Acoustic Noise Prediction Research Articles

An equivalent and simplified approach for acoustic noise prediction in a PM synchronous motor based on the semi‐analytical‐FEM model

AbstractThe vibration and acoustic noise of a permanent‐magnet synchronous motor are analysed and evaluated. Acoustic noise sound levels, their prominent frequencies, and the noisiest motor speed range are predicted. According to many resources, the radial vibration of the stator system due to the magnetic attraction between rotor permanent magnets and stator iron teeth is the main reason for the acoustic noise propagation of the PMSMs. The dominant orders of the spatial circumferential harmonics of the radial magnetic forces (RMFs) have been investigated and compared. The complete and complicated mechanical components, materials, and harmonics of the magnetic forces of the motor and their interaction are simplified and equalised to a vibration model, which consists of the interaction between the stator system and the dominant harmonic orders of the RMFs. Based on this approach, the simplest and most adequate semi‐analytical‐FEM model for noise prediction in PMSMs is proposed. This model, in addition to simplification, clarifies the role of the main mechanical and electromagnetic origins of noise generation. The acoustic noise prediction, using the proposed method has been compared with the experimental results. There is a proper agreement between the analytical, the FEM, and measurement results.

Acoustic scattering effect prediction of helicopter fuselage based on BEM and convective FW–H equation

The main acoustic noise source of helicopters is supposed to be the rotor blades, but the scattering effect of the helicopter fuselage sometimes cannot be ignored. For the accuracy of acoustic noise prediction and the research on the scattering affections of the helicopter fuselage, an FWH–BEM Method (FBM) based on convective FW–H equation and boundary element method (BEM) is presented for the prediction of the noise scattering effects of helicopter fuselage and the approach to the calculation of a helicopter’s acoustic noise field. In this paper, different fuselage models are adopted for the comparisons of the acoustic noise scattered by different types of fuselages. According to the discovery that helicopter fuselages with sharp edges can bring more significant acoustic scattering effects, a research on the influence of radius of curvature (RC), which reflects the sharpness of fuselage sharp edges, is also carried out. In addition, the acoustic scattering effects of the same type of fuselage but with different length, width and height ratios are also compared for discovering the influences of the fuselage size. The presented FBM is efficient to analyze the acoustic scattering effects of the helicopter fuselage and predict the acoustic noise field, taking both the rotor and the fuselage into account. Besides, the research in this paper leads to the discovery of the influence factors of the acoustic scattering effects and helps the proper selection of the fuselage in a helicopter stealth design.

Prediction of acoustic noise and vibration of a 24/16 traction switched reluctance machine

This study presents a numerical modelling approach for the prediction of vibration and acoustic noise for a 24/16 traction switched reluctance machine (SRM). The numerical modelling includes the simulation of electromagnetic force in JMAG, the calculation of natural frequencies and the simulation of vibration and acoustic noise in ACTRAN. Considerations in the modelling of geometries, meshing and contacts of the 24/16 SRM are discussed to ensure the accuracy of the numerical simulation. Two-dimensional fast Fourier transform (FFT) is applied to the radial nodal force at the stator pole tip to analyse the dominant harmonics. FFT is also applied to the simulated surface displacement of the housing and the sound pressure at 2000 rpm to analyse their dominant frequency components. The dominant harmonics for the vibration and acoustic noise at 2000 rpm are confirmed. The numerical modelling method presented in this study can also be applied to the other SRMs and electric machines to predict the vibration behaviour and the radiated acoustic noise.

Surrogate-Based Acoustic Noise Prediction of Electric Motors

Design and optimization problems typically require running thousands of motor simulations, which could take several hours if not days. Finding alternative means of reducing the solution time has recently gained research interest. Surrogate models can emulate the outputs of computer simulations with less computational effort. This article proposes the use of surrogate models to predict the acoustic noise, applied to an interior permanent-magnet synchronous motor (IPMSM). The simulation procedure involves using finite element analysis (FEA) to evaluate the acoustic performance across a design space of stator and rotor geometric variations. Then, four different classes of surrogate models are used to learn a portion of the design space before attempting to generalize and make predictions in a much larger space with relatively less computational burden. It is demonstrated that the trained models can be considered as appropriate replacements of the time-consuming FEA for future design and optimization problems of the same motor case study.

High-speed switched reluctance machine: natural frequency calculation and acoustic noise prediction

In this study, an analytical model is proposed for natural frequency calculation and acoustic noise prediction for high speed switched reluctance machines. The developed natural frequency model results are compared with the mechanical finite element analysis results in terms of 6 different mode shapes that cause the majority of the acoustic noise in switched reluctance machines. The results show that the analytical results are consistent with the numerical method results with minimum 90% matching. Based on the natural frequency calculation model, a new acoustic noise prediction method is developed that only needs a radial force waveform as an input emerging on stator pole surfaces. The comparison of the developed and the numerical results clearly indicates that the acoustic noise level of the switched reluctance machine can be effectively found during the design process without using time-consuming numerical methods.

GIS Approach for Collaborative Monitoring and Prediction of Environmental Noise in Urban areas

Environmental noise, as well as being a form of environmental pollution that affects mainly urban areas, it is a problem that involves people's quality of life. This paper presents a methodology that takes advantage of the Volunteered Geographic Information (VGI) in obtaining georeferenced environmental noise maps and the corresponding statistics for a particular area of interest. The methodology herein presented considers the phases of Data acquisition, Analysis and data processing, and Visualization of the information. The design and development of a Geographic Information System is presented, which consists of a web mapping application, an application for mobile devices, called NoiseMonitor, Geospatial Analysis and Machine Learning methods (Support Vector Machines and Artificial Neural Networks) for acoustic noise prediction using contextual information, that is, some factors around the measurements. A study case is based on Mexico City.

