Sensorless commutation of a two-phase linear machine for marine renewable power generation

A sensorless scheme is presented for a two-phase permanent-magnet linear machine targeted for use in marine wave-power generation. This is a field where system reliability is a key concern. The scheme is able to extract the effective inductance and back-emf of the machine's phases simultaneously from measurements of the current ripple present on the power electronic converter. These measurements can then be used to estimate position. An enhancement to the scheme in the presence of spatially-varying mutual inductance between phases allows more accurate and reliable tracking from indutance-based measurements than would otherwise be expected. This scheme is able to operate at any speed including, critically, when stationary. Experimental results show promise for the scheme, although some work to reduce the level of noise would be desirable. © 2013 IEEE.

Dynamic modelling of the brushless doubly fed machine

A coupled-circuit model for the brushless doubly fed machine (BDFM) has been developed. The transformation of the model into the d-q axis form, ultimately in a synchronous reference frame in which machine currents and voltages have constant values in the steady state, has been carried out. A model-reduction technique is presented, which gives a concise representation of the 'nested-loop' rotor design using a single d-q pair. These models have been experimentally verified and give a convenient and accurate way of calculating the dynamic behaviour of a BDFM. The ability to represent the BDFM with a single d-q pair considerably simplifies the design of suitable controllers. © The Institution of Engineering and Technology 2013.

Design and market considerations for axial flux superconducting electric machine design

In this paper, the authors investigate a number of design and market considerations for an axial flux superconducting electric machine design that uses high temperature superconductors. The axial flux machine design is assumed to utilise high temperature superconductors in both wire (stator winding) and bulk (rotor field) forms, to operate over a temperature range of 65-77 K, and to have a power output in the range from 10s of kW up to 1 MW (typical for axial flux machines), with approximately 2-3 T as the peak trapped field in the bulk superconductors. The authors firstly investigate the applicability of this type of machine as a generator in small- and medium-sized wind turbines, including the current and forecasted market and pricing for conventional turbines. Next, a study is also carried out on the machine's applicability as an in-wheel hub motor for electric vehicles. Some recommendations for future applications are made based on the outcome of these two studies. Finally, the cost of YBCO-based superconducting (2G HTS) wire is analysed with respect to competing wire technologies and compared with current conventional material costs and current wire costs for both 1G and 2G HTS are still too great to be economically feasible for such superconducting devices.

Finite element analysis of the ring rolling process with integrated closed-loop control

In FEA of ring rolling processes the tools' motions usually are defined prior to simulation. This procedure neglects the closed-loop control, which is used in industrial processes to control up to eight degrees of freedom (rotations, feed rates, guide rolls) in real time, taking into account the machine's performance limits as well as the process evolution. In order to close this gap in the new simulation approach all motions of the tools are controlled according to sensor values which are calculated within the FE simulation. This procedure leads to more realistic simulation results in comparison to the machine behaviour. © 2012 CIRP.

High-performance bowing machine tests of bowed-string transients

The development is described of a computer-controlled bowing machine that can bow a string with a range of gestures that match or exceed the capabilities of a human violinist. Example measurements of string vibration under controlled bowing conditions are shown, including a Schelleng diagram and a set of Guettler diagrams, for the open D string of a cello. For some results a rosin-coated rod was used in place of a conventional bow, to provide quantitative data for comparison with theoretical predictions. The results show qualitative consistency with the predictions of Schelleng and Guettler, but details are revealed that go beyond the limitations of existing models. © S. Hirzel Verlag · EAA.

Decoupling method for vector control of the brushless doubly-fed machine

The brushless doubly-fed machine exhibits rotor-speed-dependent, cross-coupling effects between inputs and outputs when vector control is implemented. Manipulation of the model equations shows that these effects are represented by rotation angles. A parameter-independent decoupling method is presented which reduces these cross-coupling disturbances by estimating the rotation angle and applying it back to the controller. © 2013 IEEE.

Reference frame re-alignment for vector control of the brushless doubly-fed machine

Vector control provides stability and performance when applied to the brushless doubly-fed machine, however cross-coupling effects can arise between inputs and outputs. To address these effects, a procedure is proposed to both visualize and minimize the cross-coupling by means of steady-state mapping and a re-alignment of the dq reference frame. With this method implemented, gain-response tests show improved decoupling across the operating region. © 2013 EUCA.

Randomized nonlinear component analysis

Copyright © (2014) by the International Machine Learning Society (IMLS) All rights reserved. Classical methods such as Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA) are ubiquitous in statistics. However, these techniques are only able to reveal linear re-lationships in data. Although nonlinear variants of PCA and CCA have been proposed, these are computationally prohibitive in the large scale. In a separate strand of recent research, randomized methods have been proposed to construct features that help reveal nonlinear patterns in data. For basic tasks such as regression or classification, random features exhibit little or no loss in performance, while achieving drastic savings in computational requirements. In this paper we leverage randomness to design scalable new variants of nonlinear PCA and CCA; our ideas extend to key multivariate analysis tools such as spectral clustering or LDA. We demonstrate our algorithms through experiments on real- world data, on which we compare against the state-of-the-art. A simple R implementation of the presented algorithms is provided.

Noise and vibration in brushless doubly fed machine and brushless doubly fed reluctance machine

This study investigates modes of vibration in brushless doubly fed machine and brushless doubly fed reluctance machine due to the interaction of its fundamental magnetic fields, via the bending forces they set up in the back iron. It is shown that the presence of two field components of different pole numbers leads to vibration components in addition to those that would be expected in single field machines such as the induction motor. Formulations for the frequencies and magnitudes of the expected vibration components are given and verified experimentally. It is shown that the strength of the vibration components is highly dependent on the choice of pole numbers in the machine, with some much worse than equivalent induction machines and some very similar. The methodology presented enables designers to determine whether their machines are likely to suffer from vibration problems in advance of construction, and to apply remedies where appropriate. © The Institution of Engineering and Technology 2014.

Motor systems: reaching out and grasping the molecular tools.

Two recent studies provide important insights into the organization of premotor circuitries, showing that control of highly-specific skilled forelimb movements, such as reaching and grasping, requires activation of specific subpopulations of neurons in the brainstem and spinal cord.

Achievements and challenges in machine vision-based inspection of large concrete structures

Large concrete structures need to be inspected in order to assess their current physical and functional state, to predict future conditions, to support investment planning and decision making, and to allocate limited maintenance and rehabilitation resources. Current procedures in condition and safety assessment of large concrete structures are performed manually leading to subjective and unreliable results, costly and time-consuming data collection, and safety issues. To address these limitations, automated machine vision-based inspection procedures have increasingly been proposed by the research community. This paper presents current achievements and open challenges in vision-based inspection of large concrete structures. First, the general concept of Building Information Modeling is introduced. Then, vision-based 3D reconstruction and as-built spatial modeling of concrete civil infrastructure are presented. Following that, the focus is set on structural member recognition as well as on concrete damage detection and assessment exemplified for concrete columns. Although some challenges are still under investigation, it can be concluded that vision-based inspection methods have significantly improved over the last 10 years, and now, as-built spatial modeling as well as damage detection and assessment of large concrete structures have the potential to be fully automated.