Methods to Estimate the Confidence Level of the Experimentally Derived Statistical Energy Analysis Model: Application to Vehicles

1997 ◽  
Author(s):  
L. Hermans ◽  
K. De Langhe ◽  
L. Demeestere
Keyword(s):  
Confidence Level ◽  
Energy Analysis ◽  
Statistical Energy Analysis ◽  
Analysis Model ◽  
Model Application

scholarly journals Statistical Energy Analysis Model for Sound Pressure Level Prediction on Refrigerators

2020 ◽  
Vol 48 (2) ◽  
pp. 233-250
Author(s):  
R. Zárate ◽  
J. Poblet-Puig ◽  
M. Ortega ◽  
M. López-Parra
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Energy Analysis ◽  
Pressure Level ◽  
Statistical Energy Analysis ◽  
Analysis Model

scholarly journals Corrected Statistical Energy Analysis Model in a Non-Reverberant Acoustic Space

2021 ◽  
Vol 55 (3) ◽  
pp. 203-219
Author(s):  
Al Munawir ◽  
Azma Putra ◽  
Iwan Prasetiyo ◽  
Wan Mohd Farid Wan Mohamad ◽  
Safarudin Herawan
Keyword(s):  
Energy Analysis ◽  
Statistical Energy Analysis ◽  
Analysis Model ◽  
Acoustic Space

Structure-Borne Tire Noise Statistical Energy Analysis Model

1997 ◽  
Vol 25 (3) ◽  
pp. 177-186 ◽  
Author(s):  
J. J. Lee ◽  
A. E. Ni
Keyword(s):  
High Frequency ◽  
Energy Analysis ◽  
Frequency Noise ◽  
Statistical Energy Analysis ◽  
Analysis Model ◽  
High Frequency Noise ◽  
Tire Noise ◽  
Modeling Methodology ◽  
Vehicle System ◽  
Good Agreement

Abstract The application of the Statistical Energy Analysis (SEA) technique on vehicle high frequency noise has gained popularity. It is desirable to model the tire to provide the capability of vehicle system NVH prediction. An SEA model for the structure-borne noise has been developed. The point mobility shows good agreement with measurement. The modeling methodology on tread bands, sidewalls, and their coupling are discussed. The modeling requirements and prospects are also included.

Numerical study of acoustic transmission across heavily damped plate using hybrid Ray-Tracing-SEA method

2020 ◽  
pp. 1351010X2093955
Author(s):  
Feng Yan ◽  
Robin Wilson ◽  
Peter Rutherford
Keyword(s):  
Field Theory ◽  
Ray Tracing ◽  
Energy Analysis ◽  
Numerical Study ◽  
Effective Length ◽  
Energy Concentration ◽  
Statistical Energy Analysis ◽  
Analysis Model ◽  
Damped System ◽  
The Difference

Energy transmission across lightly damped structures has been well studied including the approved success of statistical energy analysis in mid and high frequency bands. For heavily damped elements, the diffuse field theory, which is used in computing coupling loss factors, tends to fail. Energy attenuation with distance becomes more significant for such elements and hence the energy is less likely to be evenly distributed within those elements. A ray tracing algorithm is developed taking account of this phenomenon by tracking the travel history of a great number of discrete rays. The predicted transmitted energy is used in a modified statistical energy analysis model to calculate energy level difference between different subsystems. Numerical validation and comparison on a concrete five-plate system are conducted in both lightly damped and heavily damped cases. Both the classic and the hybrid models show good agreement for lightly damped system and differ for heavily damped system. The difference tends to become larger with increasing frequency and internal damping level. The parameter “effective length ratio” is proposed to describe the phenomena of energy concentration along the edge and as in indicator of whether the application of diffuse field theory is appropriate.

A SEA Model for the Noise Analysis and Prediction of a Vacuum Cleaner

2009 ◽  
Author(s):  
Lifang Yang ◽  
Zhiyong Long
Keyword(s):  
Loss Factor ◽  
Energy Analysis ◽  
Noise Analysis ◽  
Input Power ◽  
Statistical Energy Analysis ◽  
Analysis Model ◽  
Vacuum Cleaner ◽  
Prediction And Control ◽  
Noise Vibration ◽  
And Control

As an effective method for middle and high-frequency vibro-acoustics prediction, SEA (Statistical Energy Analysis) has been successfully applied to some areas such as aerospace, ship, and car. In this paper, a statistical energy analysis model is built for studying the noise prediction and control of vacuum cleaner. First the principles for subsystem partition are provided and subsystems and connections of SEA model are completed in AutoSEA software. Then for complex structures, their equivalent parameters are discussed. For different structures, a series of formulae of SEA parameters are provided, such as module density, damping loss factor and coupling loss factor, the input power is obtained by experimental measurement. By comparing the simulated SPL(sound pressure level) with the measured SPL, the correctness of the model is verified. Furthermore, error sources of the model are analyzed. This study can offer guidance and reference on how to carry out noise-vibration study and build up vacuum cleaner SEA model.

scholarly journals Experimental validation of variance estimation in the statistical energy analysis of a structural-acoustic system

2019 ◽  
Vol 233 (18) ◽  
pp. 6448-6459
Author(s):  
Luis Andrade ◽  
Robin S Langley ◽  
Tore Butlin ◽  
Matthew de Brett ◽  
Ole M Nielsen
Keyword(s):  
Experimental Evidence ◽  
Variance Estimation ◽  
Energy Analysis ◽  
Statistical Energy Analysis ◽  
Acoustic System ◽  
Analysis Model ◽  
Vibrating Structures ◽  
Mean And Variance ◽  
The Mean ◽  
Acoustic Cavities

The Statistical Energy Analysis (SEA) approach has largely been used in vibro-acoustic modelling to predict the averaged energy in coupled vibrating structures and acoustic cavities. The average is performed over an ensemble of nominally identical built-up systems where random responses are observed at high frequencies after excitation. Over the years, this approach has been extended to predict the energy variance employing the statistics of the Gaussian Orthogonal Ensemble, and numerical and experimental evidence has supported the predictions of the mean and variance of energy of coupled vibrating structures. However, little experimental evidence is found to validate the prediction of the variance of energy in coupled structural-acoustic systems. In this work, the mean and variance of energies predicted from a statistical energy analysis model have been validated with experimental measurements on a structural-acoustic system, comprised by a flat thin plate coupled to an enclosed acoustic volume. The structural system has been randomised by adding small masses on arbitrary positions on the plate, whereas the randomisation of the acoustic cavity is achieved by allocating rigid baffles in random positions within the acoustic volume. In general, good agreement is found between the predictions of the model and the experimental results.

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