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Rapid prediction method and system for exterior noise of high-speed train

A technology for high-speed trains and prediction methods, which can be applied to measurement devices, ultrasonic/sonic/infrasonic measurements, special data processing applications, etc., and can solve problems such as difficulty in satisfying high-speed train acoustic optimization.

Active Publication Date: 2019-02-01
CENT SOUTH UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a fast prediction method and system for high-speed train external noise, which is used to solve the problem that existing experimental methods and simulation technologies are difficult to meet the requirements of high-speed train acoustics. Optimizing Technical Issues

Method used

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  • Rapid prediction method and system for exterior noise of high-speed train
  • Rapid prediction method and system for exterior noise of high-speed train
  • Rapid prediction method and system for exterior noise of high-speed train

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Experimental program
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Embodiment 1

[0043] The fast prediction method of the high-speed train exterior noise of the present embodiment comprises the following steps:

[0044] S1: When the train is running at a constant speed, the bogie area, the pantograph area, the windshield area and the head area are the most important external radiation noise sources, so the surface of the high-speed train is divided into multiple areas. In this embodiment, Divide into bogie, pantograph, front and windshield, simplify the sound sources in different areas into compact point sound sources, calculate the radiated sound pressure level of each compact point sound source, and establish multiple compact point sound sources The energy superposition model of the radiated sound pressure level.

[0045] The compact point sound source is calculated by the sound radiation formula of the free-field linear motion point source, and the calculation formula of the radiated sound pressure of each compact point sound source is as follows:

[0...

Embodiment 2

[0058] This embodiment is an application example of Embodiment 1. The steps of the rapid prediction method of high-speed train exterior noise in this embodiment are basically the same as those in Embodiment 1, the only difference being:

[0059] In this embodiment, in step S2, according to the marshalling and actual size data of the high-speed train, when the real vehicle sound source imaging test is carried out, the test train adopts a 6-car marshalling, and the 66-channel standard spoke-type phased acoustic array of the Danish B&K company is used for the test. , the array diameter is 4.0m. The center of the array is 19.0m away from the center of the track, the center of the array is 3.5m above the track surface, and the single measurement time is set to 8s.

[0060] S201: spectrum analysis.

[0061] The beamforming algorithm is used to obtain the initial sound source image, and then the NNLS (non-negative least square method) technology is used to clear the initial sound so...

Embodiment 3

[0102] This embodiment provides a computer system, including a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, the steps in any of the foregoing embodiments are implemented.

[0103] In summary, the present invention can more accurately predict the far-field radiation noise outside the CRH380AM train under different formations and different speed levels, and the prediction accuracy increases with the increase of the vehicle speed.

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Abstract

The invention discloses a fast prediction method and a system for external noise of a high-speed train, The method comprises the following steps: dividing the surface of a high-speed train into a plurality of regions, simplifying the sound sources in different regions into compact point sound sources, calculating the radiation sound pressure level of each compact point sound source, and establishing an energy superposition model of radiation sound pressure levels of a plurality of compact point sound sources; According to the marshalling and actual size data of the high-speed train, the real vehicle sound source imaging test is carried out, and the noise curves of each compact point sound source under different speed levels are obtained. According to the noise curves of each compact pointsource, the spectral patterns of multiple compact point sources are fitted, and the noise spectral pattern fitting coefficients of different regions at different velocity levels are obtained. According to the fitting coefficients and the energy superposition model, the radiated noise of the high-speed train at different speed levels and the whole vehicle at the distance from the track is calculated. The present invention provides a quick assessment of the impact on the overall noise characteristics.

Description

technical field [0001] The invention relates to the technical field of high-speed trains, in particular to a fast prediction method and system for high-speed train exterior noise. Background technique [0002] The noise problem caused by high-speed railways is becoming more and more serious. A large number of actual vehicle test data show that the internal and external noise of China's CRH series high-speed trains is difficult to meet the European Union's railway noise standards (Chinese standards also quote or refer to this standard), which directly affects the direction of China's high-speed trains. In the world, the comprehensive management of noise needs to be solved urgently. China's high-speed train technology started relatively late, and the independent research and development of standard EMUs did not last long, lacking top-level design experience in acoustic optimization. When integrating noise suppression technology into the design stage and solving the problems t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G01H17/00
CPCG01H17/00G06F30/20Y02T90/00
Inventor 杨志刚谭晓明吴晓龙高建勇
Owner CENT SOUTH UNIV
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