Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

This paper presents the design, development and SIMULINK implementation of the lumped parameter model of C-axis drive from GEISS five-axis CNC machine tool. The simulated results compare well with the experimental data measured from the actual machine. Also the paper describes the steps for data acquisition using ControlDesk and hardware-in-the-loop implementation of the drive models in dSPACE real-time system. The main components of the HIL system are: the drive model simulation and input – output (I/O) modules for receiving the real controller outputs. The paper explains how the experimental data obtained from the data acquisition process using dSPACE real-time system can be used for the development of machine tool diagnosis and prognosis systems that facilitate the improvement of maintenance activities

Enhanced Torque Control of a PMSM Supplied by a Four-Leg Voltage Source Inverter Using the Third Harmonic

This paper investigates an electrical drive composed of a four-leg voltage source inverter and a three-phase starconnected surface permanent magnet synchronous machine with concentrated windings. The inverter fourth leg is clamped to the neutral point of the machine. We find the current references leading to smooth torque and maximal torque per ampere operation in the presence of a third harmonic electromotive force component. We further analyze the advantages of the proposed topology in terms of torque increase and dc-link voltage requirements

Low-cost, high-resolution, fault-robust position and speed estimation for PMSM drives operating in safety-critical systems

In this paper it is shown how to obtain a low-cost, high-resolution and fault-robust position sensing system for permanent magnet synchronous motor drives operating in safety-critical systems, by combining high-frequency signal injection with binary Hall-effect sensors. It is shown that the position error signal obtained via high-frequency signal injection can be merged easily into the quantization-harmonic-decoupling vector tracking observer used to process the Hall-effect sensor signals. The resulting algorithm provides accurate, high-resolution estimates of speed and position throughout the entire speed range; compared to state-of-the-art drives using Hall-effect sensors alone, the low speed performance is greatly improved in healthy conditions and also following position sensor faults. It is envisaged that such a sensing system can be successfully used in applications requiring IEC 61508 SIL 3 or ISO 26262 ASIL D compliance, due to its extremely high mean time to failure and to the very fast recovery of the drive following Hall-effect sensor faults at low speeds. Extensive simulation and experimental results are provided on a 3.7 kW permanent magnet drive

On the reliability of electrical drives for safety-critical applications

The aim of this work is to present some issues related to fault tolerant electric drives,which are able to overcome different types of faults occurring in the sensors, in thepower converter and in the electrical machine, without compromising the overallfunctionality of the system. These features are of utmost importance in safety-criticalapplications. In this paper, the reliability of both commercial and innovative driveconfigurations, which use redundant hardware and suitable control algorithms, will beinvestigated for the most common types of fault: besides standard three phase motordrives, also multiphase topologies, open-end winding solutions, multi-machineconfigurations will be analyzed, applied to various electric motor technologies. Thecomplexity of hardware and control strategies will also be compared in this paper, sincethis has a tremendous impact on the investment costs

Techno-economic comparison of operational aspects for direct drive and gearbox-driven wind turbines

The majority of wind turbines currently in operation have the conventional Danish concept design-that is, the three-bladed rotor of such turbines is indirectly coupled with an electrical generator via a gearbox. Recent technological developments have enabled direct drive wind turbines to become economically feasible. Potentially, direct drive wind turbines may enjoy higher levels of availability due to the removal of the gearbox from the design. However, this is only a theory: so far not substantiated by detailed analytic calculation. By providing such a calculation, this paper enables us to quantitatively evaluate technical and economic merits of direct drive and gearbox-driven wind turbines

Why (and How) Networks Should Run Themselves

The proliferation of networked devices, systems, and applications that we depend on every day makes managing networks more important than ever. The increasing security, availability, and performance demands of these applications suggest that these increasingly difficult network management problems be solved in real time, across a complex web of interacting protocols and systems. Alas, just as the importance of network management has increased, the network has grown so complex that it is seemingly unmanageable. In this new era, network management requires a fundamentally new approach. Instead of optimizations based on closed-form analysis of individual protocols, network operators need data-driven, machine-learning-based models of end-to-end and application performance based on high-level policy goals and a holistic view of the underlying components. Instead of anomaly detection algorithms that operate on offline analysis of network traces, operators need classification and detection algorithms that can make real-time, closed-loop decisions. Networks should learn to drive themselves. This paper explores this concept, discussing how we might attain this ambitious goal by more closely coupling measurement with real-time control and by relying on learning for inference and prediction about a networked application or system, as opposed to closed-form analysis of individual protocols