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One of the challenges in condition monitoring systems is the residual life time prediction. This prediction is done based on statistical methods, based on physical knowledge about the considered process or a combination of these approaches. Physical knowledge of the system is a result of long-term experience of process operators. However, it can be gained as well by analyzing appropriately designed process models. The additional benefit of such models is that particular effects and their impact on the process behavior can be analyzed in detail and without plant operation in a shorter time. The current contribution developed in the framework of the research project Model Based Hierarchic Condition Monitoring presents such models for condition monitoring of roller chains. First, already existing high order dynamic models given by nonlinear differential equations of such chains are extended to incorporate effects that occur due to a deterioration of the chain condition. Then, a simple model is developed and compared to the high order model. Based on the two models the change in the process behavior due to a deterioration of the roller chain condition is analyzed to illustrate that these models can be used in future research in the above mentioned research project to better predict the residual life time of the considered roller chains.
This paper presents a laboratory experiment integrating the fields of electronics design, power electronics and drive control. The aim of this experiment is first to illustrate the need for a deep knowledge and the challenges in power electronics and its applications, in this particular case for drive control. The different tasks in this experiment are executed on a complete setup for a brushless dc motor test bench. The tasks assigned to the students are designed such that, in some tasks the knowledge from a particular field, power electronics, electronic design or drive control is deepened, whereas in other tasks the knowledge from more than one of these fields is needed to solve the given problem. Thus, the experiment trains students in the particular domains but illustrates as well the links between power electronics, electronic design and drive control.
Methods for increasing the energy efficiency of induction motors by an appropriate control strategy have been a subject of research during the last years. Several methods for loss minimization have been developed for induction motors operated in a steady state. In recent years, some solutions for the dynamic case have been given as well either using an online or offline optimization approach, implying a certain computational burden, which is undesired in practice. This paper shows that the appropriate application of steady state techniques during transients due to a changing motor torque is a suboptimal strategy with an acceptable performance for efficiency optimization given an induction machine where saturation effects of the main inductance must be considered. The optimization problem is simplified such that a simple suboptimal solution is possible and the quality of the suboptimal solution is investigated by simulations and measurements. The proposed solution is simple, easy to implement, and does not require an online optimization. In addition, the influence of magnetizing induction saturation is considered.
The limited interfaces of today's IC design environments for editing PCell parameters hinder a solid advancement towards more complex analog PCell modules. This paper presents Hierarchical Instance Parameter Editing (HIPE), a highly flexible concept for the customization of PCell sub-instances. Introducing a new type of parameter, HIPE facilitates the dynamic creation of multi-level editing forms reflecting the actual contents of a PCell instance. This approach greatly improves a PCell's ease-of-use, substantially simplifies PCell development, and allows for a hierarchical execution of parameter validation callbacks. Our HIPE implementation has been integrated into a professional PCell development tool and represents a key enabling technology for upcoming generations of high-level hierarchical PCells.
Der Entwurf analoger integrierter Schaltkreise ist bis heute durch einen weitgehend manuellen Entwurfsstil mit anschließender Verifikation gekennzeichnet. Das Backend dieses Prozesses bildet der Layoutentwurf, der mit der SDL-Methode (schematic driven layout) durchgeführt und mit den Verifikationsschritten DRC und LVS abgeschlossen wird. Als Ziel wird i.a. in Analogie zu den im Digitalbereich existierenden Lösungen eine vollautomatische Layoutsynthese auch für Analogschaltungen angestrebt. Die hier vorgeschlagene neue Designmethodik hat nicht diese vielfach geforderte Layoutsynthese im Analogbereich zum Inhalt. Sie stellt vielmehr einen realistischeren - und aus Sicht des Autors vor allem notwendigen - Zwischenschritt dar. Die Kernaussage besteht darin, dass zunächst eine Methode bereitzustellen ist, bei der alle die Schaltungsfunktion beeinflussenden Randbedingungen (constraints) rechnergestützt prüfbar sein müssen. Erst auf dieser Basis wird es gelingen, in einem weiteren Schritt analoges Layout zu synthetisieren. Diese These wird aus einer Betrachtung der historischen Entwicklung der EDA-Werkzeuge hergeleitet. Die Extrapolation dieser Historie lässt eine Wegskizze für einen neuen "constraint-driven" Designflow erkennen, dessen Hauptvorteil in einer rechnergestützten Absicherung der Schaltungsfunktion besteht. Weitere mögliche neue Merkmale eines solchen Designflows werden diskutiert: Abkehr von den klassischen sequentiellen Designschritten wie Platzierung und Routing hin zu einer "kontinuierlichen" Layoutentstehung und neuartige Chancen für eine wesentlich verbesserte Wiederverwendbarkeit (reuse) von Layoutergebnissen durch die Nutzung höherer Abstraktionsebenen.
