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Updated: Jul 22, 2026

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在具有机器学习的粒子加速器中预测故障的操作数据

Majdi I Radaideh1,2, Chris Pappas1, Mark Wezensky1

  • 1Spallation Neutron Source, Oak Ridge National Laboratory, Oak Ridge, TN 37830, United States.

Data in brief
|November 6, 2023
PubMed
概括

这项研究收集了来自Spallation中子源的电力系统数据,创建了一个有价值的数据集,用于训练机器学习模型,以预测和防止粒子加速器的故障.

关键词:
错误的预后是错误的预后健康管理健康管理高压转换器调制器高压转换器调制器机器学习 机器学习信号处理 信号处理分裂中子源的中子来源是分裂中子.

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Three-Phase Short Circuit—Unloaded Synchronous Machine01:21

Three-Phase Short Circuit—Unloaded Synchronous Machine

Conducting a three-phase short circuit test on an unloaded synchronous machine helps understand its impact on the system. The AC fault current's oscillogram, with the DC offset removed, reveals that the waveform amplitude decreases from an initially high value to a steady-state level for one phase of the machine.
This behavior occurs due to the magnetic flux produced by the short-circuit armature currents. Initially, these currents follow high-reluctance paths but eventually shift to...