基于EPICS的电源老化测试与异常诊断系统开发

Development of a power supply aging test and fault diagnosis system based on EPICS

  • 摘要: 针对加速器各子系统电源老化测试耗时长、数据量大等特点,采用人工值守的方式监测设备运行状态不具有现实可行性,为实现对电源设备的通信状态、参数输出、异常信息等各类运行参数的长时间稳定监测,设计并实现了一种集成式数据采集与异常诊断系统。系统基于实验物理与工业控制系统(EPICS)架构,利用控制系统工作室(CSS)作为操作员界面开发工具,结合 JavaScript 实现多过程变量(PV) 的安全读取机制,通过逐变量异常隔离与try-catch异常捕获技术,实现正常运行数据的长时间连续记录与通信异常的日志输出。该系统已在三种型号的电源老化测试任务中成功应用,结果表明,该系统具有良好的可靠性与稳定性。

     

    Abstract:
    Background Power supplies are critical components in high-energy physics facilities and accelerator systems. Aging testing is essential to verify long-term reliability and operational stability, but such tests feature long durations and massive data volumes, making manual monitoring inefficient and infeasible. Stable communication and real-time parameter monitoring are also vital for ensuring safe and controllable operation during testing.
    Purpose This study aims to develop a highly reliable, automated system for long-term monitoring, data recording, and fault diagnosis of power supplies during aging tests, with the goal of achieving uninterrupted data acquisition, accurate fault logging, and strong system stability for industrial-grade accelerator power supply applications.
    Methods An integrated monitoring and fault diagnosis system is constructed based on the Experimental Physics and Industrial Control System (EPICS) architecture. Control System Studio (CSS) is used to develop the operator interface. JavaScript is applied to implement a robust multi-PV secure reading mechanism. Per-variable anomaly isolation and try-catch exception handling are adopted to ensure fault localization and system robustness. A dual-thread structure is designed to separate UI interaction and background data recording.
    Results The system was validated in 72 h aging tests on three types of power supplies. It achieved stable continuous data recording at a 10 s sampling interval, accurately captured communication anomalies, and generated standardized fault logs. No crashes or data losses occurred during long-term operation, and all monitored parameters remained within designed accuracy ranges.
    Conclusions The developed system satisfies the requirements of long-duration, high-stability power supply aging monitoring. It enables automatic data collection, real-time visualization, and precise fault diagnosis, greatly improving test efficiency and traceability. The system provides a practical and standardized solution for automated aging evaluation of accelerator power supply systems.

     

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