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Backup bearings (BBs) are used to protect active magnetic bearings in the event of rotor delevitation. To gain insight into the design, selection and operation of BBs, a model that can accurately simulate the behaviour of a rotor and BB system during a rotor delevitation event is required. This paper presents a model that can accurately simulate rotor delevitation and predict the occurrence of forward and backward whirl. The model, called BBSim, is based on the integration of a number of simpler models for each of the important mechanisms that govern the behaviour of a BB system. Estimation of parameters that are critical in determining the rotor’s behaviour inside the BB clearance is achieved using empirical methods. Rotor orbit plots confirm the model’s capability of simulating the characteristic motions of rotor delevitation.

The dynamic reconfiguration of an FPGA has many advantages, but the overhead from the process reduces the functional density of applications. Functional density is an indication of the composite benefits a reconfigured application obtains above its generic counterpart and measures the computational throughput per unit hardware resources. Typically, only quasi-static applications obtain a functional density advantage by dynamically reconfiguring its parameters. Contributing to the functional density reduction of applications with tight time constraints is the overhead to generate a new configuration, and the time it takes to load it onto the device. Normally these applications have to reuse their hardware numerous times between configurations before obtaining a functional density advantage. The most promising reconfiguration method to improve functional density with minimal hardware reuse was one that extracts certain characteristics from the bitstream and then implements a bitstream specialiser that generates new hardware at bit-level while the device is being reconfigured. While it was shown that this method allows reconfiguration of an application in real-time, its effect on functional density was not determined. This paper will show that a significant increase in functional density can be achieved for applications where reconfiguration is required before the next execution cycle of the application.CATEGORIES: · Hardware ~ Reconfigurable logic and FPGAs · Computer systems organization ~ Other architectures

Despite the many advantages run-time reconfiguration of FPGAs brings to the table, its usage is mostly limited to quasi-static applications. This is either due to the throughput of the reconfiguration process, or the time required to create new hardware. In order to optimise the former, the literature proposes a block RAM (BRAM)-based architecture in which a new configuration is stored in localised memory and reconfiguration is facilitated by a controller implemented in the FPGA fabric. The limitation of this architecture is that only a subset of configurations can be stored. When new hardware is required, the slow synthesis process (or a part thereof) has to be repeated for each new configuration. Various third-party tools aim to mitigate this overhead, but since the bitstream is shrouded in obscurity, all rely on a layer of abstraction that make them unusable in real-time. To address this issue, this paper presents a novel method to parse and analyse a Xilinx® FPGA bitstream to extract certain characteristics. It is shown how these characteristics could be used to design and implement a bitstream specialiser, capable of taking a bitstream and modifying the configuration bits of lookup tables in real-time. CATEGORIES: · Hardware ~ Reconfigurable logic and FPGAs · Computer systems organization ~ Other architectures

A number of gearbox failures can be attributed to lubricant related problems. One measure of the condition of gearbox oil is its viscosity. In electrically powered systems, motor current signal analysis allows online estimation of the viscosity of gearbox oil without requiring additional sensors. Previous work on this problem entailed monitoring the power (and change in power) of sidebands of the shaft frequency in the induction motor current spectrum. Sideband frequencies in the current spectrum can however be influenced by other potential problems in the electromechanical system ranging from bearing faults to gearbox teeth damage.\ud \ud \ud Changes in the lubricant viscosity result in changes in the mechanical and thermal losses in the system. These small deviations in the mechanical and thermal losses in the system become visible in the ratio of the electrical energy demanded by the induction motor to the kinetic energy of the rotating mechanical parts. Speed and load invariance can be ensured by normalizing the measured energy ratio with lookup table values obtained when the system attained thermal equilibrium. Speed or load perturbations in the system give rise to small deviations in the normalized energy ratio curve. The distributions of these deviations are significantly different (in a statistical sense) for different oil viscosity values.

Kabelo, I'm not sure if this journal is open access??? The presence of landmines poses a worldwide humanitarian problem. Often, these mines are difficult to detect with metal detectors. Ground penetrating radar (GPR) is a promising technology for the detection of landmines with low metal content. Automatic landmine detection typically consists of two steps, namely preprocessing (or clutter removal) and classification. In this paper the clutter removal algorithm consists of a nonlinear frequency domain filter followed by principal component based filtering. Principal component analysis is performed in the frequency domain to build a background model for the clutter. The latter model is removed from the observed data in the log-frequency domain in order to preserve the phase component of the spectrum. Finally, the data is normalized and transformed to the time domain. The results presented in this paper show a marked improvement in the ability to remove general background clutter. Classification is performed on the basis of the prediction performance of neural network time-series models of the various classes of GPR responses. The classification system can correctly identify the position of metal anti-tank (AT) mines. It can also recognize specific examples of low metal AT and (anti-personnel) AP mines, but does have a low generalization ability for such mines http://www.saiee.org.za/displaycustomlink.aspx?name=AfricaResearchJournal

Coal ore isn't a uniform material. In order to optimize the coal liberation process it is necessary to classify a coal ore sample into its constituent components as quickly and cheaply possible. This paper investigates whether it is feasible to employ image processing and pattern recognition to segment a photographic image of coal ore into its various mineral components prior to the sample being crushed. The key to solving this classification problem is to model the visual texture of the various coal components by means of a low-dimensional texture space consisting of two main dimensions, namely: roughness and regularity. The regularity of each texture is estimated by means of a novel model-based approach. The distribution of the various coal components in the resultant feature space is modelled by means of a mixtures model and a simple nearest-neighbour decision rule is used to classify each pixel in the image. The performance of the classification system is encouraging and shows the feasibility of our idea.

A fair amount of research has been done on the modeling of the oculomotor system. Models of the oculomotor neural circuitry that include the effect of alcohol are less plentiful in literature. We investigated the correlation between blood-alcohol levels and the response characteristics of the optical-oculomotor system. Video recordings of eye movements were regarded as the main sensor, with a breathalyzer for verification. System identification was done based on the transfer function of a proposed delay-based model. The correlation of coefficients of the model to increasing blood-alcohol concentration was seen to display behavior that was unique to each test.

Despite the numerous advantages reconfigurable computing adds to a system, it is only advantageous if the execution time exceeds the configuration time. As a result of the long configuration time, reconfiguration is only suitable for quasi-static applications. Due to the additional overhead required for communication, the bus-based architectures most commonly used to connect the configuration controller to the memory contribute to the configuration time. A method proposed to ameliorate this overhead is an architecture utilizing localized block RAM (BRAM), directly connected to the configuration controller to store the configuration data. The drawback of this method is that the BRAM is extremely limited and only a discrete set of configurations can be stored. This paper is a work in progress and proposes a hardware reconfiguration architecture that addresses the size limitation of the localized BRAM-architecture by using parameterizable configuration. This will allow a single bitstream stored in the BRAM to be specialized according to certain parameters, which will be used to reconfigure the device. This will migrate reconfigurable computing to more dynamic applications. The architecture proposed in this paper will be validated using real-time PID control of a five degree of freedom active magnetic bearing system.

A state-space model with uncertainties for an active magnetic bearing energy storage flywheel system (Fly-UPS) is developed. A multivariable robust H∞ controller for the Fly-UPS is then synthesised. Different weighting schemes are explained and used for H∞ controller synthesis. Furthermore, the additive uncertainties between the nominal simulation model and the physical model at varied rotational speeds are characterised. Stability robustness for additive uncertainties is verified via the gain/phase margin stability robustness criterion. The performance robustness (disturbance attenuation) is analysed by assessing model sensitivity with the ISO/CD 14839-3 sensitivity standard.