A multi-point and multi-layer coupling prediction method of wind speed along high-speed railway

Abstract

The invention discloses a multi-point and multi-layer coupling prediction method of wind speed along a high-speed railway. The method includes the following steps: 1. Install 5 auxiliary wind measuring stations around the target wind measuring station position; 2. Filter the original wind speed data and After decomposition, wavelet noise reduction is performed; 3. Signal summation and reconstruction; 4. Select m auxiliary wind measurement stations that are more significant than the target wind measurement station; 5. Each frequency layer of the selected auxiliary wind measurement station is Establish a prediction model for each PF component of the sequence; 6. Use the PF components of each frequency layer of the selected m auxiliary wind measurement stations as input, use the PF components of each frequency layer of the target wind measurement station as the output, and use GA optimization The RBF neural network is trained; 7. Use the multi-step ahead prediction values ​​of m auxiliary wind measurement stations to obtain the multi-step ahead wind speed prediction value of the target wind measurement station. The invention can perform high-precision multi-step advance prediction of wind speed along the railway for effective train dispatching and command in high-speed railway strong wind environments, and can avoid data interruption caused by hardware failure of a single wind measuring station.

Description

technical field [0001] The invention belongs to the field of railway wind speed prediction, in particular to a multi-point and multi-layer coupling prediction method for wind speed along a high-speed railway. Background technique [0002] my country has a vast territory, and the railway wind environment is complicated, and strong winds often occur in some places. Strong wind is one of the main disasters leading to train accidents, ranging from train outage to severe train crashes. In special wind field areas, such as tunnel entrances, bridges, tuyeres, areas where different wind-shielding facilities meet, and curved road sections, etc., the flow field around the train changes more obviously, and the aerodynamic load changes significantly, making the train more prone to accidents. With the development of my country's railways, the speed of trains is gradually increasing. The shape, traction mode, and structure of the EMU are very different from those of ordinary speed train...

AI Technical Summary

Problems solved by technology

Existing railway wind speed prediction methods are mostly based on a single anemometer station, and the sampling signal is single, which cannot avoid the problems caused by the hardware failure of a single anemometer station

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