperature induced wavelength shifts in the individual sensors are automatically compensated. Thirdly, temperature induced changes in the sensor pressure sensitivity are also compensated. Fourthly, the approach provides the possibility to detect and compensate for malfunctioning sensors. Finally, the system is immune to changes in the density of the monitored fluid and even to changes in the effective force of gravity, as might be obtained in an aerospace application. The performance of an individual sensor was characterized and displays a sensitivity (54 pm/cm), enhanced by more than a factor of 2 when compared to a sensor head configuration based on a silica FBG published in the literature, resulting from the much lower elastic modulus of POF. Furthermore, the temperature/humidity behavior and measurement resolution were also studied in detail. The proposed configuration also displays a highly linear response, high resolution and good repeatability. The results suggest the new configuration can be a useful tool in many different applications, such as aircraft fuel monitoring, and biochemical and environmental sensing, where accuracy and stability are fundamental. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Fiber-optic liquid level monitoring system using microstructured polymer fiber Bragg grating array sensors:performance analysis

A highly sensitive liquid level monitoring system based on microstructured polymer optical fiber Bragg grating (mPOFBG) array sensors is reported for the first time. The configuration is based on five mPOFBGs inscribed in the same fiber in the 850 nm spectral region, showing the potential to interrogate liquid level by measuring the strain induced in each mPOFBG embedded in a silicone rubber (SR) diaphragm, which deforms due to hydrostatic pressure variations. The sensor exhibits a highly linear response over the sensing range, a good repeatability, and a high resolution. The sensitivity of the sensor is found to be 98 pm/cm of water, enhanced by more than a factor of 9 when compared to an equivalent sensor based on a silica fiber around 1550 nm. The temperature sensitivity is studied and a multi-sensor arrangement proposed, which has the potential to provide level readings independent of temperature and the liquid density.

Influence of digital dispersion equalization on phase noise enhancement in coherent optical system

The phase noise enhancement due to digital dispersion equalization is investigated, which indicates that the phase noise from transmitter laser can also interact with the dispersion depending on the choice of digital dispersion compensation methods. © OSA 2012.

The design and validation of an optical coherence tomography-based classification system for focal vitreomacular traction

PurposeTo develop and validate a classification system for focal vitreomacular traction (VMT) with and without macular hole based on spectral domain optical coherence tomography (SD-OCT), intended to aid in decision-making and prognostication.MethodsA panel of retinal specialists convened to develop this system. A literature review followed by discussion on a wide range of cases formed the basis for the proposed classification. Key features on OCT were identified and analysed for their utility in clinical practice. A final classification was devised based on two sequential, independent validation exercises to improve interobserver variability.ResultsThis classification tool pertains to idiopathic focal VMT assessed by a horizontal line scan using SD-OCT. The system uses width (W), interface features (I), foveal shape (S), retinal pigment epithelial changes (P), elevation of vitreous attachment (E), and inner and outer retinal changes (R) to give the acronym WISPERR. Each category is scored hierarchically. Results from the second independent validation exercise indicated a high level of agreement between graders: intraclass correlation ranged from 0.84 to 0.99 for continuous variables and Fleiss' kappa values ranged from 0.76 to 0.95 for categorical variables.ConclusionsWe present an OCT-based classification system for focal VMT that allows anatomical detail to be scrutinised and scored qualitatively and quantitatively using a simple, pragmatic algorithm, which may be of value in clinical practice as well as in future research studies.

Enhancing the Visualization of the Peripheral Retina with Wide Field-of-View Optical Coherence Tomography

The goal of my Ph.D. thesis is to enhance the visualization of the peripheral retina using wide-field optical coherence tomography (OCT) in a clinical setting.

OCT has gain widespread adoption in clinical ophthalmology due to its ability to visualize the diseases of the macula and central retina in three-dimensions, however, clinical OCT has a limited field-of-view of 300. There has been increasing interest to obtain high-resolution images outside of this narrow field-of-view, because three-dimensional imaging of the peripheral retina may prove to be important in the early detection of neurodegenerative diseases, such as Alzheimer's and dementia, and the monitoring of known ocular diseases, such as diabetic retinopathy, retinal vein occlusions, and choroid masses.

Before attempting to build a wide-field OCT system, we need to better understand the peripheral optics of the human eye. Shack-Hartmann wavefront sensors are commonly used tools for measuring the optical imperfections of the eye, but their acquisition speed is limited by their underlying camera hardware. The first aim of my thesis research is to create a fast method of ocular wavefront sensing such that we can measure the wavefront aberrations at numerous points across a wide visual field. In order to address aim one, we will develop a sparse Zernike reconstruction technique (SPARZER) that will enable Shack-Hartmann wavefront sensors to use as little as 1/10th of the data that would normally be required for an accurate wavefront reading. If less data needs to be acquired, then we can increase the speed at which wavefronts can be recorded.

