Fault Prediction and Diagnosis of Boiler Combustion System Based on Artificial Intelligence
邱禄全1
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作者信息
1. 国能神福(龙岩)发电有限公司,龙岩 364000
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摘要
火力发电厂锅炉系统的可靠性和效率直接影响整个发电系统的性能和稳定性,因此提出一种基于人工智能的火电厂锅炉燃烧系统故障预测与诊断方法,结合自适应控制的智能冷却系统和数字孪生技术,实现对锅炉温度的精确控制和故障预测.智能冷却系统通过比例-积分-微分(Proportional Integral Derivative,PID)控制算法动态调节冷却介质的流量,保持锅炉在最佳温度范围内运行.利用数字孪生技术构建锅炉系统的虚拟模型,与实际系统实时同步,进行状态监测和故障预测.结果表明,该系统能够快速响应温度变化,保持系统稳定,有效预防故障的发生,提高了锅炉系统的运行效率和可靠性.
Abstract
As a primary means of electricity production,thermal power plants'boiler systems directly impact the performance and stability of the entire power generation system.This paper proposes an artificial intelligence-based method for fault prediction and diagnosis in thermal power plant boiler combustion systems,combining adaptive control intelligent cooling systems and digital twin technology to achieve precise control of boiler temperature and fault prediction.The intelligent cooling system dynamically adjusts the cooling medium flow using a Proportional Integral Derivative(PID)control algorithm,maintaining the boiler within the optimal temperature range.The virtual model of boiler system is constructed by digital twin technology,and the condition monitoring and fault prediction are carried out synchronously with the real system.The result shows that the system can quickly respond to temperature changes,maintain system stability,effectively prevent faults,and improve the operational efficiency and reliability of the boiler system.
关键词
锅炉燃烧系统/故障预测/智能冷却系统/PID控制/数字孪生技术
Key words
boiler combustion system/fault prediction/intelligent cooling system/Proportional Integral Derivative(PID)control/digital twin technology
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