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Model-based expert system to automatically adapt milling forces in Pareto optimal multi-objective working points

机译:基于模型的专家系统,可自动适应帕累托最优多目标工作点中的铣削力

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摘要

The objective of this paper is to present an open and modular expert rule-based system in order to automatically select cutting parameters in milling operations. The knowledge base of the system presents considerations of stability, machine drives efficiency and restrictions while adaptively controlling milling forces in suitable working points. Moreover, a novel classical cost function has been conceived and constructed to Pareto-optimise cutting parameters subjected to multi-objective purposes, namely: tool-life, surface roughness, material remove rate and stability rate parameter. Different Pareto optimal front solutions can be obtained modulating the weighting factors of the cost function. Additional rules have been added in order to manually and/or automatically modulate this cost function. Furthermore, a database which relates weighting factors, cutting conditions and cost function variables is produced for learning purposes. Chatter detection and suppression system automatically feedback to the system to take into account non-modelled disturbances. Finally, since the knowledge of the system is basically obtained from mathematical models, the possibility of combining experience and knowledge from expert engineers and operators is included. In this way, best practice from mathematical modelling and expert engineers and operators is joined in one system obtaining a full, automated system combining the best of each world. As a result, the expert rule-based system selects Pareto optimal cutting conditions for a broad range of milling processes, sorting out automatically different problems such as chatter vibrations, incorporating model reference adaptive control (MRAC) of forces. This procedure is intuitive, being executed in the same way as a human expert would do and it provides the possibility to interact with expert engineers and operators in order to take into account their experience and knowledge. Finally, the expert system is designed in modular form allowing incorporating new functionalities in rule based forms to them or just adding new modules to improve the performance of the milling system.
机译:本文的目的是提出一种基于专家规则的开放式模块化系统,以便在铣削操作中自动选择切削参数。该系统的知识库介绍了稳定性,机器驱动效率和限制因素,同时在合适的工作点自适应地控制铣削力。此外,已经构想并构造了新颖的经典成本函数,以进行多目标的帕累托优化切削参数,即:刀具寿命,表面粗糙度,材料去除率和稳定率参数。可以通过调节成本函数的加权因子来获得不同的Pareto最优前解决方案。为了手动和/或自动调整此成本函数,添加了其他规则。此外,为了学习目的,产生了与加权因子,切削条件和成本函数变量相关的数据库。颤振检测和抑制系统会自动反馈给系统,以考虑非建模干扰。最后,由于该系统的知识基本上是从数学模型中获得的,因此可以将专家工程师和操作员的经验和知识相结合。通过这种方式,将数学建模,专家工程师和操作员的最佳实践结合到一个系统中,从而获得了一个结合了世界上最好水平的完整自动化系统。结果,基于专家规则的系统为广泛的铣削过程选择了帕累托最优切削条件,并自动结合了模型参考自适应控制(MRAC),自动解决了诸如颤振之类的不同问题。此过程很直观,以与人类专家相同的方式执行,并且为与专家工程师和操作员进行交互以考虑他们的经验和知识提供了可能性。最终,专家系统以模块化形式设计,允许将基于规则形式的新功能并入其中,或者仅添加新模块以改善铣削系统的性能。

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