摘要
为提高机组运行的可靠性,减少非计划停机次数,针对某电厂超超临界机组堵磨跳机原因开展了事故分析。认为磨煤机堵煤初期调整措施不及时,严重堵煤后又进行了过度疏通,导致炉膛内实际燃料量大幅增加,燃烧显著增强,机组最终因折焰角集箱严重超温而发生跳闸。在上述分析的基础上,根据磨煤机关键运行参数,结合大数据与人工智能算法,构建了磨煤机堵煤智能预警模型,以期提前发现故障迹象,尽早采取干预措施,保证机组的安全稳定运行。上述智能预警模型应用后,机组再未出现严重堵煤故障,相关模型构建与应用经验可供后续同类机组参考。
In order to improve the reliability of unit operation and reduce the number of unscheduled shutdown,an accident analysis was carried out for the cause of wear blocking and tripping of ultra supercritical unit in a power plant.It is considered that the adjustment measures at the initial stage of coal blockage of the pulverizer are not timely,and excessive dredging is carried out after serious coal blockage,resulting in a significant increase in the actual fuel quantity in the furnace,a significant increase in combustion,and the unit finally trips due to the serious overtemperature of the flame angle header.On the basis of the above analysis,according to the key operating parameters of the pulverizer,combined with big data and artificial intelligence algorithm,an intelligent early warning model for coal blockage of the pulverizer is constructed,in order to find fault signs in advance and take intervention measures as soon as possible to ensure the safe and stable operation of the unit.After the application of the above intelligent early warning model,there is no serious coal blockage fault in the unit.The relevant model construction and application experience can be used as a reference for similar units in the future.
作者
郭云飞
罗俊然
王林
李昭
孙龙飞
赵如宇
蔺奕存
谭祥帅
冷静
桑秀军
GUO Yunfei;LUO Junran;WANG Lin;LI Zhao;SUN Longfei;ZHAO Ruyu;LIN Yicun;TAN Xiangshuai;LENG Jing;SANG Xiujun(Xi'an Thermal Power Research Institute Co.Ltd.,Xi'an 710054,China;Huaneng Guilin gas distributed energy Co.Ltd.,Guilin 541199,China;Huaneng Qinbei Power Generation Co.Ltd.,Jiyuan 459012,China)
出处
《工业加热》
CAS
2023年第4期22-25,共4页
Industrial Heating
基金
国家科技支撑计划资助项目(2020BAA03B01)
华能集团标准项目(HNBZ22-Q049)。
关键词
磨煤机
堵煤
水煤比
智能预警
大数据
coal mill
coal blockage
water coal ratio
intelligent early warning
big data