A method for predicting insertion loss of high-speed railway sound barriers based on five sound source models

Abstract

The invention discloses a method for predicting the insertion loss of a high-speed railway sound barrier with five sound source modes. According to the composition, location, frequency characteristics and attenuation law of the high-speed railway noise source, the high-speed railway noise source is equivalently simplified as wheel-rail area, vehicle The lower part of the body, the upper part of the car body, the current collection system, and the structural noise source of the bridge are five parts, and the insertion loss of the wing plate to the five sound sources is calculated separately through the single sound source mode. After the sound barrier is installed, the noise of the wheel-rail area, the lower part of the car body, the upper part of the car body, the current collection system and the bridge structure noise is superimposed to the sensitive points, and the total noise level after the installation of the sound barrier is obtained, and then compared with the installation sound The noise level in front of the barrier is subtracted, and the insertion loss correction item of the bridge flange is introduced to obtain the predicted value of the insertion loss using the calculation method of five sound sources. The invention overcomes the defects existing in the prediction of the insertion loss of the existing sound barrier, is applied to the engineering design of the sound barrier of high-speed railways and the impact evaluation of environmental noise, and has the advantages of accurate prediction value and strong engineering practicability.

Description

technical field [0001] The invention belongs to the research field of high-speed railway noise control in the subject of environmental engineering, and relates to a method for predicting noise reduction effects of high-speed railway sound barriers, in particular to a method for predicting insertion loss of high-speed railway sound barriers with five sound source modes, which is suitable for high-speed railways Sound barrier engineering design and environmental noise impact assessment. Background technique [0002] The prediction of insertion loss of sound barrier is an important content in the engineering design of high-speed railway sound barrier. In order to predict the theoretical noise reduction of different heights of noise barriers on noise sensitive points, and to determine the reasonable height of high-speed railway noise barriers, the method proposed in the latest research results at home and abroad divides the high-speed railway sound source into upper and lower pa...

AI Technical Summary

Problems solved by technology

[0003] However, the above methods still have obvious shortcomings when predicting the insertion loss of high-speed railway sound barriers

On the one hand, the actual noise sources of high-speed railways are distributed in a large range from 3m below the rail surface to 5.6m above the rail surface. It is difficult to accurately determine the distribution characteristics of the noise sources only by using the lower and upper equivalent sound sources, and the noise source of the high-speed railway The equivalent frequency and energy ratio are not constants, but are variables related to the train speed. The insertion loss predicted by the existing method is a constant that has nothing to do with the speed of the train, and there is a certain deviation from the measured value, which brings difficulties to engineering design. In some cases, the actual noise reduction effect after installing the sound barrier is lower than the predicted value, and engineering remedial measures are required to make the environmental noise reach the design target value, which passively increases the amount of engineering construction and capital investment; on the other hand, this method can only predict the upper part The insertion loss when the sound source is completely unobstructed by the sound barrier greatly limits its scope of application

Images