关键词: 重型燃气轮机, 跳机故障预测, 改进粒子滤波, 二次重采样

Abstract: 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.

Key words: heavy-duty gas turbine, tripping fault prediction, improved particle filter, secondary resampling