Method for predicting psychoacoustic parameters in high-speed train based on statistical energy flow analysis

Abstract

The invention relates to a method for predicting psychoacoustic parameters in a high-speed train based on statistical energy flow analysis. The method comprises the steps of: acquiring high-speed train exterior noise source excitation; conducting a sound insulation test on a high-speed train body structure sample piece; conducting an internal loss factor test on a high-speed train interior sound cavity; conducting an internal loss factor test on high-speed train interiors; predicting a sound pressure level inside the train by utilizing a statistical energy flow analysis method; and calculating and analyzing psychoacoustic objective parameters in the high-speed train. The method has the beneficial effects that the method for high-speed train interior noise simulation and modeling analysis and interior psychoacoustic objective parameter prediction is provided, is more rapid and accurate when compared with prediction methods utilizing a BP neural network and the like, and is more suitable for engineering practice.

Description

technical field [0001] The invention belongs to the field of NVH prediction and analysis in the rail transit vehicle industry, and relates to a method for predicting psychoacoustic parameters in high-speed trains based on statistical energy flow analysis. Background technique [0002] At present, domestic and foreign high-speed train interior noise prediction and analysis methods mainly include finite element method and boundary element method, hybrid analysis method, and statistical energy analysis method, which are respectively applicable to the analysis and prediction of high-speed train interior low-frequency, intermediate-frequency and high-frequency noise. It is precisely because of the difference in the applicable frequency band analysis range of each method that it is often necessary to establish a variety of different geometric analysis models, which increases the workload of simulation prediction. Especially when the geometric model is large, the finite element and...

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Problems solved by technology

[0004] There have been many cases of using the statistical energy analysis method to predict the noise in the car. It is precisely because of the use of the statistical energy theory that the calculation time is greatly shortened, which has great guiding significance in engineering, but the statistical energy analysis is only suitable for the application into the prediction and simulation analysis of high-frequency noise, while the prediction of medium and low-frequency noise has a large error

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