Now showing 1 - 10 of 397
  • Publication
    Path-based statistical gate-level analyses considering timing and energy
    ( 2012) ; ;
    Haase, Joachim
    Global and local fluctuations in leading-edge semiconductor manufacturing affect today's integrated circuits. While the former had been known and counteracted for years already, the latter arose when moving device dimensions into the deep submicron regime. In industrial digital circuit design, global and local variations are considered separately by process corners and on-chip variations. Both approaches have been criticized being inaccurate. As an alternative, for instance Statistical Static Timing Analysis applies analytical standard cell models to handle variability on gate level. We think, however, that multivariate statistical models may be an attractive solution as well since they may combine information on timing and power. In this paper, we propose a fully statistical approach for standard cell modelling and its application in statistical gate-level analyses combining propagation delay and energy consumption for timing paths. Using 45-nm predictive technology models, our gate-level results are close to SPICE reference simulations. Nevertheless, further research on statistical standard cell modeling is required on the way towards statistical analyses of complete digital blocks.
  • Publication
    Verbesserte Wälzlagerüberwachung durch Kombination von Vibrations- und AE-Sensorik sowie multivariater, ML-gestützter Datenanalyse
    Wachsende Ansprüche an Verfügbarkeit und Effizienz von Produktionsanlagen führen zu einem größeren Bedarf, laufend Informationen über deren Zustand zu erhalten. Diese werden durch Condition Monitoring Systeme (CMS) gewonnen. Die sensorbasierte Überwachung des aktuellen Zustands ermöglicht die frühzeitige Detektion eintretender Schäden und Verschleißzustände, was zur Optimierung von Wartungsprogrammen genutzt wird. Insbesondere bei industriellen Anwendungen ist die Bandbreite der Einsatzfälle und Betriebsumgebungen der zu überwachenden Komponenten allerdings sehr groß. Ein anschauliches Beispiel sind die weit verbreiteten Wälzlager in der Antriebstechnik. Kleinste Ausführungen finden sich in der Medizintechnik, während in Windenergieanlagen und Kränen Durchmesser von mehreren Metern erreicht werden. Ebenso variieren die aufzunehmenden Lasten, Drehzahlen und Betriebsdauern sehr stark. Es werden daher deutliche Anpassungen der CMS für jeden Einzelfall notwendig. Dies betrifft zunächst die Instrumentierung mit verschiedenartiger Sensorik für Vibration, Ultraschall, Temperaturen oder Messung der Verunreinigungen in Schmiermitteln. Es zeigt sich, dass hier jeweils unterschiedliche Messgrößen zur Erzeugung aussagekräftiger Daten zu Schadensmerkmalen geeignet sind. Daraus resultieren Anpassungsarbeiten an den verwendeten Algorithmen zur Signalanalyse, Merkmalsextraktion und Klassifikation. Besonderes Potential liegt in der permanenten Instrumentierung mit heterogenen, miteinander vernetzten Sensoren im Sinne des IoT (Internet of Things) in Verbindung mit einer multivariaten Datenanalyse. Aufbauend auf einer eigens entwickelten skalierbaren Sensorplattform zur Anbindung unterschiedlicher Sensoren und ihrer Datenströme konnte durch die Kombination von Vibrations- und Acoustic Emission-Sensoren sowie Machine Learning-Algorithmen ein flexibles System zur Gleitlagerüberwachung geschaffen werden. Hauptnutzen für Anwender und Vorteile: - Erhöhung der Genauigkeit der Datenanalyse durch Aggregation heterogener Messdaten - Erhöhte Robustheit des Systems z.B. gegen variierende Einbaubedingungen des Lagers - Schnelle Anpassung und Konfiguration des Systems an unterschiedliche Anwendungen - IoT-basiertes Systemkonzept ermöglicht die Integration in vorhandene IT-Infrastrukturen
  • Publication
    Simulation platform for application development on a vision-system-on-chip with integrated signal processing
    Image sensors with integrated, programmable signal processing execute computationally intensive processing steps during or immediately after image acquisition, thereby allowing for reducing output data to relevant features only. In contrast to conventional image processing systems, the tasks of image acquisition and actual image processing in such a ""vision chip"" cannot be viewed independently of each other. Both for validating the architecture and supporting programming in the course of application development, modeling on the system level has been performed as part of the design process of the vision-system-on-chip. Apart from the implementation of all essential components of the integrated control unit as well as digital and analog signal processing, special attention has been paid to the integration into the development environment. Being able to purposefully insert parameter deviations and/or defects at different points of the analog processing enables investigations with respect to their influence on image processing algorithms performed on the image sensor. Due to its high simulation speed and compatibility to the real system, especially regarding the to-be-executed programs, the resulting simulation model is very well suited for use in application development.
