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Mathematische Modellbildung zur Befahrbarkeitssimulation einer mobilen Tiefsee-Arbeitsmaschine
(1988)
Die Forderung nach dem systematischen Gewinnen von Tiefsee-Erzen, wie beispielsweise Manganknollen, mit selbstfahrenden Arbeitsmaschinen führt auf das schwierige Problem der Befahrbarkeit (Traffikabilität) des Tiefseebodens. Im vorliegenden Beitrag wird ein mathematisches Modell zur Befahrbarkeitssimulation einer ferngesteuerten Sammelmaschine vorgestellt. Am Beispiel eines, als Konstruktionsentwurf spezifizierten, aktiven Manganknollenkollektors im großtechnischen Maßstab werden die Modellannahmen und Voraussetzungen für den zugrundeliegenden Tiefseeboden, das Fahrwerk und die betrachteten Betriebszustände und Lastsituationen beschrieben. Mit Hilfe eines koordinatentransformierten Kräftesystems werden die Wechselbeziehungen zwischen Tiefseeboden und einem Vierraupen-Fahrwerk in einem Algorithmus zusammengefaßt. Als Anwendungsbeispiele werden mittels EDV-Programmierung interessierende Betriebszustände und Lastsituationen simuliert. Abschließend werden weitere Modellvarianten aufgezeigt.
Yams of the most widely differing nature are produced in textile mills. The production stages necessary for this are carried out with the aid of textile machines. Between these individual textile machines - from cards to spinning machines - sliver cans serve as a rule as transport containers, in which the sensitive sliver material is temporarily stored, and presented to the next production stage.
Der vorliegende Beitrag befaßt sich mit Automatisierungsmöglichkeiten in Textilbetrieben für konventionelle als auch für nichtkonventionelle Spinnverfahren. Aus der Vielzahl derzeit existenter Produktionsschritte werden die standardisierbaren Automatisierungskombinationen zwischen den eingesetzten Textilmaschinen von Karden bis zu Spinnautomaten herausgearbeitet. Hierfür werden die heute in der Praxis befindlichen Transportmittel aufgezeigt und, vom Materialfluß ausgehend, die Zuordnungsmöglichkeiten der Maschinen in den Produktionsschritten und deren Automatisierungsbausteine definiert. Durch eine ganzheitliche Betrachtungsweise werden je nach Automatisierungsziel die verschiedenen Lösungsansätze diskutiert und als Bausteine gegenübergestellt. Hierdurch werden neue mechatronische Automatisierungslösungen vorgestellt, die eine Integration von Produktionsschritten oder die Automatisierung zwischen den einzelnen Produktionsschritten ermöglicht.
Bond graph modelling was devised by Professor Paynter at the Massachusetts Institute of Technology in 1959 and subsequently developed into a methodology for modelling multidisciplinary systems at a time when nobody was speaking of object-oriented modelling. On the other hand, so-called object-oriented modelling has become increasingly popular during the last few years. By relating the characteristics of both approaches, it is shown that bond graph modelling, although much older, may be viewed as a special form of object-oriented modelling. For that purpose the new object-oriented modelling language Modelica is used as a working language which aims at supporting multiple formalisms. Although it turns out that bond graph models can be described rather easily, it is obvious that Modelica started from generalized networks and was not designed to support bond graphs. The description of bond graph models in Modelica is illustrated by means of a hydraulic drive. Since VHDL-AMS as an important language standardized and supported by IEEE has been extended to support also modelling of non-electrical systems, it is briefly investigated as to whether it can be used for description of bond graphs. It turns out that currently it does not seem to be suitable.
Multidisciplinary systems are described most suitably by bond graphs. In order to determine unnormalized frequency domain sensitivities in symbolic form, this paper proposes to construct in a systematic manner a bond graph from another bond graph, which is called the associated incremental bond graph in this paper. Contrary to other approaches reported in the literature the variables at the bonds of the incremental bond graph are not sensitivities but variations (incremental changes) in the power variables from their nominal values due to parameter changes. Thus their product is power. For linear elements their corresponding model in the incremental bond graph also has a linear characteristic. By deriving the system equations in symbolic state space form from the incremental bond graph in the same way as they are derived from the initial bond graph, the sensitivity matrix of the system can be set up in symbolic form. Its entries are transfer functions depending on the nominal parameter values and on the nominal states and the inputs of the original model. The sensitivities can be determined automatically by the bond graph preprocessor CAMP-G and the widely used program MATLAB together with the Symbolic Toolbox for symbolic mathematical calculation. No particular program is needed for the approach proposed. The initial bond graph model may be non-linear and may contain controlled sources and multiport elements. In that case the sensitivity model is linear time variant and must be solved in the time domain. The rationale and the generality of the proposed approach are presented. For illustration purposes a mechatronic example system, a load positioned by a constant-excitation d.c. motor, is presented and sensitivities are determined in symbolic form by means of CAMP-G/MATLAB.