A SET-BASED SYSTEM FOR ELIMINATING INFEASIBLE DESIGNS IN ENGINEERING PROBLEMS DOMINATED BY UNCERTAINTY-猫眼课题宝

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1997

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作者：

W. Finch;A. Ward

本文概述了一个系统，消除不可行的设计，从工程设计问题占主导地位的多个来源的不确定性。它概述的方法表示约束的设计参数的值集使用量化的关系，一类特殊的谓词逻辑表达式，表达了工程系统中固有的一些因果信息。本文扩展了约束满足技术，并描述了消除算法，量化的关系和目录的公差或可调部分。它演示了一个简单的电子电路上的这些工具的效用，并描述了它们的实现和测试的原型软件工具。1.0引言这项工作解决类的设计问题，其中的不确定性复杂的设计，制造和工程系统的操作。不确定性从许多来源进入设计过程，包括：制造变化，环境变化，操作员调整和其他工程师决策的不确定性。例如，在电子设计中，元件公差通常对设计的成功至关重要。与（Ward，89）相比，这种方法提供了更大的表达能力，更清晰的语义，以及与计算机科学中成熟思想的更紧密联系。在设计过程中包括不确定性的结果是，精确的值不再足以描述工程系统的属性。例如，电子工程师很少用标称值来描述电阻，通常使用公差值（例如100欧姆±10%）。对于电阻器，这种表示比单个值更有表现力;它限制了有关可能的制造变化的信息。已经提出了几种表示法，用于包括工程分析和设计中的变化。概率分布，例如正态曲线，通常描述由随机过程引起的变化。(Wood和Antonsson，89）和（Wood，et. al，92）使用模糊集表示来编码并通过工程方程传播不精确性。(Ward，89）使用封闭和标记的区间来表示参数的可能值和所需值的集合。（Habib and Ward，91）然后将这种方法扩展到任意集合。在本文所述的方法中，封闭的区间描述了许多类型的设计变化，然而，新的传播操作取代传统的区间数学。本节的其余部分将简要讨论设计过程的基于集合的范例，并为一个简单的电子电路制定一个设计问题。以下各节描述系统的每个组件并将其应用于设计示例。最后，这些想法被集成到一个软件工具中，通过消除不可行的设计来减少设计空间的大小。1.1基于集合的设计这种方法在基于集合的设计范式的框架内最容易理解。基于集合的设计是沃德创造的一个术语，描述了一个过程，其中“设计师.他们必须在一系列操作条件下对一系列工件（物理对象）进行推断;他们不能简单地模拟或分析单个的、完全指定的设计”（Ward，89）。这与迭代或点到点的方法形成了对比，迭代或点到点的方法综合了一个单一的解决方案，然后通过一系列的分析，评估和修改来发展设计（例如，参见Shigley和Mitchell，83）。一个例子，改编自（李，96），说明了如何基于集合的推理有效地找到一些类型的答案，

This paper gives an overview of a system which eliminates infeasible designs from engineering design problems dominated by multiple sources of uncertainty. It outlines methods for representing constraints on sets of values for design parameters using quantified relations, a special class of predicate logic expressions which express some of the causal information inherent in engineering systems. The paper extends constraint satisfaction techniques and describes elimination algorithms that operate on quantified relations and catalogs of toleranced or adjustable parts. It demonstrates the utility of these tools on a simple electronic circuit, and describes their implementation and test in a prototype software tool. 1.0 INTRODUCTION This work addresses classes of design problems in which uncertainty complicates the design, manufacture, and operation of engineering systems. Uncertainty enters design processes from many sources, including: manufacturing variations, environmental changes, operator adjustment, and uncertainty in the decisions of other engineers. In electronic design, for example, component tolerances are often critical to a design’s success. Compared with (Ward, 89) this approach offers greater expressive power, a clearer semantics, and closer ties to well-established ideas in computer science. A result of including uncertainty in design processes is that precise values are no longer sufficient to describe the attributes of engineering systems. Electronic engineers, for example, rarely describe resistors solely by nominal values, typically using toleranced values (e.g. 100 ohms ±10%) instead. For resistors, this representation is more expressive than a single value; it constrains information about possible manufacturing variations. Several representations have been proposed for including variations in engineering analysis and design. Probability distributions, e.g. normal curves, often describe variations resulting from stochastic processes. (Wood and Antonsson, 89) and (Wood, et. al, 92) use fuzzy set representations to encode and propagate imprecision through engineering equations. (Ward, 89) uses closed and labeled intervals to represent sets of possible and required values for parameters. (Habib and Ward, 91) then extend this approach to arbitrary sets. In the approach described in this paper, closed intervals describe many types of design variation; however, new propagation operations replace conventional interval mathematics. The remainder of this section briefly discusses the Set-Based Paradigm for design processes and formulates a design problem for a simple electronic circuit. The following sections describe each component of the system and apply it to the design example. Finally, these ideas are integrated into a software tool that reduces the size of design spaces by eliminating infeasible designs. 1.1 Set-Based Design This approach is most readily understood within the framework of the Set-Based Design paradigm. Set-Based Design is a term coined by Ward describing a process in which “designers...must draw inferences about sets of artifacts (physical objects) under sets of operating conditions; they cannot simply simulate or analyze single, completely specified designs” (Ward, 89). This contrasts iterative, or p int-to-point , approaches which synthesize a single solution and then evolve the design through a series of analyses, evaluations and modifications (see for example Shigley and Mitchell, 83). An example, adapted from (Lee, 96), illustrates how set-based reasoning efficiently finds answers to some types of

A SET-BASED SYSTEM FOR ELIMINATING INFEASIBLE DESIGNS IN ENGINEERING PROBLEMS DOMINATED BY UNCERTAINTY

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