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

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.