For my second aim, we will create a sophisticated optical model that reproduces the measured aberrations of the human eye. If we know how the average eye's optics distort light, then we can engineer ophthalmic imaging systems that preemptively cancel inherent ocular aberrations. This invention will help the retinal imaging community to design systems that are capable of acquiring high resolution images across a wide visual field. The proposed model eye is also of interest to the field of vision science as it aids in the study of how anatomy affects visual performance in the peripheral retina.

Using the optical model from aim two, we will design and reduce to practice a clinical OCT system that is capable of imaging a large (800) field-of-view with enhanced visualization of the peripheral retina. A key aspect of this third and final aim is to make the imaging system compatible with standard clinical practices. To this end, we will incorporate sensorless adaptive optics in order to correct the inter- and intra- patient variability in ophthalmic aberrations. Sensorless adaptive optics will improve both the brightness (signal) and clarity (resolution) of features in the peripheral retina without affecting the size of the imaging system.

The proposed work should not only be a noteworthy contribution to the ophthalmic and engineering communities, but it should strengthen our existing collaborations with the Duke Eye Center by advancing their capability to diagnose pathologies of the peripheral retinal.

Nonlinear optics with cold Rb atoms using tapered optical nanofibres

Optical nanofibres (ONFs) are very thin optical waveguides with sub-wavelength diameters. ONFs have very high evanescent fields and the guided light is confined strongly in the transverse direction. These fibres can be used to achieve strong light-matter interactions. Atoms around the waist of an ONF can be probed by collecting the atomic fluorescence coupling or by measuring the transmission (or the polarisation) of the probe beam sent through it. This thesis presents experiments using ONFs for probing and manipulating laser-cooled 87Rb atoms. As an initial experiment, a single mode ONF was integrated into a magneto-optical trap (MOT) and used for measuring the characteristics of the MOT, such as the loading time and the average temperature of the atom cloud. The effect of a near-resonant probe beam on the local temperature of the cold atoms has been studied. Next, the ONF was used for manipulating the atoms in the evanescent fields region in order to generate nonlinear optical effects. Four-wave mixing, ac Stark effect (Autler-Townes splitting) and electromagnetically induced transparency have been observed at unprecedented ultralow power levels. In another experiment, a few-mode ONF, supporting only the fundamental mode and the first higher order mode group, has been used for studying cold atoms. A higher pumping rate of the atomic fluorescence into the higher order fibreguided modes and more interactions with the surrounding atoms for higher order mode evanescent light, when compared to signals for the fundamental mode, have been identified. The results obtained in the thesis are particularly for a fundamental understanding of light-atom interactions when atoms are near a dielectric surface and also for the development of fibre-based quantum information technologies. Atoms coupled to ONFs could be used for preparing intrinsically fibre-coupled quantum nodes for quantum computing and the studies presented here are significant for a detailed understanding of such a system.

A cloud-based system for measuring radiation treatment plan similarity

PURPOSE: Radiation therapy is used to treat cancer using carefully designed plans that maximize the radiation dose delivered to the target and minimize damage to healthy tissue, with the dose administered over multiple occasions. Creating treatment plans is a laborious process and presents an obstacle to more frequent replanning, which remains an unsolved problem. However, in between new plans being created, the patient's anatomy can change due to multiple factors including reduction in tumor size and loss of weight, which results in poorer patient outcomes. Cloud computing is a newer technology that is slowly being used for medical applications with promising results. The objective of this work was to design and build a system that could analyze a database of previously created treatment plans, which are stored with their associated anatomical information in studies, to find the one with the most similar anatomy to a new patient. The analyses would be performed in parallel on the cloud to decrease the computation time of finding this plan. METHODS: The system used SlicerRT, a radiation therapy toolkit for the open-source platform 3D Slicer, for its tools to perform the similarity analysis algorithm. Amazon Web Services was used for the cloud instances on which the analyses were performed, as well as for storage of the radiation therapy studies and messaging between the instances and a master local computer. A module was built in SlicerRT to provide the user with an interface to direct the system on the cloud, as well as to perform other related tasks. RESULTS: The cloud-based system out-performed previous methods of conducting the similarity analyses in terms of time, as it analyzed 100 studies in approximately 13 minutes, and produced the same similarity values as those methods. It also scaled up to larger numbers of studies to analyze in the database with a small increase in computation time of just over 2 minutes. CONCLUSION: This system successfully analyzes a large database of radiation therapy studies and finds the one that is most similar to a new patient, which represents a potential step forward in achieving feasible adaptive radiation therapy replanning.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Scanning Laser Optical Tomography Resolves Structural Plasticity during Regeneration in an Insect Brain

