康炤旭     ★北京廣利核系統工程有限公司

摘要：DCS系統是核電站的神經中樞，DCS系統的安全穩定運行對核電 站的安全具有重要意義。DCS系統本身具有豐富的自診斷功能，當系統 出現異常也會記錄大量的在線和離線日志。對于離線日志目前的分析 手段比較單一，只能通過人工方式進行日志的提取與分析。本文描述 了一種提高離線日志的提取與分析效率的方法，利用Windows自帶的 API函數，文件傳輸命令等自動獲取DCS系統離線日志并統一收集到指 定節點。利用Python語言對收集到的離線日志進行分析，結合DCS系 統特點，從離線日志中提取出影響DCS系統穩定運行的信息。這些信息 采用JSON異步讀取的方式，通過ECharts圖表工具將分析結果以html 格式進行在線展示，輔助操作員對DCS系統的健康狀態進行輔助分析及 判斷，為DCS的智能化運維提供了理論與技術參考。

關鍵詞：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

點擊預覽：基于數據可視化的DCS系統日志分析方法研究及應用.pdf

摘自《自動化博覽》2021年5月刊