  • Publication
    KI-basierte Anomaliedetektion in der Produktion
    ( 2020) ; ;
    Neudeck, Willi
    Mit der stetig zunehmenden Menge an IoT-Komponenten werden die in der Produktion aufgenommenen Datenmengen zukünftig weiterhin enorm wachsen. Für den Menschen wird es dabei zunehmend schwerer, den Überblick über den Inhalt der aufgenommenen Daten zu behalten. Automatisierte Lösungen aus dem Bereich des maschinellen Lernens bieten enorme Vorteile bzgl. Analyseaufwand und Erkennungsgenauigkeit potentieller Schadensfälle. Die direkte Klassifikation spezifischer Schadensfälle ist jedoch aufgrund der für Fehlerfälle oftmals nicht vorhandenen Daten vielfach nicht anwendbar. Stattdessen müssen in der Regel Daten des Normalbetriebs (""Gut-Fälle"") ausreichen. Abweichungen davon werden als Anomalien bezeichnet und können mittels Verfahren des maschinellen Lernens (ML) erkannt werden. Dieser Vortrag gibt einen Überblick über wesentliche Methoden der Anomalieerkennung und liefert Beispiele für deren erfolgreiche Integration in bestehende Produktionsabläufe.
  • Publication
    Miniaturization of power converters by piezoelectric transformers - chances and challenges
    ( 2017)
    Radecker, Matthias
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    Gu-Stoppel, Shan-Shan
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    Yang, Yujia
    A systematic approach of the feasibility to integrate complete piezo-based power supply on silicon is the focus of research activities within Fraunhofer EAS, ISIT an IZM. Up to now, fully integrated off-line power supplies on chip are available for below 1 Watts, e.g. from Texas Instruments. Higher power levels up to 10 Watts and more are strongly desired for many miniaturized applications as Off-Line LED light sources, integrated power supplies for communication devices as iPhone, portable devices for medical applications, portable beamers an others. The integration of high-efficient power supplies based on magnetic transformers (PT) including galvanic isolation is limited due to the physics of electromagnetism. Piezoelectric transformers can be integrated when PZT material is applied on silicon to a height of several Micrometers to form an oscillating device which will be processed after micro-bonding in an etching process. Although power density of discrete PT is already high, it can be increased by a factor of 100 to 1000 in integrated devices on silicon taking advantage of uniform crystal structure of sputtering process and improved heat removal through silicon. The driving topology can be formed by high-voltage Mosfets or multi-level low-voltage Mosfet topology based on SOI or GaN on Si and integrated micro-inductors in the future. Serial piezo-transformer-strings allow for high isolating voltage up to 4 kV and provide efficiency up to 95% or more. Synchronous rectifying devices can be formed by low-voltage Mosfets at the output stage of the power supply. The advantage will be an extreme miniaturization compared to discrete power supplies, reduction of blocking capacitors by interleaving techniques, and thus, high reliability including intelligent integrated functions as stabilization circuits, sensors or control.
  • Publication
    Body biasing for analog design: Practical experiences in 22 nm FD-SOI
    ( 2017)
    Rao, Sunil Satish
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    Shrivastava, Asish
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    This paper presents the practical application of body biasing control of ultra-deep submicron FD-SOI technologies for analog and mixed-signal designs. The body biasing control is dedicated for dynamic control of the tradeoff between speed vs. power consumption for advanced digital circuits. However, in this work we focus on trading-off and improvement of analog circuit performances. Three different circuits were explored and designed: an all CMOS bandgap reference, a 500 MSps current-steering DAC, and a 12-bit sigma-delta modulator. All designs were verified and realized in Globalfoundries 22 nm FD-SOI technology.
