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An industrial tool wear monitoring system for interrupted turning

机译：用于中断车削的工业工具磨损监测系统

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摘要

An effective wear-monitoring system for machine tool inserts could yield significant cost savings for manufacturers. Over the years, various methods have been proposed to achieve tool condition monitoring (TCM), and recently sensor-based approaches for indirectly estimating tool wear have become highly popular. One difficulty with collecting sensory information from machine tools is that the signal-to-noise ratio of useful information about the tool wear is extremely poor. This problem can be overcome by using advanced signal-processing methods and also by fusing the information obtained from numerous sensors into a single modelling or decision-making scheme such as neural networks (NNs). Neural networks are known for their capacity to solve problems effectively in cases where theoretical/analytical models cannot be established. Furthermore, NNs can handle noisy and incomplete data such as that typically obtained from machining operations. Although numerous authors have proposed the NN approach for TCM, various problems still hamper a practical method of applying the technique for industrial use. This paper proposes a technique which should overcome these difficulties. A cost-effective and reliable tool condition monitoring system (TCMS) was developed, utilising the advantages of NNs for a typical industrial machining operation. The operation considered is interrupted turning (facing and boring) of Aluminium alloy components for the automotive industry. The development and implementation of various hardware and software components for the proposed technique are described in this paper. The main advantages of the technique are its accuracy, reliability and cost-effectiveness.
机译：有效的机床刀片磨损监测系统可以为制造商节省大量成本。多年来，已经提出了多种方法来实现工具状态监视（TCM），并且最近基于传感器的间接估计工具磨损的方法已变得非常流行。从机床收集感觉信息的一个困难是，有关刀具磨损的有用信息的信噪比极差。通过使用高级信号处理方法以及将从众多传感器获得的信息融合到单个建模或决策方案（例如神经网络（NN））中，可以解决此问题。在无法建立理论/分析模型的情况下，神经网络以有效解决问题的能力而闻名。此外，NN可以处理嘈杂和不完整的数据，例如通常从加工操作中获得的数据。尽管许多作者提出了用于中药的NN方法，但是各种问题仍然阻碍了将该技术应用于工业用途的实用方法。本文提出了一种应克服这些困难的技术。利用NN在典型工业加工操作中的优势，开发了一种经济高效且可靠的刀具状态监控系统（TCMS）。所考虑的操作是中断汽车行业铝合金部件的车削（表面和镗孔）。本文介绍了用于该技术的各种硬件和软件组件的开发和实现。该技术的主要优点是其准确性，可靠性和成本效益。

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