康炤旭     ★北京广利核系统工程有限公司

摘要：DCS系统是核电站的神经中枢，DCS系统的安全稳定运行对核电 站的安全具有重要意义。DCS系统本身具有丰富的自诊断功能，当系统 出现异常也会记录大量的在线和离线日志。对于离线日志目前的分析 手段比较单一，只能通过人工方式进行日志的提取与分析。本文描述 了一种提高离线日志的提取与分析效率的方法，利用Windows自带的 API函数，文件传输命令等自动获取DCS系统离线日志并统一收集到指 定节点。利用Python语言对收集到的离线日志进行分析，结合DCS系 统特点，从离线日志中提取出影响DCS系统稳定运行的信息。这些信息 采用JSON异步读取的方式，通过ECharts图表工具将分析结果以html 格式进行在线展示，辅助操作员对DCS系统的健康状态进行辅助分析及 判断，为DCS的智能化运维提供了理论与技术参考。

关键词：Python；ECharts；DCS日志；IIS；JSON

Abstract: DCS system is the nerve center of normal operation of  nuclear power plant. The safe and stable operation of DCS system is  of great significance to the safety of nuclear power plants. The DCS  system itself has rich self-diagnosis functions, and a large number of  online and offline logs will be recorded when the system is abnormal.  At present, the analysis method of offline log is relatively simple,  and the log can only be extracted and analyzed manually. This paper  describes a method to improve the efficiency of offline log extraction  and analysis of offline logs, using the API function and file transfer  command of windows to automatically obtain the offline log of DCS  system and collect it to the designated nodes. Python language is used  to analyze the collected offline logs. According to the characteristics  of the DCS system, the information that affects the stable operation of  the DCS system is extracted from the offline logs. The information is  read asynchronously by JSON, and the analysis results are displayed  online in HTML format through Ecarts chart tool, which helps operators  to analyze and judge the health status of DCS system, and provides  theoretical and technical reference for intelligent operation and  maintenance of DCS.

Key words: Python; ECharts; Log of DCS; IIS; JSON

点击预览：基于数据可视化的DCS系统日志分析方法研究及应用.pdf

摘自《自动化博览》2021年5月刊