基于多目标进化算法的飞机燃油量指示系统快速设计

IF 5.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
D. Judt, C. Lawson, A. S. V. Heerden
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引用次数: 6

摘要

飞机上的电气、机械和流体系统的设计正日益与飞机结构定义过程相结合。一个例子是飞机燃油量指示(FQI)系统,其设计强烈依赖于油箱的几何定义。因此,需要灵活的FQI设计方法来快速评估飞机水平变化对系统级的影响。为此,提出了一种具有两阶段适应度分配和FQI特定交叉过程的遗传算法(FQI- ga)。它可以处理多种测量精度约束,与机翼油箱几何形状的参数定义相耦合,并通过两个性能目标进行测试。一系列可比较的节点放置问题的交叉程序对FQI-GA进行了测试。结果表明,探针结构的组合特性和精度约束要求在任何交叉过程之前都有一个探针集选择机制。采用近似的空客A320要求和油箱几何形状进行了案例研究,结果与FQI-GA得到的探头位置结果吻合良好。在可达性和探测质量方面,帕累托锋面是线性的,质量变化不大。案例研究证实,FQI- ga方法可以包含复杂的需求,并且设计人员可以使用它来快速研究FQI探针布局和权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rapid design of aircraft fuel quantity indication systems via multi-objective evolutionary algorithms
The design of electrical, mechanical and fluid systems on aircraft is becoming increasingly integrated with the aircraft structure definition process. An example is the aircraft fuel quantity indication (FQI) system, of which the design is strongly dependent on the tank geometry definition. Flexible FQI design methods are therefore desirable to swiftly assess system-level impact due to aircraft level changes. For this purpose, a genetic algorithm with a two-stage fitness assignment and FQI specific crossover procedure is proposed (FQI-GA). It can handle multiple measurement accuracy constraints, is coupled to a parametric definition of the wing tank geometry and is tested with two performance objectives. A range of crossover procedures of comparable node placement problems were tested for FQI-GA. Results show that the combinatorial nature of the probe architecture and accuracy constraints require a probe set selection mechanism before any crossover process. A case study, using approximated Airbus A320 requirements and tank geometry, is conducted and shows good agreement with the probe position results obtained with the FQI-GA. For the objectives of accessibility and probe mass, the Pareto front is linear, with little variation in mass. The case study confirms that the FQI-GA method can incorporate complex requirements and that designers can employ it to swiftly investigate FQI probe layouts and trade-offs.
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来源期刊
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering 工程技术-工程:综合
CiteScore
9.90
自引率
21.50%
发文量
21
审稿时长
>12 weeks
期刊介绍: Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal. The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems. The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering. It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality. Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.
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