Fibre optic sensors for high speed hypervelocity impact studies and low velocity drop tests

The initial aim of this project was to develop a non-contact fibre optic based displacement sensor to operate in the harsh environment of a 'Light Gas Gun' (LGG), which can 'fire' small particles at velocities ranging from 1-8.4 km/s. The LGG is used extensively for research in aerospace to analyze the effects of high speed impacts on materials. Ideally the measurement should be made close to the centre of the impact to minimise corruption of the data from edge effects and survive the impact. A further requirement is that it should operate at a stand-off distance of ~ 8cm. For these reasons we chose to develop a pseudo con-focal intensity sensor, which demonstrated resolution comparable with conventional PVDF sensors combined with high survivability and low cost. A second sensor was developed based on 'Fibre Bragg Gratings' (FBG) which although requiring contact with the target the low weight and very small contact area had minimal effect on the dynamics of the target. The FBG was mounted either on the surface of the target or tangentially between a fixed location. The output signals from the FBG were interrogated in time by a new method. Measurements were made on composite and aluminium plates in the LGG and on low speed drop tests. The particle momentum for the drop tests was chosen to be similar to that of the particles used in the LGG.

Credibility theory-based available transfer capability assessment

Since the development of large scale power grid interconnections and power markets, research on available transfer capability (ATC) has attracted great attention. The challenges for accurate assessment of ATC originate from the numerous uncertainties in electricity generation, transmission, distribution and utilization sectors. Power system uncertainties can be mainly described as two types: randomness and fuzziness. However, the traditional transmission reliability margin (TRM) approach only considers randomness. Based on credibility theory, this paper firstly built models of generators, transmission lines and loads according to their features of both randomness and fuzziness. Then a random fuzzy simulation is applied, along with a novel method proposed for ATC assessment, in which both randomness and fuzziness are considered. The bootstrap method and multi-core parallel computing technique are introduced to enhance the processing speed. By implementing simulation for the IEEE-30-bus system and a real-life system located in Northwest China, the viability of the models and the proposed method is verified.

Cost-effective optical coherence tomography spectrometer based on a tilted fiber Bragg grating

A compact, fiber-based spectrometer for biomedical application utilizing a tilted fiber Bragg grating (TFBG) as integrated dispersive element is demonstrated. Based on a 45° UV-written PS750 TFBG a refractive spectrometer with 2.06 radiant/μm dispersion and a numerical aperture of 0.1 was set up and tested as integrated detector for an optical coherence tomography (OCT) system. Featuring a 23 mm long active region at the fiber the spectrum is projected via a cylindrical lens for vertical beam collimation and focused by an achromatic doublet onto the detector array. Covering 740 nm to 860 nm the spectrometer was optically connected to a broadband white light interferometer and a wide field scan head and electronically to an acquisition and control computer. Tomograms of ophthalmic and dermal samples obtained by the frequency domain OCT-system were obtained achieving 2.84 μm axial and 7.6 μm lateral resolution. © 2014 SPIE.

InP-based active and passive components for communication systems at 2 μm

Progress on advanced active and passive photonic components that are required for high-speed optical communications over hollow-core photonic bandgap fiber at wavelengths around 2 μm is described in this paper. Single-frequency lasers capable of operating at 10 Gb/s and covering a wide spectral range are realized. A comparison is made between waveguide and surface normal photodiodes with the latter showing good sensitivity up to 15 Gb/s. Passive waveguides, 90° optical hybrids, and arrayed waveguide grating with 100-GHz channel spacing are demonstrated on a large spot-size waveguide platform. Finally, a strong electro-optic effect using the quantum confined Stark effect in strain-balanced multiple quantum wells is demonstrated and used in a Mach-Zehnder modulator capable of operating at 10 Gb/s.

A laser induced breakdown spectroscopy quantitative analysis method based on the robust least squares support vector machine regression model

Data fluctuation in multiple measurements of Laser Induced Breakdown Spectroscopy (LIBS) greatly affects the accuracy of quantitative analysis. A new LIBS quantitative analysis method based on the Robust Least Squares Support Vector Machine (RLS-SVM) regression model is proposed. The usual way to enhance the analysis accuracy is to improve the quality and consistency of the emission signal, such as by averaging the spectral signals or spectrum standardization over a number of laser shots. The proposed method focuses more on how to enhance the robustness of the quantitative analysis regression model. The proposed RLS-SVM regression model originates from the Weighted Least Squares Support Vector Machine (WLS-SVM) but has an improved segmented weighting function and residual error calculation according to the statistical distribution of measured spectral data. Through the improved segmented weighting function, the information on the spectral data in the normal distribution will be retained in the regression model while the information on the outliers will be restrained or removed. Copper elemental concentration analysis experiments of 16 certified standard brass samples were carried out. The average value of relative standard deviation obtained from the RLS-SVM model was 3.06% and the root mean square error was 1.537%. The experimental results showed that the proposed method achieved better prediction accuracy and better modeling robustness compared with the quantitative analysis methods based on Partial Least Squares (PLS) regression, standard Support Vector Machine (SVM) and WLS-SVM. It was also demonstrated that the improved weighting function had better comprehensive performance in model robustness and convergence speed, compared with the four known weighting functions.

