摘要
由于发电设备存在高维度、强非线性和多工况等建模难题,常规监测系统难以有效拟合并监测其运行过程中的复杂工况和故障。文章基于高精度数据挖掘技术,开展发电设备数据驱动建模和故障预警方法研究,并利用计算机技术,实现模型在线实例化运行,最终形成一套适配于发电设备的数据驱动故障预警系统,有效保障发电设备的安全稳定运行。
Due to the high-dimensional,strong non-linear and multi-scenario modeling difficulties of the power generation equipment,it is difficult for conventional monitoring systems to match and monitor the complex scenarios and faults during their operation effectively.Based on high-precision data mining technology,the article researches on the data-driven modeling and fault early warning methods for power generation equipment.Using computer technology,the model is instantiated online,ultimately forming a data-driven fault early warning system suitable for power generation equipment and effectively ensuring the stable operation of the power generation equipment.
作者
方超
黎璠
徐辉平
FANG Chao;LI Fan;XU Huiping(Shanghai Power Equipment Research Institute Co.,Ltd.,200240)
出处
《电机技术》
2024年第5期27-31,36,共6页
Electrical Machinery Technology
基金
上海发电设备成套设计研究院有限责任公司自主投入研发资助项目(202468169J)。
关键词
数据挖掘
发电设备
非线性
故障诊断
数据驱动建模
data mining
power generation equipment nonlinear
fault diagnosis
data-driven modeling
