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On-line tool condition monitoring and control system in forging processes

机译:锻造过程中的在线工具状态监控系统

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Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.
机译:冷散装金属成型使得大规模生产小型复杂固体零件经济上可行。在金属成形中使用的工具在初步成本估算和生产过程中具有许多不确定性,并且持续的工具更换和维护大大降低了生产率并提高了制造成本。为了解决这一点,已经开发出使用人工神经网络(ANN)的在线工具状态监测系统,以将来自多个传感器的信息集成用于锻造过程。与力,声发射信号和过程条件一起,从理论模型中开发的信息集成到ANN工具监控系统中,以预测工具寿命并提供维护计划。

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