Multi-model multi-feature fusion method for predicting wind speed along high-speed railway

Abstract

The invention discloses a multi-model multi-feature fusion method for predicting the wind speed along a high-speed railway, and the method comprises the following steps: 1, installing five auxiliary wind measurement stations nearby a wind measurement station; 2, carrying out the processing of original wind speed data through an interactive multi-model Kalman filtering method; 3, carrying out the wavelet processing of the filtered data, and building a prediction submodel for the low-frequency data after wavelet processing; 4, inputting target wind measurement station multistep-ahead prediction values and weather forecast target wind station prediction values obtained by a space-target wind measurement multistep-ahead prediction model, a self-target wind measurement station multistep-ahead prediction model and a weather-target wind measurement station multistep-ahead prediction model into a Bayes combined model, and obtaining the final target wind measurement station prediction value. The method can avoid the data interruption caused by a single wind measurement station hardware fault, and also can provide longer emergency processing time for the safety of the high-speed railway in a severe wind environment.

Description

Technical field [0001] The invention belongs to the field of railway wind speed prediction, and particularly relates to a multi-model multi-feature fusion method for predicting wind speed along a high-speed railway. Background technique [0002] With the sustained and stable development of my country's economy, my country's railway construction has entered a period of rapid development. With the increase of railway operating lines and the increase of train speed, the safety, stability and comfort of train operation have received more and more attention. Strong winds are one of the main natural disasters leading to train accidents. Strong winds often occur in some areas along the railway lines in my country, which brings great challenges to the safe and stable operation of trains. In order to prevent train accidents, it is necessary to establish a railway gale monitoring and early warning system so that the railway department can dispatch and command in advance. The wind speed pr...

AI Technical Summary

Problems solved by technology

At the same time, due to the reliability problems of hardware equipment, the prediction effect of a single model is unstable, and the wind speed prediction data along the railway line is not allowed to interrupt the output, so the wind speed prediction along the railway line must have stable performance and be able to output high precision continuously under various abnormal conditions forecast data

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