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SMART MACHINING SIMULATION BASED ON HIGH-LEVEL DATA

机译:基于高水平数据的智能加工模拟

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摘要

The main objective of any machining simulation system is to produce a model that can reveal or mimic the real machining process as accurately as possible. Current simulation systems often use G-code or CL data as input that has inherent drawbacks such as vendor-specific nature, incomplete data, irreversible data conversions and lack of accuracy. These limitations hinder the development of a 'trustworthy' simulation system. Hence, there is a need for higher-level input data that can assist with accurate simulation for machining processes. There is also a need to take into account of true behaviour and real-time data of a machine tool. The paper presents a 'near-real simulation' solution for more accurate results. STEP-NC is used as the input data as it provides a more complete data model for machining simulations. Data from the machine tool is captured by means of sensors to provide true values for machining simulation purposes. The outcome of the research provides a smart and better informed simulation environment. The paper reviewed some of the current simulation approaches, discussed input data sources for smart simulation system and proposed near-real simulation system architecture.
机译:任何加工模拟系统的主要目标是产生一个可以尽可能准确地揭示或模拟实际加工过程的模型。当前的仿真系统通常使用G代码或CL数据作为输入,这具有固有的缺陷,例如特定于供应商的性质,不完整的数据,不可逆的数据转换以及缺乏准确性。这些局限性阻碍了“可信赖”仿真系统的开发。因此,需要可以帮助精确模拟加工过程的高级输入数据。还需要考虑机床的真实行为和实时数据。本文提出了一种“近乎真实的仿真”解决方案,以实现更准确的结果。 STEP-NC用作输入数据,因为它为加工仿真提供了更完整的数据模型。来自机床的数据通过传感器捕获,以提供用于加工仿真目的的真实值。研究的结果提供了一个智能且信息灵通的仿真环境。本文回顾了一些当前的仿真方法,讨论了智能仿真系统的输入数据源,并提出了近乎真实的仿真系统架构。

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