Polymer optical fibre sensors for endoscopic optoacoustic imaging

Opto-acoustic imaging (OAI) shows particular promise for in-vivo biomedical diagnostics. Its applications include cardiovascular, gastrointestinal and urogenital systems imaging. Opto-acoustic endoscopy (OAE) allows the imaging of body parts through cavities permitting entry. The critical parameter is the physical size of the device, allowing compatibility with current technology, while governing flexibility of the distal end of the endoscope based on the needs of the sensor. Polymer optical fibre (POF) presents a novel approach for endoscopic applications and has been positively discussed and compared in existing publications. A great advantage can be obtained for endoscopy due to a small size and array potential to provide discrete imaging speed improvements. Optical fibre exhibits numerous advantages over conventional piezo-electric transducers, such as immunity from electromagnetic interference and a higher resolution at small sizes. Furthermore, micro structured polymer optical fibres offer over 12 times the sensitivity of silica fibre. We present a polymer fibre Bragg grating ultrasound detector with a core diameter of 125 microns. We discuss the ultrasonic signals received and draw conclusions on the opportunities and challenges of applying this technology in biomedical applications.

Comprehensive secondary pyrolysis in fluidized-bed fast pyrolysis of biomass, a fluid dynamics based modelling effort

Homogenous secondary pyrolysis is category of reactions following the primary pyrolysis and presumed important for fast pyrolysis. For the comprehensive chemistry and fluid dynamics, a probability density functional (PDF) approach is used; with a kinetic scheme comprising 134 species and 4169 reactions being implemented. With aid of acceleration techniques, most importantly Dimension Reduction, Chemistry Agglomeration and In-situ Tabulation (ISAT), a solution within reasonable time was obtained. More work is required; however, a solution for levoglucosan (C6H10O5) being fed through the inlet with fluidizing gas at 500 °C, has been obtained. 88.6% of the levoglucosan remained non-decomposed, and 19 different decomposition product species were found above 0.01% by weight. A homogenous secondary pyrolysis scheme proposed can thus be implemented in a CFD environment and acceleration techniques can speed-up the calculation for application in engineering settings.

Computational model of bladder tissue based on its measured optical properties

Urinary bladder diseases are a common problem throughout the world and often difficult to accurately diagnose. Furthermore, they pose a heavy financial burden on health services. Urinary bladder tissue from male pigs was spectrophotometrically measured and the resulting data used to calculate the absorption, transmission, and reflectance parameters, along with the derived coefficients of scattering and absorption. These were employed to create a "generic" computational bladder model based on optical properties, simulating the propagation of photons through the tissue at different wavelengths. Using the Monte-Carlo method and fluorescence spectra of UV and blue excited wavelength, diagnostically important biomarkers were modeled. Additionally, the multifunctional noninvasive diagnostics system "LAKK-M" was used to gather fluorescence data to further provide essential comparisons. The ultimate goal of the study was to successfully simulate the effects of varying excited radiation wavelengths on bladder tissue to determine the effectiveness of photonics diagnostic devices. With increased accuracy, this model could be used to reliably aid in differentiating healthy and pathological tissues within the bladder and potentially other hollow organs.

Two-section fiber optic Raman polarizer for high-speed transmission systems

We report on a theoretical study of polarization impairments in periodically spun fiber Raman amplifiers. Based on the Stochastic Generator approach we have derived equations for polarization dependent gain and mean-square gain fluctuations. We show that periodically spun fiber can work as a Raman polarizer but it suffers from increased polarization dependent gain and gain fluctuations. Unlike this, application of a depolarizer can result in suppression of polarization dependent gain and gain fluctuations. We demonstrate that it is possible to design a new fiber Raman polarizer by combining a short fiber without spin and properly chosen parameters and a long periodically spun fiber. This polarizer provides almost the same polarization pulling for all input signal states of polarization and so have very small polarization dependent gain. The obtained results can be used in high-speed fiber optic communication for design of quasi-isotropic spatially and spectrally transparent media with increased Raman gain. © 2011 IEEE.

A new sensorless speed control scheme for doubly-fed reluctance generators

This paper presents the development and experimental validation of a novel angular velocity observer-based field-oriented control algorithm for a promising low-cost brushless doubly fed reluctance generator (BDFRG) in wind power applications. The BDFRG has been receiving increasing attention because of the use of partially rated power electronics, the high reliability of brushless design, and competitive performance to its popular slip-ring counterpart, the doubly fed induction generator. The controller viability has been demonstrated on a BDFRG laboratory test facility for emulation of variable speed and loading conditions of wind turbines or pump drives.

