Quality control algorithm of second level wind speed monitoring data along high speed railway based on PI-BBI
The ultrasonic anemometer of high-speed rail is susceptible to external interference to produce second-level abnormal wind speed due to the installation environment.The existing basic quality control methods and minute-level time-interval quality control algorithms in the meteorological field cannot accurately identify the second-level abnormal wind speed,resulting in that the monitoring wind speed can not well meet the second-level wind speed monitoring and early warning requirements of high-speed rail-way.To solve the problem,a second-level wind speed monitoring data quality control algorithm based on PI-BBI was proposed according to the abnormal value data characteristics of wind speed monitoring along the high-speed railway.Firstly,a two-way memory network with long-and short-term was used to predict wind speed anomalies based on physical information and obtains the prediction error.Then the prediction error was smoothed by an improved exponential weighted moving average method.Finally uses an isolated forest was used to detect outliers in the smooth error sequence,enabling the identification of outliers in the raw wind speed series.Experimental results show that this quality control algorithm can effectively improve the quality of wind speed monitoring data along the high-speed railway.The accuracy and predictability of wind speed monitoring and early warning are improved.
NETL
NSTL
万方数据
