摘要
火电厂的锅炉燃烧系统涉及多个因素和环节,如炉内燃烧、煤粉制备等,任何环节出现故障问题,都会严重影响整个系统的燃烧效率及运行效果。本文以火电厂锅炉燃烧过程与原理为切入点,深入探讨了常见故障类型原因、人工智能的具体应用,并选取数字孪生技术展开试验探究。结果显示,基于数字孪生技术构建虚拟模型,实时和燃烧系统同步,可快速发现锅炉温度的变化,有效预防故障问题的发生,确保锅炉系统安全、可靠地运行。
The boiler combustion system in thermal power plants involves multiple factors and processes,such as in-furnace combustion and pulverized coal preparation.Any malfunction in any of these processes can seriously affect the combustion efficiency and operational effectiveness of the entire system.This article takes the combustion process and principles of boilers in thermal power plants as the starting point,deeply discusses the causes of common fault types and the specific applications of artificial intelligence,and selects digital twin technology for experimental exploration.The results show that building a virtual model based on digital twin technology,which is synchronized in real-time with the combustion system,can quickly detect changes in boiler temperature,effectively prevent the occurrence of faults,and ensure the safe and reliable operation of the boiler system.
作者
丛志学
谷延宏
张兆珅
王喆
Cong Zhixue;Gu Yanhong;Zhang Zhaoshen;Wang Zhe(Guoneng Kangping Power Generation Co.,Ltd.,Shenyang,Liaoning,China,110500)
出处
《仪器仪表用户》
2025年第5期87-89,共3页
Instrumentation
关键词
人工智能
火电厂
锅炉燃烧系统
故障预测
artificial intelligence
thermal power plant
boiler combustion system
fault prediction