Electromagnetic design and loss calculations of a 1.12-MW high-speed permanent-magnet motor for compressor applications

Electromagnetic design of a 1.12-MW, 18 000-r/min high-speed permanent-magnet motor (HSPMM) is carried out based on the analysis of pole number, stator slot number, rotor outer diameter, air-gap length, permanent magnet material, thickness, and pole arc. The no-load and full-load performance of the HSPMM is investigated in this paper by using 2-D finite element method (FEM). In addition, the power losses in the HSPMM including core loss, winding loss, rotor eddy current loss, and air friction loss are predicted. Based on the analysis, a prototype motor is manufactured and experimentally tested to verify the machine design.

Web-based report generators, data visualization, and Web-to-database connectivity

Because some Web users will be able to design a template to visualize information from scratch, while other users need to automatically visualize information by changing some parameters, providing different levels of customization of the information is a desirable goal. Our system allows the automatic generation of visualizations given the semantics of the data, and the static or pre-specified visualization by creating an interface language. We address information visualization taking into consideration the Web, where the presentation of the retrieved information is a challenge. ^ We provide a model to narrow the gap between the user's way of expressing queries and database manipulation languages (SQL) without changing the system itself thus improving the query specification process. We develop a Web interface model that is integrated with the HTML language to create a powerful language that facilitates the construction of Web-based database reports. ^ As opposed to other papers, this model offers a new way of exploring databases focusing on providing Web connectivity to databases with minimal or no result buffering, formatting, or extra programming. We describe how to easily connect the database to the Web. In addition, we offer an enhanced way on viewing and exploring the contents of a database, allowing users to customize their views depending on the contents and the structure of the data. Current database front-ends typically attempt to display the database objects in a flat view making it difficult for users to grasp the contents and the structure of their result. Our model narrows the gap between databases and the Web. ^ The overall objective of this research is to construct a model that accesses different databases easily across the net and generates SQL, forms, and reports across all platforms without requiring the developer to code a complex application. This increases the speed of development. In addition, using only the Web browsers, the end-user can retrieve data from databases remotely to make necessary modifications and manipulations of data using the Web formatted forms and reports, independent of the platform, without having to open different applications, or learn to use anything but their Web browser. We introduce a strategic method to generate and construct SQL queries, enabling inexperienced users that are not well exposed to the SQL world to build syntactically and semantically a valid SQL query and to understand the retrieved data. The generated SQL query will be validated against the database schema to ensure harmless and efficient SQL execution. (Abstract shortened by UMI.)^

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

A thermally wavelength-tunable photonic switch based on silicon microring resonator

Silicon photonics is a very promising technology for future low-cost high-bandwidth optical telecommunication applications down to the chip level. This is due to the high degree of integration, high optical bandwidth and large speed coupled with the development of a wide range of integrated optical functions. Silicon-based microring resonators are a key building block that can be used to realize many optical functions such as switching, multiplexing, demultiplaxing and detection of optical wave. The ability to tune the resonances of the microring resonators is highly desirable in many of their applications. In this work, the study and application of a thermally wavelength-tunable photonic switch based on silicon microring resonator is presented. Devices with 10μm diameter were systematically studied and used in the design. Its resonance wavelength was tuned by thermally induced refractive index change using a designed local micro-heater. While thermo-optic tuning has moderate speed compared with electro-optic and all-optic tuning, with silicon’s high thermo-optic coefficient, a much wider wavelength tunable range can be realized. The device design was verified and optimized by optical and thermal simulations. The fabrication and characterization of the device was also implemented. The microring resonator has a measured FSR of ∼18 nm, FWHM in the range 0.1-0.2 nm and Q around 10,000. A wide tunable range (>6.4 nm) was achieved with the switch, which enables dense wavelength division multiplexing (DWDM) with a channel space of 0.2nm. The time response of the switch was tested on the order of 10 μs with a low power consumption of ∼11.9mW/nm. The measured results are in agreement with the simulations. Important applications using the tunable photonic switch were demonstrated in this work. 1×4 and 4×4 reconfigurable photonic switch were implemented by using multiple switches with a common bus waveguide. The results suggest the feasibility of on-chip DWDM for the development of large-scale integrated photonics. Using the tunable switch for output wavelength control, a fiber laser was demonstrated with Erbium-doped fiber amplifier as the gain media. For the first time, this approach integrated on-chip silicon photonic wavelength control.

Parameter optimization for noise and vibration reduction associated with position and speed sensorless control of permanent magnet machines at low speed

With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^