ECRH系统中央控制器异常诊断设计与仿真
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中国科学院 等离子体物理研究所

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TP273

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国家重点研发计划(2017YFE0300200,2017YFE0300503,2017YFE0300401,2017YFE0400600)


Design and Simulation of Abnormal Diagnosis of Central Controller of ECRH System
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    摘要:

    异常诊断是ECRH控制系统中存在的一大问题。由于控制回旋管的信号繁多,且控制实时性要求高,一般延迟要求在微秒量级。一旦发生故障,控制系统会立即关闭各高压电源以保护回旋管。想要查找异常发生的原因,只能将各信号均接入示波器,并且等待该故障再次发生时被示波器捕获,这样不仅难以定位异常,而且耗时耗力。针对以上问题,设计了ECRH系统中央控制器的异常诊断逻辑,该诊断逻辑主要基于正常的回旋管控制流程,通过判断回旋管控制流程的走向以及各种检测输入信号来诊断异常发生的原因。将诊断逻辑与正常的回旋管控制逻辑嵌入到同一片FPGA芯片中,并发运行。时序仿真结果表明,在故障发生时能够立即输出异常信号给计算机,实现了实时在线故障检测和诊断,使整个电子回旋共振加热控制系统更加智能化。

    Abstract:

    Abnormal diagnosis is a big problem in the electronic cyclotron resonance heating control system. Since the signals for controlling the gyrotron are numerous and the real-time control requirements are high, the general delay requirement is on the order of microseconds. In the event of a fault, the control system immediately shuts down the high voltage power supplies to protect the gyrotron. If you want to find out the cause of the abnormality, you can only connect each signal to the oscilloscope and wait for the fault to occur again when it is captured by the oscilloscope. This is not only difficult to locate the abnormality, but also time-consuming and labor-intensive. Aiming at the above problems, the abnormal diagnosis logic of the central controller of the electron cyclotron resonance heating system is designed. The diagnostic logic is mainly based on the normal gyrotron control flow, and the abnormality occurs by judging the direction of the gyrotron control flow and various detection input signals. The diagnostic logic and the normal gyro control logic are embedded in the same field programmable gate array chip and run concurrently. The simulation results show that the abnormal signal can be output to the computer immediately when a fault occurs, real-time online fault detection and diagnosis is realized, and the whole electron cyclotron resonance heating control system is more intelligent.

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引用本文

杨永. ECRH系统中央控制器异常诊断设计与仿真计算机测量与控制[J].,2020,28(5):46-50.

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  • 收稿日期:2019-12-03
  • 最后修改日期:2019-12-24
  • 录用日期:2019-12-25
  • 在线发布日期: 2020-05-25
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