基于改进粒子滤波的重型燃气轮机跳机故障预测

重型燃气轮机是清洁发电的重要装备,其轴系的振动水平是机组运行状态的直观表征.跳机故障是由于振动加大而触发的非计划突然停机,会对燃气轮机的核心部件(如叶片、拉杆等)产生较大冲击,造成设备损伤.提出基于改进粒子滤波的重型燃气轮机振动趋势预测方法,通过对粒子滤波方法的分析,提出一种二次重采样策略,使得改进粒子滤波对粒子匮乏现...

Tripping Fault Prediction of Heavy-duty Gas Turbines Based on Improved Particle Filter

Heavy-duty gas turbine was the significant equipment in clear energy, and the vibration level of the shafting system is a visual representation of the operating states. Tripping faults were as a kind of unplanned sudden shutdown triggered by increasing vibrations, which would cause a large impact on the core components of the gas turbine, such as blades and tie rods, resulting in equipment damages. A method for predicting the vibration trend of heavy-duty gas turbines was proposed based on improved particle filter. By analyzing the particle filter, a secondary resampling strategy was proposed to make the improved particle filter more resistant to particle degeneracy and improve the adaptability of particle filter. The improved method was verified in a tripping fault of a 300 MW heavy-duty gas turbine, which shows a superior prediction accuracy of tripping fault time. The proposed approach may guide the control strategy of gas turbines.