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Operation Status Tracking for Legacy Manufacturing Systems via Vibration Analysis

机译:通过振动分析跟踪传统制造系统的运行状态

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Tracking the status of manufacturing systems is important for analyzing the performance of a manufacturing process. Unfortunately, legacy manufacturing systems are technologies from the yesteryears which have no Internet connectivity and very often are not programmable. Gathering operational information of such systems is often done manually with poor temporal resolution. This work proposes an Internet-of-things (IoT) approach that uses vibration sensors to track the operation status of legacy manufacturing systems. One of the challenges of using vibration data is to identify the meaning of the vibration without prior knowledge of the vibration profile and without the privilege to interrupt the manufacturing process. Although there are many existing works that capture and analyze vibration data, these existing works very often only focus on fault diagnosis and prognosis. Our work focuses on using the vibration data to monitor the operation status of a manufacturing machine. Experimental results show that the proposed vibration analysis method is able to track the operation status of a machine with more than 90% accuracy, in the worst case with 90.2% and standard uncertainty of 3.6%.
机译:跟踪制造系统的状态对于分析制造过程的性能很重要。不幸的是,传统的制造系统是过去的几年中没有互联网连接的技术,并且通常是不可编程的。此类系统的操作信息的收集通常是在较差的时间分辨率下手动完成的。这项工作提出了一种物联网(IoT)方法,该方法使用振动传感器来跟踪旧制造系统的运行状态。使用振动数据的挑战之一是在没有振动曲线的先验知识并且没有中断制造过程的特权的情况下识别振动的含义。尽管有许多现有的工作可以捕获和分析振动数据,但是这些现有的工作通常只专注于故障诊断和预后。我们的工作重点是使用振动数据来监视制造机器的运行状态。实验结果表明,所提出的振动分析方法能够以超过90%的精度跟踪机器的运行状态,在最坏的情况下具有90.2%的精度和3.6%的标准不确定度。

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