基于多元状态估计技术建模的引风机早期诊断研究Research on Early Diagnosis of Induced Draft Fan Based on Multivariate State Estimation Technology
陈统钱
CHEN Tongqian
摘要(Abstract):
随着发电厂容量的增大,机组设备越来越复杂,其相应的故障发生率也日益提高。如何对发电机组进行状态监测与早期诊断,在故障早期发现设备劣化趋势,从而减少故障发生,使发电机组安全稳定运行是近年来发电厂面临的主要难题。采用基于多变量状态估计技术的建模方法,对引风机的运行状态进行实时预测,帮助运行人员发现分析设备早期的故障特征信号并采取解决措施,避免设备进一步恶化。该方法在发电厂的实际应用表明,使用效果良好,在发电设备的早期诊断领域有着广阔的应用前景。
With the capacity increase of power plant, equipment is becoming increasingly complicated and the failure rate is increasing day by day. It is a major problem in recent years for power plants to handle that how to monitor and diagnose the generator set and detect the deterioration trend of the equipment in the early stage of the fault to reduce the faults and ensure operation safety and stability of the generating set In this paper, a modeling method based on multivariable state estimation is used for real-time forecast of the operating status of the draft fan and helping the operating personnel detect and analyze the characteristic signal of the early equipment fault, and take measures to avoid further deterioration of the equipment. The practical application of the method in power plants proves that it is effective and has a broad application prospect in the early diagnosis of power generation equipment.
关键词(KeyWords):
引风机;早期诊断;多元状态估计(MSET);建模;供油压力
induced draft fan;early diagnosis;multivariate state estimation(MSET);modeling;oil supply pressure
基金项目(Foundation):
作者(Author):
陈统钱
CHEN Tongqian
DOI: 10.19585/j.zjdl.201708010
参考文献(References):
- [1]李泉,尹峰,陈波.超临界机组主汽温模型预测控制研究[J].浙江电力,2016,35(10):40-42.
- [2]CHANG SHUPING,GAO MING.The Application of Failure Prognostic System in State Monitoring of Power Plant Generation Equipments[C].World Automation Congress Proceedings,2012.
- [3]裴玉龙,章立宗,刘永新,等.基于多源信息融合的设备动作状态自动识别方法的研究[J].浙江电力,2016,35(10):65-68.
- [4]CHENG S F,PECHT M G.Multivariate state estimation technique for remaining useful life prediction of electronic products[C].Proceedings of AAAI Fall Symp Artif Intell.Prognostics,Arlington,VA,2007.
- [5]张少敏,毛冬,王保义.大数据处理技术在风电机组齿轮箱故障诊断与预警中的应用[J].电力系统自动化,2016(14):129-134.
- [6]孙小林.火电厂风机故障预警系统的应用研究[D].北京:华北电力大学,2015.
- [7]滕卫明,刘林,卢伟明,等.基于SBM技术的发电设备故障预警系统研究[J].中国电力,2015(1):40-46.
- [8]常剑,高明.基于相似性建模的发电机组设备故障预警系统[J].机电工程,2012(5):576-579.
- [9]王军民.双级动叶可调式轴流引风机高负荷失速分析[J].浙江电力,2016,35(8):50-52.
- [10]卢建海.双机并联变频器在7 200 k W引风机中的应用[J].浙江电力,2015,34(12):58-60.
- [11]应明良,冉志超.1 000 MW机组锅炉汽动引风机运行试验分析[J].浙江电力,2015,34(7):46-48.
- [12]林彤.引风机电动机轴承烧损故障原因分析[J].浙江电力,2015,34(5):42-44.
- 引风机
- 早期诊断
- 多元状态估计(MSET)
- 建模
- 供油压力
induced draft fan - early diagnosis
- multivariate state estimation(MSET)
- modeling
- oil supply pressure