关键词: 火电厂, 汽轮机组, 经验模态分解, 特征通流面积, 性能劣化, 故障诊断

Abstract: In this paper, regarding the load variation under different operation conditions, the characteristic flow area of the steam turbine extraction sections is taken as the benchmark value to evaluate the deterioration of the steam turbine performance, which is calculated in terms of the specific volume and the temperature respectively. Based on the historical data of a power plant, the characteristic flow area is calculated and the error analysis is then carried out. It is discovered that the results calculated by the specific volume is more accurate than that by the temperature. To verify the correctness of the results, the C-language based dynamic web page is created for real-time monitoring by employing the characteristic flow area of the specific volume as the benchmark. Then by using the empirical mode decomposition (EMD) method, the deterioration trend is analyzed on the big data of the long-term operation such that the micro trend of each extraction section is obtained. Moreover, once the degradation reaches a certain level, an early warning will be issued for the failure alert.

Key words: thermal power plant, steam turbine unit, empirical mode decomposition (EMD), characteristic flow area (CFA), performance deterioration, fault diagnosis