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Predictive maintenance and safety operation by device integration on the QUEST large experimental device

机译:试验大型实验装置对设备集成的预测维护和安全运行

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摘要

As technology has improved in recent years, it has become possible to create new valuable functions by combining various devices and sensors in a network. This concept is referred to as the Internet of Things (IoT), and predictive maintenance is a new valuable function associated with the IoT. In large-scale experimental facilities with many researchers, it is not desirable that experiments cannot be performed due to sudden failure of equipment. For this reason, it is important to predict the failure in advance based on the measurement results of sensors and to perform repairs in a planned manner. On the Q-shu University experiment with steady-state spherical tokamak (QUEST) large experimental device, it is necessary to drive a large current of 50 kA, and the diagnosis of its power line deterioration is well performed as predictive maintenance through the evaluation of its contact resistances of several micro ohms order on the network. In addition, as an example of the IoT, mechanisms to assist safe operation, such as a sound alarm system and an entrance management system, are built by sharing experimental information between devices via the network.
机译:随着近年来技术的改善,可以通过在网络中组合各种设备和传感器来创造新的有价值的功能。这个概念被称为物联网(物联网),预测性维护是与物联网相关的新贵函数。在具有许多研究人员的大型实验设施中,不希望由于设备的突然故障而无法进行实验。因此,重要的是基于传感器的测量结果预测预先预测失败,并以计划方式执行维修。在Q-Shu大学实验与稳态球形Tokamak(Quest)大型实验装置,有必要推动50 ka的大电流,通过评估,其电力线劣化的诊断很好地进行了预测性维护它在网络上的几个微欧姆订单的接触电阻。另外,作为IOT的示例,通过通过网络共享设备之间共享实验信息,构建辅助安全操作的机制,例如声音警报系统和入口管理系统。

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