Intelligent Automated Modular Design Synthesis of Mechatronic Systems

机电系统智能自动化模块化设计综合

基本信息

  • 批准号:
    RGPIN-2014-06289
  • 负责人:
  • 金额:
    $ 1.75万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2018
  • 资助国家:
    加拿大
  • 起止时间:
    2018-01-01 至 2019-12-31
  • 项目状态:
    已结题

项目摘要

Mechatronics design integrates several engineering disciplines in one system and plays an increasingly important role in both research and industry. In a mechatronic system, multi-domain components stem from mechanical, electronics and control engineering to form a special integration and a functional interaction in one product. The integration required among the multi-domain components makes it difficult for engineers to understand the design task as a whole, and this inherent complexity puts great strain on their creativity as they constantly need to develop new and improved products. Existing Computer Aided Design (CAD) solutions can help them to a certain extent; but they remain passive tools relying mainly on their own knowledge. Therefore, more intelligent and dynamic CAD support is highly desirable and to this end, Artificial Intelligence can help achieve this through design automation. **The MAIN objective of this research program is to develop automated solutions based on artificial evolution to support mechatronics engineers in their design task. However, a major drawback lies in the fact that automatically generated solutions, while valid, are generally very complex and cumbersome and end up not being considered as usable design alternatives by engineers. **The HYPOTHESIS underlying this research program is that simpler/more modular artificially evolved design candidates will be used by engineers as valid design alternatives. The added modularity would allow designers to shuffle between and re-use subsystems for increased design flexibility and product functionality.**The FIRST axis of research in this program will provide optimized artificial evolution solutions that offer engineers new, simpler and usable design alternatives, and in order to mitigate models' complexity levels, modularity principles will be integrated in the evolution. We will embed modularity as a full part of the artificial evolution of new design candidates trough the definition of new mechatronics-related modularity indexes. Additionally, Mechatronic systems models will be automatically generated using a building-block modular approach. The automated design support solutions will be using evolutionary computing techniques inspired from nature such as genetic programming and genetic algorithms in order to synthesis new mechatronic systems that meet design specifications subject to various constraints. **Moreover, to reduce the design space to feasible solutions only, the developed evolutionary design solution will be constrained by an intelligent decision support system. This will allow the engineers to get more design alternatives in faster times. The constraining of the design candidates' domain and the optimization of the artificial evolution performances represents the SECOND axis of this research program.**Finally, the THIRD axis of this research program deals with validation. To this end, two relevant real-word examples will be investigated, in terms of Micro-Electro-Mechanical systems and a robotic arm manipulator. **Our proposed approach offers excellent perceptive of success because it extends the spectrum of solutions for design engineers by offering new alternatives of mechatronic designs that are both feasible and simple enough to understand, use and re-use.
机电一体化设计是一门集多个工程学科于一体的学科,在科研和工业领域发挥着越来越重要的作用。在机电一体化系统中,多领域部件源于机械、电子和控制工程,在一个产品中形成特殊的集成和功能交互。多领域组件之间的集成要求使得工程师很难从整体上理解设计任务,并且这种固有的复杂性给他们的创造力带来了巨大的压力,因为他们需要不断开发新的和改进的产品。现有的计算机辅助设计(CAD)解决方案可以在一定程度上帮助他们;但它们仍然是被动的工具,主要依靠自己的知识。因此,更智能和动态的CAD支持是非常可取的,为此,人工智能可以通过设计自动化帮助实现这一目标。**本研究计划的主要目标是开发基于人工进化的自动化解决方案,以支持机电一体化工程师的设计任务。然而,一个主要的缺点在于,自动生成的解决方案虽然有效,但通常非常复杂和繁琐,最终不会被工程师视为可用的设计替代方案。**本研究计划的假设是,工程师将使用更简单/更模块化的人工进化设计候选方案作为有效的设计替代方案。增加的模块化将允许设计人员在子系统之间切换和重用,以增加设计灵活性和产品功能。**该计划的第一轴研究将提供优化的人工进化解决方案,为工程师提供新的,更简单和可用的设计替代方案,并且为了降低模型的复杂性,模块化原则将集成到进化中。我们将通过定义新的机电一体化相关的模块化指标,将模块化作为新候选设计的人工进化的完整部分嵌入其中。此外,机电系统模型将使用构建块模块化方法自动生成。自动化设计支持解决方案将使用受自然启发的进化计算技术,如遗传编程和遗传算法,以合成满足各种约束条件下设计规范的新机电系统。**此外,为了将设计空间缩小到只有可行的方案,开发的进化设计方案将受到智能决策支持系统的约束。这将允许工程师在更快的时间内获得更多的设计方案。设计候选域的约束和人工进化性能的优化是本研究计划的第二轴。**最后,本研究计划的第三个轴涉及验证。为此,将研究两个相关的实际例子,分别是微机电系统和机械臂操纵器。**我们提出的方法提供了出色的成功洞察力,因为它为设计工程师提供了解决方案的范围,提供了既可行又易于理解、使用和重用的机电一体化设计的新替代方案。

