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.

Prediction of Transient Vibration Envelopes Using Statistical Energy Analysis Techniques

1990 ◽  
Vol 112 (1) ◽  
pp. 127-137 ◽  
Author(s):  
M. L. Lai ◽  
A. Soom
Keyword(s):  
Loss Factor ◽  
Energy Analysis ◽  
A Priori ◽  
Coupled Systems ◽  
Time Varying ◽  
Statistical Energy Analysis ◽  
Coupling Loss ◽  
Transient Vibration ◽  
Coupled Plates ◽  
Coupling Loss Factor

The prediction, by the statistical energy analysis (SEA) method, of transient vibration envelopes for coupled systems is investigated. The relation between the time-varying energy transferred between two coupled subsystems and time-varying energies of the subsystems is studied numerically and experimentally. These studies indicate that time-varying energy transmitted between two subsystems is related to the subsystem energies by an apparent time-varying coupling loss factor. It is shown that the apparent coupling loss factor approaches the asymptotic (or steady-state) coupling loss factor as response energies and transferred energies are integrated over progressively larger times. Both the apparent time-varying coupling loss factor and the asymptotic coupling loss factor, determined experimentally, are used in energy balance equations to predict the time-varying vibration envelopes of a system of two point-coupled plates and the results are compared. Although overall response predictions are similar, considerable differences are noted in individual frequency bands. However, no general method for a priori determination of the apparent time-varying coupling loss factor is suggested.

Probability Distribution of Statistical Energy Analysis Model Responses Due to Parameter Randomness

1998 ◽  
Vol 120 (3) ◽  
pp. 641-647 ◽  
Author(s):  
X. L. Huang ◽  
C. J. Radcliffe
Keyword(s):  
Probability Distribution ◽  
Energy Analysis ◽  
Hypothesis Test ◽  
Noise Analysis ◽  
Response Probability ◽  
Statistical Hypothesis ◽  
Design Parameters ◽  
Physical Parameters ◽  
Frequency Noise ◽  
Statistical Energy Analysis

The Statistical Energy Analysis (SEA) methodology has been widely used in aerospace, ship and automotive industry for high frequency noise analysis and acoustic designs. SEA models are treated here as baseline representations of a population of models for systems such as automotive vehicles. SEA responses from the population of all possible models for a vehicle have a random distribution because of the unavoidable uncertainty in the physical parameters due to fabrication imperfection, manufacturing and assembly variations. The random characteristics of the SEA responses can be described by the response probability distribution. In this work, SEA energy response probability distributions due to parameter randomness in a small neighborhood of nominal design values in frequency bands are proven through the Central Limit Theorem to be Gaussian for infinite number of design parameters. Mean squared sound pressure and velocity are directly proportional to SEA energy responses, their distributions are also shown to be Gaussian. In engineering applications, the number of design parameters is always finite for any SEA models. A Monte Carlo test and Statistical Hypothesis test on a simple 3-element SEA model show that the theoretical, infinite order, Gaussian distributions are good approximations for response distributions of a finite parameter SEA model.

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

Application of Statistical Energy Analysis for Damage Detection in Spacecraft Structures

2005 ◽  
Vol 293-294 ◽  
pp. 525-532 ◽  
Author(s):  
J. López-Díez ◽  
M. Torrealba ◽  
A. Güemes ◽  
C. Cuerno-Rejado
Keyword(s):  
Damage Detection ◽  
Loss Factor ◽  
Energy Analysis ◽  
Stiffened Panel ◽  
Statistical Energy Analysis ◽  
Coupling Loss ◽  
System Characteristics ◽  
Coupling Loss Factor

This paper analyses the applicability of the Statistical Energy Analysis (SEA) for detecting incipient damages in a typical spacecraft structure, as a stiffened panel. The damage on attachment element is investigated by analyzing its influence on the system characteristics. Because of incipient damage affects mainly on highest modes, rather than on lowest, the coupling loss factor between sub-elements can be used to detect and localize the damage.

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