基于大数据分析的燃煤发电机组回热系统故障远程诊断

Remote Fault Diagnosis of Regenerative System of Coal Fired Generator Unit Based on Big Data Analysis

随着火电机组的技术升级与革新,回热系统故障诊断技术正逐渐朝着线上即时监测的方向发展。基于此,文章首先指出了回热系统状态监测与故障诊断面临的6大问题:检测手段、材料性能诊断、故障机理复杂、人工智能应用、缺乏故障数据和诊断技术应用推广难;随后提出了基于大数据分析的燃煤发电机组回热系统故障远程诊断,并针对性地提出了数学模型、经验知识以及数据驱动3种系统原理;最后针对性地为这3种系统绘制了流程图,以确保大数据与回热系统故障诊断能够更好地融合。

With the technical upgrading and innovation of thermal power units,the fault diagnosis technology of regenerative system is gradually moving towards the direction of online real-time monitoring.Based on this,this paper first points out six major problems faced by the condition monitoring and fault diagnosis of the regenerative system:detection means,material performance diagnosis,complex mechanism faults,application of artificial intelligence Jack of fault data and difficulty in popularization and application of diagnostic technology.Subsequendy,a remote fault diagnosis system for the regenerative system of coal-fired power generation units based on big data analysis was proposed,and three system principles:mathematical model,empirical knowledge and data driven were put forward.Finally,a flow chart was drawn for it to ensure better integration of big data and regenerative system fault diagnosis.