摘要
根据支撑向量集和神经网络及回归分析算法相结合的数据挖掘理念,对电站风机的运行状态进行在线测量和数据处理。利用风机性能曲线,实时显示风机运行在性能曲线上的位置,避免因风机自身抢风而造成风机失速现象。根据风机实时效率及功率大小,调整风机的出力,并适度匹配汽动引风机的转速。精细调整风机变导叶的角度,确保风机运转于高效区,降低了机组煤耗。
According to the concept of data mining combining support vector set and neural network and regression analysis algorithm, on-line measurement and data processing of power station rafts running state are carried out. The fan performance curve is used to display the position of the fan on the performance curve in real time, so as to avoid fan stall. According to the fan real-time efficiency and power size, adjust the fan output, and match the speed of the steam fan. Finely adjust the angle of the fan to change the guide vane, ensure the fan run in the high efficiency area, and reduce the coal consumption of the unit.
出处
《电站辅机》
2017年第2期36-38,44,共4页
Power Station Auxiliary Equipment
关键词
汽动
引风机
效能
数据
动态
监视
系统
应用
steam induced, draft faro effieiency
data
dynamic
monitor
system
application