Background: Optical Projection Tomography (OPT) is a microscopic technique that generates three dimensional images from whole mount samples the size of which exceeds the maximum focal depth of confocal laser scanning microscopes. As an advancement of conventional emission-OPT, Scanning Laser Optical Tomography (SLOTy) allows simultaneous detection of fluorescence and absorbance with high sensitivity. In the present study, we employ SLOTy in a paradigm of brain plasticity in an insect model system. Methodology: We visualize and quantify volumetric changes in sensory information procession centers in the adult locust, Locusta migratoria. Olfactory receptor neurons, which project from the antenna into the brain, are axotomized by crushing the antennal nerve or ablating the entire antenna. We follow the resulting degeneration and regeneration in the olfactory centers (antennal lobes and mushroom bodies) by measuring their size in reconstructed SLOTy images with respect to the untreated control side. Within three weeks post treatment antennal lobes with ablated antennae lose as much as 60% of their initial volume. In contrast, antennal lobes with crushed antennal nerves initially shrink as well, but regain size back to normal within three weeks. The combined application of transmission-and fluorescence projections of Neurobiotin labeled axotomized fibers confirms that recovery of normal size is restored by regenerated afferents. Remarkably, SLOTy images reveal that degeneration of olfactory receptor axons has a trans-synaptic effect on second order brain centers and leads to size reduction of the mushroom body calyx. Conclusions: This study demonstrates that SLOTy is a suitable method for rapid screening of volumetric plasticity in insect brains and suggests its application also to vertebrate preparations.

Near-infraread observation of supernovae with the Nordic Optical Telescope (NOT)

Supernova (SN) is an explosion of a star at the end of its lifetime. SNe are classified to two types, namely type I and II through the optical spectra. They have been categorised based on their explosion mechanism, to core collapse supernovae (CCSNe) and thermonuclear supernovae. The CCSNe group which includes types IIP, IIn, IIL, IIb, Ib, and Ic are produced when a massive star with initial mass more than 8 M⊙ explodes due to a collapse of its iron core. On the other hand, thermonuclear SNe originate from white dwarfs (WDs) made of carbon and oxygen, in a binary system. Infrared astronomy covers observations of astronomical objects in infrared radiation. The infrared sky is not completely dark and it is variable. Observations of SNe in the infrared give different information than optical observations. Data reduction is required to correct raw data from for example unusable pixels and sky background. In this project, the NOTCam package in the IRAF was used for the data reduction. For measuring magnitudes of SNe, the aperture photometry method with the Gaia program was used. In this Master’s thesis, near-infrared (NIR) observations of three supernovae of type IIn (namely LSQ13zm, SN 2009ip and SN2011jb), one type IIb (SN2012ey), in addition to one type Ic (SN2012ej) and type IIP (SN 2013gd) are studied with emphasis on luminosity and colour evolution. All observations were done with the Nordic Optical Telescope (NOT). Here, we used the classification by Mattila & Meikle (2001) [76], where the SNe are differentiated by the infrared light curves into two groups, namely ’ordinary’ and ’slowly declining’. The light curves and colour evolution of these supernovae were obtained in J, H and Ks bands. In this study, our data, combined with other observations, provide evidence to categorize LSQ13zm, SN 2012ej and SN 2012ey as being part of the ordinary type. We found interesting NIR behaviour of SN 2011jb, which lead it to be classified as a slowly declining type.

Non-contact test set-up for aeroelasticity in a rotating turbomachine combining a novel acoustic excitation system with tip-timing

Due to trends in aero-design, aeroelasticity becomes increasingly important in modern turbomachines. Design requirements of turbomachines lead to the development of high aspect ratio blades and blade integral disc designs (blisks), which are especially prone to complex modes of vibration. Therefore, experimental investigations yielding high quality data are required for improving the understanding of aeroelastic effects in turbomachines. One possibility to achieve high quality data is to excite and measure blade vibrations in turbomachines. The major requirement for blade excitation and blade vibration measurements is to minimize interference with the aeroelastic effects to be investigated. Thus in this paper, a non-contact-and thus low interference-experimental set-up for exciting and measuring blade vibrations is proposed and shown to work. A novel acoustic system excites rotor blade vibrations, which are measured with an optical tip-timing system. By performing measurements in an axial compressor, the potential of the acoustic excitation method for investigating aeroelastic effects is explored. The basic principle of this method is described and proven through the analysis of blade responses at different acoustic excitation frequencies and at different rotational speeds. To verify the accuracy of the tip-timing system, amplitudes measured by tip-timing are compared with strain gage measurements. They are found to agree well. Two approaches to vary the nodal diameter (ND) of the excited vibration mode by controlling the acoustic excitation are presented. By combining the different excitable acoustic modes with a phase-lag control, each ND of the investigated 30 blade rotor can be excited individually. This feature of the present acoustic excitation system is of great benefit to aeroelastic investigations and represents one of the main advantages over other excitation methods proposed in the past. In future studies, the acoustic excitation method will be used to investigate aeroelastic effects in high-speed turbomachines in detail. The results of these investigations are to be used to improve the aeroelastic design of modern turbomachines.