项目成果

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Achiche, Sofiane其他文献

Using Data-Mining Approaches for Wind Turbine Power Curve Monitoring: A Comparative Study
  • DOI:
    10.1109/tste.2013.2241797
  • 发表时间:
    2013-07-01
  • 期刊:
  • 影响因子:
    8.8
  • 作者:
    Schlechtingen, Meik;Santos, Ilmar Ferreira;Achiche, Sofiane
  • 通讯作者:
    Achiche, Sofiane
Deep green function convolution for improving saliency in convolutional neural networks
  • DOI:
    10.1007/s00371-020-01795-8
  • 发表时间:
    2021-02-01
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    Beaini, Dominique;Achiche, Sofiane;Raison, Maxime
  • 通讯作者:
    Raison, Maxime
Integrated and concurrent detailed design of a mechatronic quadrotor system using a fuzzy-based particle swarm optimization
Proof of Concept of an Assistive Robotic Arm Control Using Artificial Stereovision and Eye-Tracking
Condition Monitoring of Manufacturing Processes under Low Sampling Rate

Achiche, Sofiane的其他文献

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{{ truncateString('Achiche, Sofiane', 18)}}的其他基金

Development of an Intelligent Design Support Tool for Integrated Design of Multidomain Systems
多域系统集成设计智能设计支持工具的开发
  • 批准号:
    RGPIN-2019-05497
  • 财政年份:
    2022
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
Development of an Intelligent Design Support Tool for Integrated Design of Multidomain Systems
多域系统集成设计智能设计支持工具的开发
  • 批准号:
    RGPIN-2019-05497
  • 财政年份:
    2021
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
Development of an Intelligent Design Support Tool for Integrated Design of Multidomain Systems
多域系统集成设计智能设计支持工具的开发
  • 批准号:
    RGPIN-2019-05497
  • 财政年份:
    2020
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
Development of an Intelligent Design Support Tool for Integrated Design of Multidomain Systems
多域系统集成设计智能设计支持工具的开发
  • 批准号:
    RGPIN-2019-05497
  • 财政年份:
    2019
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
Nature inspired image processing software based on Maxwell Equations
基于麦克斯韦方程组的自然启发图像处理软件
  • 批准号:
    520615-2018
  • 财政年份:
    2018
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Idea to Innovation
Intelligent Automated Modular Design Synthesis of Mechatronic Systems
机电系统智能自动化模块化设计综合
  • 批准号:
    RGPIN-2014-06289
  • 财政年份:
    2017
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual
An intelligent multi-criteria approach for supporting the design and synthesis of a virtual reality headset
支持虚拟现实耳机设计和合成的智能多标准方法
  • 批准号:
    492859-2015
  • 财政年份:
    2016
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Engage Grants Program
Dimensionnement et contrôle d'actionneurs d'un exosquelette des membres inférieurs
下属成员外骨骼行动者的维度和控制
  • 批准号:
    492768-2015
  • 财政年份:
    2016
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Engage Grants Program
Développement d'une solution intelligente et temps réel de quantification de l'erreur sur les mouvements articulaires pour aide à la décision aux chirurgiens
开发辅助外科决策运动的智能解决方案和量化错误的时间
  • 批准号:
    507306-2016
  • 财政年份:
    2016
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Engage Grants Program
Intelligent Automated Modular Design Synthesis of Mechatronic Systems
机电系统智能自动化模块化设计综合
  • 批准号:
    RGPIN-2014-06289
  • 财政年份:
    2016
  • 资助金额:
    $ 1.75万
  • 项目类别:
    Discovery Grants Program - Individual

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