81 resultados para Machine-tools - Numerical control


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CAD software can be structured as a set of modular 'software tools' only if there is some agreement on the data structures which are to be passed between tools. Beyond this basic requirement, it is desirable to give the agreed structures the status of 'data types' in the language used for interactive design. The ultimate refinement is to have a data management capability which 'understands' how to manipulate such data types. In this paper the requirements of CACSD are formulated from the point of view of Database Management Systems. Progress towards meeting these requirements in both the DBMS and the CACSD community is reviewed. The conclusion reached is that there has been considerable movement towards the realisation of software tools for CACSD, but that this owes more to modern ideas about programming languages, than to DBMS developments. The DBMS field has identified some useful concepts, but further significant progress is expected to come from the exploitation of concepts such as object-oriented programming, logic programming, or functional programming.

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The paper presents a novel vector control structure for the Brushless Doubly-Fed Machine (BDFM) which is derived based on the machine synchronous operation. In fact, the synchronous operation of the BDFM provides an efficient approach for determining the required reference angle in the machine vector control structure. The utilization of such reference angle makes the vector control structure presented in this paper different from and, in fact, more effective than the existing rotor flux and stator flux orientation schemes proposed for the machine. The results of implementing the vector control scheme in simulations confirm the effectiveness of the proposed approach for the BDFM control. © 2010 IEEE.

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This paper proposed a novel control scheme for operating the Single Phase Brushless Doubly-Fed Machine (SPB) based on Stator-Flux-Oriented control algorithm. The SPB is a new type of Brushless Doubly-Fed Machine (BDFM) which shows a potential in applications which require adjustable speed such as Wind Power generation and speed adjustable Drive. The SPB can be applied to single-phase power system and the lower cost of the SPB makes the SPB suitable for low-rated power conversion applications. This paper develops the control scheme of the SPB with explicit mathematical analysis and block diagram of the controller. Experimental verification is also given. © 2011 IEEE.

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A novel test method for the characterisation of flexible forming processes is proposed and applied to four flexible forming processes: Incremental Sheet Forming (ISF), conventional spinning, the English wheel and power hammer. The proposed method is developed in analogy with time-domain control engineering, where a system is characterised by its impulse response. The spatial impulse response is used to characterise the change in workpiece deformation created by a process, but has also been applied with a strain spectrogram, as a novel way to characterise a process and the physical effect it has on the workpiece. Physical and numerical trials to study the effects of process and material parameters on spatial impulse response lead to three main conclusions. Incremental sheet forming is particularly sensitive to process parameters. The English wheel and power hammer are strongly similar and largely insensitive to both process and material parameters. Spinning develops in two stages and is sensitive to most process parameters, but insensitive to prior deformation. Finally, the proposed method could be applied to modelling, classification of existing and novel processes, product-process matching and closed-loop control of flexible forming processes. © 2012 Elsevier B.V.

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In conventional Finite Element Analysis (FEA) of radial-axial ring rolling (RAR) the motions of all tools are usually defined prior to simulation in the preprocessing step. However, the real process holds up to 8 degrees of freedom (DOF) that are controlled by industrial control systems according to actual sensor values and preselected control strategies. Since the histories of the motions are unknown before the experiment and are dependent on sensor data, the conventional FEA cannot represent the process before experiment. In order to enable the usage of FEA in the process design stage, this approach integrates the industrially applied control algorithms of the real process including all relevant sensors and actuators into the FE model of ring rolling. Additionally, the process design of a novel process 'the axial profiling', in which a profiled roll is used for rolling axially profiled rings, is supported by FEA. Using this approach suitable control strategies can be tested in virtual environment before processing. © 2013 AIP Publishing LLC.

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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.

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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.

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Previous studies of transonic shock control bumps have often been either numerical or experimental. Comparisons between the two have been hampered by the limitations of either approach. The present work aims to bridge the gap between computational fluid dynamics and experiment by planning a joint approach from the outset. This enables high-quality validation data to be produced and ensures that the conclusions of either aspect of the study are directly relevant to the application. Experiments conducted with bumps mounted on the floor of a blowdown tunnel were modified to include an additional postshock adverse pressure gradient through the use of a diffuser as well as introducing boundary-layer suction ahead of the test section to enable the in-flow boundary layer to be manipulated. This has the advantage of being an inexpensive and highly repeatable method. Computations were performed on a standard airfoil model, with the flight conditions as free parameters. The experimental and computational setups were then tuned to produce baseline conditions that agree well, enabling confidence that the experimental conclusions are relevant. The methods are then applied to two different shock control bumps: a smoothly contoured bump, representative of previous studies, and a novel extended geometry featuring a continuously widening tail, which spans the wind-tunnel width at the rear of the bump. Comparison between the computational and experimental results for the contour bump showed good agreement both with respect to the flow structures and quantitative analysis of the boundary-layer parameters. It was seen that combining the experimental and numerical data could provide valuable insight into the flow physics, which would not generally be possible for a one-sided approach. The experiments and computational fluid dynamics were also seen to agree well for the extended bump geometry, providing evidence that, even though thebumpinteracts directly with the wind-tunnel walls, it was still possible to observe the key flow physics. The joint approach is thus suitable even for wider bump geometries. Copyright © 2013 by S. P. Colliss, H. Babinsky, K. Nubler, and T. Lutz. Published by the American Institute of Aeronautics and Astronautics, Inc.

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Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity, or derivative, of the optimal filter with respect to the static parameters of the state-space model; for instance, in order to obtain maximum likelihood model parameters of interest, or to compute the optimal controller in an optimal control problem. In Poyiadjis et al. [2011] an original particle algorithm to compute the filter derivative was proposed and it was shown using numerical examples that the particle estimate was numerically stable in the sense that it did not deteriorate over time. In this paper we substantiate this claim with a detailed theoretical study. Lp bounds and a central limit theorem for this particle approximation of the filter derivative are presented. It is further shown that under mixing conditions these Lp bounds and the asymptotic variance characterized by the central limit theorem are uniformly bounded with respect to the time index. We demon- strate the performance predicted by theory with several numerical examples. We also use the particle approximation of the filter derivative to perform online maximum likelihood parameter estimation for a stochastic volatility model.

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This paper extends the recently developed multiplexed model predictive control (MMPC) concept to ensure satisfaction of hard constraints despite the action of persistent, unknown but bounded disturbances. MMPC uses asynchronous control moves on each input channel instead of synchronised moves on all channels. It offers reduced computation, by dividing the online optimisation into a smaller problem for each channel, and potential performance improvements, as the response to a disturbance is quicker, albeit via only one channel. Robustness to disturbances is introduced using the constraint tightening approach, tailored to suit the asynchronous updates of MMPC and the resulting time-varying optimisations. Numerical results are presented, involving a simple mechanical example and an aircraft control example, showing the potential computational and performance benefits of the new robust MMPC.