  • Publication
    A DAC stage analog circuit generator for UDSM and FD-SOI technologies
    ( 2016) ;
    Rao, Sunil
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    Puppala, Ajith
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    The design of analog integrated circuits requires extensive manual work which is error-prone and inefficient. With advanced ultra-deep sub-micron (UDSM) technologies, the manual design effort increases further dramatically. This work presents the application of a rethought generator approach for the efficient reusable design of a 12 bit current steering DAC. The current mirror stage of the DAC, which is arranged in the complex Q² random walk scheme for high intrinsic matching [1], is realized by a circuit generator which automatically creates schematic, symbol, and layout of the required cells within few minutes. Originally focused on a 28 nm bulk technology, the generator code was also executed in a 28 nm FD-SOI technology with minor migration effort due to the generic nature of our tool. In addition, the fast circuit generation enables an efficient layout optimization showcasing the benefit of analog circuit generators for ""bottom-up"" design [2] in advanced technology nodes.
  • Publication
    Approach to a simulation-based verification environment for material handling systems
    ( 2012) ;
    Donath, Ulrich
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    Modern material handling systems (MHS) are complex systems which are controlled by various control units on different automation levels. The design of the MHS facility layout and the development of the control units require many different CAE tools but simulation and virtual commissioning does currently not play a significant role. This paper presents an approach towards an integrated simulation-based verification and virtual commissioning environment for all phases of an MHS project. During the first phase a material flow simulation of the plant model is conducted to analyse and confirm the planned performance indicators. The model is reused for testing and verification of the control units such as material flow controller or programmable logic controllers. An automatic equivalence inspector identifies differences between simulation results.
  • Publication
    Simulation environment for a vision-system-on-chip with integrated processing
    Imagers with programmable, highly parallel signal processing execute computationally intensive processing steps directly on the sensor, thereby allowing early reduction of the amount of data to relevant features. For the purposes of architectural exploration during development of a novel Vision-System-on-Chip (VSoC), it has been modelled on system level. Aside from the integrated control unit with multiple independent control flows, the model also realizes digital and analogue signal processing. Due to high simulation speed and compatibility with the real system, especially regarding the programs to be executed, the resulting simulation model is very well suited for usage during application development. By providing the ability to purposefully introduce parameter deviations or defects at various points of analogue processing, it becomes possible to study them with respect to their influence on image processing algorithms executed within the VSoC.
  • Publication
    Ontology-based Building Energy System Commissioning and Monitoring
    Commissioning and operating building energy systems necessitates much configuration and testing work of the building monitoring and automation system. Generally suppliers and installers use singular proprietary software systems and customized monitoring databases. Once setup and in operation, there is also no guarantee that the building is energy-efficient and most of time building users themselves act as energy wasting factors due to their wrong usage of the building energy system. As a response, the presented work aims at developing an expert system that shall ease the transition between design and operation as well as provide live recommendations for a continuous commissioning of the building energy system. For that purpose, it relies on Building Information Modeling (BIM) and Semantic Web technologies. The presented approach tries then to bring a complementary added value to classical building automation and control systems (BACS) by the means of semantic modeling and knowledge reuse for semantic analysis and characterization of the building energy system and its operational conditions. For that purpose, it implements a knowledge base of energy conservation measures and potential operating errors that prescribe energy-efficiency actions and handlings to building users or a facility managers. The system consumes for a part building data gathered during its operation through monitoring system. For another part, it relies on metadata contained in initial BIM-compliant building design models. The resulting software application might be used in the future as an add-on to existing building management systems (BMS). Modern BMS are able to handle a huge amount of data that are analyzed for supervising, controlling and benchmarking buildings. BMS data are mainly gained through sensors and meters that provide information about e.g. the operational state of technical equipment, indoor temperature or energy consumption. Because of its highly time-dependent nature, this kind of information can be categorized as dynamic data about a building in contrast to static data which represent the building and its technical systems as they are i.e. as built physical entities. This latter kind of information encompasses data about the energy system components, their technical characteristics and their layout in the building. Even if numerous dynamic data are produced during building operation there is no much use of building static information created during its design. In view of that, the proposed methodology aims at closing this informational gaps between building design and operation by making reuse of initial design models serialized in IFC. The intrinsic relationships between dynamic and static data are then represented into some ontologies and analyzed by means of logical reasoning. In existing BMS those relationships are semantically poor and only contained partially in the backend data model of the BMS, like a relational database in most cases. The proposed semantic building information model is then used for interpreting building energy system behaviors and identifying best energy conservation measures. More specifically, an energy system ontology together with a risk ontology are introduced to support reuse of knowledge for optimized building operation.