This paper enhances SWARM, a novel deterministic analog layout automation approach based on the idea of cellular automata. SWARM implements a decentralized interaction model in which responsive layout modules, covering basic circuit types, autonomously move, rotate and deform themselves to let constraint-compliant, compact layout solutions emerge from a synergetic flow of self-organization. With the ability to consider design constraints both implicitly and explicitly, SWARM joins the layout quality of procedural generators with the flexibility of optimization algorithms, combining these two kinds of automation into a “bottom-up meets top-down” flow. The new enhancements are demonstrated in an OTA example, depicting the power of SWARM and its enormous potential for future developments.
In analog layout design, chip floorplans are usually still handcrafted by human experts. Particularly, the nondiscrete variability of block dimensions must be exploited thereby, which is a serious challenge for optimization-based algorithmic floorplanners. This paper presents a fundamentally new automation approach based on self-organization, in which floorplan blocks can autonomously move, rotate and deform themselves to jointly let compact results emerge from a synergistic flow of interaction. Our approach is able to minimize area and wirelength, supports nonslicing floorplan structures, can consider fully variable block dimensions, accounts for a fixed rectilinear boundary, and works absolutely deterministic. The approach is innovatively different from conventional, top-down oriented floorplanning algorithms.
Optimization-based design automation for analog ICs still remains behind the demands. A promising alternative is given by procedural approaches such as parameterized generators, also known as PCells. We are working on a complete analog design flow based on parameterized generators for entire circuits and corresponding layout modules. Because the conventional programming of such enhanced generators is far too complicated and costly, new methods are needed to ease their development. This paper presents gPCDS (graphical PCDS), a novel tool for a designer-oriented development of schematic module generators, integrated into a common schematic entry environment. The tool is based on PCDS (Parameterized Circuit Description Scheme), a meta-language for the creation of parametrized analog circuits. Schematic module generators are a very desirable complement to layout module generators in order to achieve a seamless schematic- driven layout design flow on module level. By facilitating a way of generator development that matches a design expert’s mentality, gPCDS contributes to close this gap in the analog design flow.
In contrast to IC design, MEMS design still lacks sophisticated component libraries. Therefore, the physical design of MEMS sensors is mostly done by simply drawing polygons. Hence, the sensor structure is only given as plain graphic data which hinders the identification and investigation of topology elements such as spring, anchor, mass and electrodes. In order to solve this problem, we present a rule-based recognition algorithm which identifies the architecture and the topology elements of a MEMS sensor. In addition to graphic data, the algorithm makes use of only a few marking layers, as well as net and technology information. Our approach enables RC-extraction with commercial field solvers and a subsequent synthesis of the sensor circuit. The mapping of the extracted RC-values to the topology elements of the sensor enables a detailed analysis and optimization of actual MEMS sensors.
Virtual prototyping of integrated mixed-signal smart sensor systems requires high-performance co-simulation of analog frontend circuitry with complex digital controller hardware and embedded real-time software. We use SystemC/TLM 2.0 in conjunction with a cycle-count accurate temporal decoupling approach (TD) to simulate digital components and firmware code execution at high speed while preserving clock-cycle accuracy and, thus, real-time behavior at time quantum boundaries. Optimal time quanta ensuring real-time capability can be calculated and set automatically during simulation if the simulation engine has access to exact timing information about upcoming inter-process communication events. These methods fail in the case of non-deterministic, asynchronous events, resulting in potentially invalid simulation results. In this paper, we propose an extension to the case of asynchronous events generated by blackbox sources from which a priori event timing information is not available, such as coupled analog simulators or hardware in the loop. Additional event processing latency or rollback effort caused by temporal decoupling is minimized by calculating optimal time quanta dynamically in a SystemC model using a linear prediction scheme. We analyze the theoretical performance of the presented predictive temporal decoupling approach (PTD) by deriving a cost model that expresses the expected simulation effort in terms of key parameters such as time quantum size and CPU time per simulation cycle. For an exemplary smart-sensor system model, we show that quasi-periodic events that trigger activities in TD processes are handled accurately after the predictor has settled.