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Multidisciplinary Design Optimization
of Modular Industrial Robots by
Utilizing High Level CAD Templates
1、Introduction
In the design of complex and tightly integrated engineering products, it is esntial to be able to handle interactions between different subsystems of multidisciplinary nature [1]. To achieve an optimal design, a product must be treated as a complete system instead of developing subsystems independently [2]. MDO has been established as a convincing concurrent design optimization technique in development of such complex products [3,4].
Furthermore, it has been pointed out that, regardless of discipline, basically all analys require information that has to be extracted from a geometry model [5]. Hence, according
to Bow-cutt [1], in order to enable integrated design analysis and optimization it is of vital importance to be able to integrate an automated parametric geometry generation system into the design framework. The automated geometry generation is a key enabler for so-called geometry-in-the-loop[6] multidisciplinary design frameworks, where the CAD geometries can rve as framework integrators for other engineering tools.
To eliminate noncreative work, methods for creation and automatic generation of HLCt have been suggested by Tarkian [7].The principle of high HLCts is similar to high level primitives(HLP) suggested by La Rocca and van Tooren [8], with the exception that HLCts are created and utilized in a CAD environment.Otherwi, the basics of both HLP and HLCt can, as suggested byLa Rocca, be compared to parametric LEGOV Rblocks containing a t of design and analysis parameters. The are produced and stored in libraries, giving engineers or a computer agent the possibility to first topologically lect the templates and then modify the morphology, meaning the
shape,of each template parametrically.
2、Multidisciplinary Design Framework
益康胶囊MDO is a “systematic approach to design space exploration”[17], the implementation of which allows the designer to map the interdisciplinary relations that exist in a system. In this work, the MDO framework consists of a geometry model, a finite element(FE) model, a dynamic model and a basic cost model. The geometry model provides the analysis tools with geometric input. The dynamic model requires mass properties such as mass, center of gravity, and inertia. The FE model needs the meshed geometry of the robot as well as the force and torque interactions bad on results of dynamic simulations.
High fidelity models require an extensive evaluation time which has be taken into account. This shortcoming is addresd by applying surrogate models for the FE and the CAD models. The models are briefly prented below.
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2.1 High Level CAD Template—Geometry Model
Traditionally, parametric CAD is mainly focud on morphological modifications of the geometry. However, there is a limit to morphological parameterization as follows:
行政6大模块•The geometries cannot be radically modified.
•Incread geometric complexity greatly increas parameterization complexity.
The geometry model of the robot is generated with presaved HLCts, created in CATIA V5. The are topologically instantiated with unique internal design variables. Topological parameterization allows deletion, modification, and addition of geometricelements which leads to a much greater design space captured.Three types of HLCts are ud to define the industrial robot topologically; Datum HLCt which includes wireframe references required for placement for the Actuator HLCTs and Structure HLCts, as en Fig.2.
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Fig. 2 An industrial robot (left) and a modular industrial robot(right)
The names of the references that must be provided for each HLCt instantiation are stored in the knowledge ba (e Appen-dix A.4), which is arched through by the inference engine. In Appendix A, pudocode examples describes how the references are retrieved and how they are stored in the knowledge ba.
The process starts by the ur defining the number of degrees of freedom (DOF) of the robot (e Fig. 3) and is repeated until the number of axis (i) is equal to the ur defined DOF.In order to instantiate the first Structure HLCt, two Datum and two actuator instances are needed. References from the two Datum instances help orienting the structure in space, while the geometries of the actuator instances, at both ends of the link, are ud to construct the actuator attachments, as en in Figs. 2 and 3. For the remaining links, only one new instance of both datum and actuator HLCts are required, since the datum and actuator instances from adjacent links are already available.Appendix A.2 shows a pudocode example of an instantiation function. The fir左春坊
st instantiated datum HLCt is defined with reference to the absolute coordinate system. The remaining datum HLCt instances are placed in a quential order, where the coordinate system of previous instances is ud as reference for defining the position in space according to ur inputs (e also AppendixA.3). Furthermore, the type of each actuator and structure instance is ur defined.华为手机工程模式>步入式衣帽间