Prediction of Acoustic Noise in Switched Reluctance Motor Drives

Prediction of acoustic noise distribution generated by electric machines has become an integral part of design and control in noise sensitive applications. This paper presents a fast and precise acoustic noise imaging technique for switched reluctance machines (SRMs). This method is based on distribution of radial vibration in the stator frame of the SRM. Radial vibration of the stator frame, at a network of probing points, is computed using input phase current and phase voltage waveforms. Sequentially, the acceleration of the probing network will be expanded to predict full acceleration on the stator frame surface, using which acoustic noise emission caused by the stator can be calculated using the boundary element method.

Prediction of Acoustic Noise and Torque Pulsation in PM Synchronous Machines With Static Eccentricity and Partial Demagnetization Using Field Reconstruction Method

Permanent magnet synchronous machines (PMSM) are widely used in industrial applications. Partial demagnetization and static eccentricity are among common faults in PMSM. These faults will alter the acoustic behavior and torque pulsation by a significant margin. In this paper, results of a thorough investigation on the impact of these faults on the force distribution, vibration, and acoustic behavior of the PMSM is presented. Our force analysis is based on the field reconstruction method which is a very efficient technique for multi-physics field problems in electromechanical energy converters.

An Efficient Feedback Active Noise Control Algorithm Based on Reduced-Order Linear Predictive Modeling of fMRI Acoustic Noise

Functional magnetic resonance imaging (fMRI) acoustic noise exhibits an almost periodic nature (quasi-periodicity) due to the repetitive nature of currents in the gradient coils. Small changes occur in the waveform in consecutive periods due to the background noise and slow drifts in the electroacoustic transfer functions that map the gradient coil waveforms to the measured acoustic waveforms. The period depends on the number of slices per second, when echo planar imaging (EPI) sequencing is used. Linear predictability of fMRI acoustic noise has a direct effect on the performance of active noise control (ANC) systems targeted to cancel the acoustic noise. It is shown that by incorporating some samples from the previous period, very high linear prediction accuracy can be reached with a very low order predictor. This has direct implications on feedback ANC systems since their performance is governed by the predictability of the acoustic noise to be cancelled. The low complexity linear prediction of fMRI acoustic noise developed in this paper is used to derive an effective and low-cost feedback ANC system.

An overview of the acoustical activities at the National Wind Technology Center.

The National Wind Technology Center (NWTC) has been involved in wind turbine acoustics since the 1980s. The areas of work include standards development, measurement and analysis, prediction code development, and acoustic arrays. Most measurements are conducted to the IEC 61400‐11, a standard specifically for acoustic measurements of wind turbines. The NWTC is involved in the development of this standard. The standard results in reports of overall levels as well as tonality. The NWTC has also developed a semiempirical acoustic noise prediction code for wind turbines. Validation of this code with test data (both wind tunnel and field measurements) shows reasonable prediction accuracy for both airfoil self noise and turbulent inflow noise. Lastly, to assist with wind turbine noise reduction and to identify the loudest components an acoustic array was developed to better locate noise on wind turbines. This paper will describe the NWTC’s past and current activities in wind turbine acoustics including test methods and results.

Prediction of acoustic noise from variable-speed induction motors: deterministic versus statistical approaches

The traditional approach for the prediction of noise radiated from induction motors is usually based on a deterministic approach in which the motor is modeled using finite-element and/or boundary-element methods (FEM/BEM). A great deal of structural details has to be modeled using the deterministic approach. While these deterministic methods have been shown to provide reasonable estimates of the radiated acoustic noise at low frequencies (usually, well below 2 kHz) and for small motors, the demands on computing memory and time render calculations at high frequencies and for large motors almost impossible to make. In this paper, a statistical method especially suited for calculations at high frequencies is introduced. The statistical approach does not require the same amount of details to be modeled as in the FEM/BEM because only the averaged noise within a given frequency band is sought. Furthermore, it utilizes the analytical results obtained from simple structural elements that make up the motor structure. Results demonstrate the feasibility of the method, its ability to discern the contribution of various components of a motor to the overall radiated noise, and substantial savings in the computational effort compared with FEM/BEM.

Radial force calculation and acoustic noise prediction in switched reluctance machines

This paper presents an analytical method for calculating the radial force and predicting the acoustic noise in switched reluctance machines (SRMs). The main source of acoustic noise in an SRM is the radial magnetic force inducing resonant vibration with circumferential mode shapes of the stator. An analytical relationship between radial force and radial vibration is determined, which can be used to predict the noise power level at the frequency of operation. The vibration and sound are functions of machine dimensions, material properties, and rotational speed. The knowledge of the circumferential mode shapes of vibration, the natural mode frequencies of the stator, and the frequency spectrum of the radial magnetic force can be effectively utilized to design SRMs with minimal noise through geometrical design variations. The effect of the number of stator and rotor poles on acoustic noise can also be analyzed with the model presented in this paper. Magnetodynamic simulation by finite-element analysis software has also been carried out to verify the calculation of radial force using the proposed analytical model.