To better solve the complex non-linear problem between the subjective sound quality evaluation results and objective psychoacoustics parameters, a method for the prediction of the sound quality is put forward by using a back propagation neural network (BPNN) based on particle swarm optimization (PSO), which is optimizing the initial weights and thresholds of BP network neurons through the PSO. In order to verify the effectiveness and accuracy of this approach, the noise signals of the B-Class vehicles from the idle speed to 120 km h−1 measured by the artificial head, are taken as a target. In addition, this paper describes a subjective evaluation experiment on the sound quality annoyance inside the vehicles through a grade evaluation method, by which the annoyance of each sample is obtained. With the use of Artemis software, the main objective psychoacoustic parameters of each noise sample are calculated. These parameters include loudness, sharpness, roughness, fluctuation, tonality, articulation index (AI) and A-weighted sound pressure level. Furthermore, three evaluation models with the same artificial neural network (ANN) structure are built: the standard BPNN model, the genetic algorithm-back-propagation neural network (GA-BPNN) model and the PSO-back-propagation neural network (PSO-BPNN) model. After the network training and the evaluation prediction on the three models' network based on experimental data, it proves that the PSO-BPNN method can achieve convergence more quickly and improve the prediction accuracy of sound quality, which can further lay a foundation for the control of the sound quality inside vehicles.

https://iopscience.iop.org/article/10.1088/0957-0233/27/1/015801/pdf

Sound quality prediction of vehicle interior noise and mathematical modeling using a back propagation neural network (BPNN) based on particle swarm optimization (PSO)

Intelligent evaluation of the interior sound quality of electric vehicles

In subjective sound quality pair-wise comparison evaluation, test time grows with square of the number of sound stimulus. For this reason, subjective evaluation of large quantity of stimulus is difficult to carry out with pair-wise comparison method. A grouped pair-wise comparison (GPC) method is proposed to greatly decrease time and difficult of subjective comparison test, in which stimuli in the whole evaluation corpus are divided into N test groups, with reference-link stimuli configured in each group. Derived from subjective results of each group, final results of all stimuli are reconstructed, and their perceptual attributes of sound quality can be analyzed. With car interior noise as example, realization of subjective sound quality evaluation with GPC method is introduced. The results of GPC evaluation are in good agreement with those obtained from paired comparison and semantic differential methods.

Grouped pair-wise comparison for subjective sound quality evaluation

In the process of vehicle interior sound quality research, the subjective assessment usually requires a lot of manpower, time and material resources. It is necessary to choose appropriate objective...

Vehicle Interior Sound Quality Evaluation Index Selection Scheme Based on Grey Relational Analysis

The track vertical profile irregularity is regarded as stationary ergodic Gaussian random processes.The vertical radom vibration of vehicle and track is computed on the basis of vehicle/track coupling dynamic FEM model.The analysis of system response is made in the time and frequency field.

An Analysis of Random Vibration of Vehicle/Trach Coupling System

This experiment collected sound signals of four different cars driving at different speeds on highway and replayed the noise samples with playback software HEAD Audio Recorder. The subjective evaluation tests were carried out with paired comparison method. Evaluating models between subjective evaluation and objective psychoacoustic parameters were established with SPSS analysis software.

Research on Subjective and Objective Evaluation of Car Interior Sound Quality

The interior noise samples from four cars at different positions and different speeds were selected as the evaluation objects. The subjective evaluation test of sound quality preference was carried out with paired comparison method. Several objective psycho-acoustical parameters of these samples were calculated. By way of linear correlation and multi-dimensional regression analysis, an equation between the subjective evaluation of noise preference and the objective psycho-acoustical parameters was established. The results indicate that the vehicle interior sound quality preference under the good highway and the constant-velocity driving conditions is affected mainly by two psycho-acoustical parameters Loudness and Sharpness.

Subjective Analysis and Objective Evaluation of Vehicle Sound Quality

According to the complexity and non-linear characteristics of car interior sound quality evaluation, the technology of BP neural network is used in sound quality evaluation. The interior noise samples from actual cars were obtained by road experiment. The subjective evaluation test of sound quality annoyance was carried out. Meanwhile, several objective psycho-acoustical parameters of these samples were calculated. The sound quality prediction model of vehicle interior noise was established based on BP neural network. Annoyance of samples was obtained by means of the prediction model and the results were compared with that obtained by multiple liner regression prediction model. The results indicate that the prediction results from BP neural network model were close to the measured values. The BP neural network model was more effective than multiple liner regression model, and it can be used effectively to the evaluation of modern car noise.

Sound Quality Evaluation Control of Car Interior Noise

The noise level in a tractor cab directly affects the driving experience. Reducing the noise level in a tractor cab is an important means of improving the image of the product brand and protecting the physical and psychological health of employees. To reduce medium- and low-frequency noise in a tractor cab, the influence of the installation of coupled resonance acoustic materials (CRAMs) on tractor driver ear noise is investigated in this study. Theories for sound absorption by perforated plates and sound insulation by thin membranes are used to design a CRAM composed of a perforated plate, elastic membrane and additional mass. The acoustic impedance and sound absorption coefficient of the CRAM are obtained by an equivalent circuit method, and the resonance frequency of a local resonance system composed of an elastic membrane and additional mass is calculated. The effects of different hole diameters and porosities of the perforated plate on the CRAM sound absorption coefficient are compared. The results of tests performed using impedance tubes over a wide frequency range of 50 Hz~1600 Hz show that the maximum sound absorption coefficient is 0.99 and several transmission loss peaks of 15 dB~26 dB. Measurement of the acoustic response of the CRAM installed on the cab front panel shows that an ear noise reduction of approximately 1.3 dB(A) for a tractor working speed of 2200 rpm. The results show that the designed CRAM has a relatively good effect on reducing driver ear noise over a wide frequency band and is a feasible scheme for noise reduction in a tractor cab.

Noise Reduction in Tractor Cabs Using Coupled Resonance Acoustic Materials

During long-term continuous braking, high-intensity braking, or frequent braking, the temperature of the brake disc or brake drum will increase significantly, resulting in a decrease in the friction coefficient, the aggravation of the wear degree, and the dangerous heat recession of partial or even total loss of braking efficiency. This paper focuses on an innovative double rotor permanent magnet braking device, which is located on the inner side of the wheel hub, to improve the heat decay resistance of the friction braking device. The structure and principle of the double rotor permanent magnet braking device were given, and its main structural parameters were designed, calculated, and optimized. The geometric model and finite element model of the double rotor permanent magnet braking device were established. The static and transient magnetic field analysis and the braking torque characteristic analysis of the double rotor permanent magnet braking device were carried out by using Maxwell electromagnetic analysis software. The results show that the magnetic flux density in the working area of the double rotor permanent magnet braking device increases with the increase in rotation speed, the braking torque changes with the change of rotation speed, and the maximum braking torque occurs in the low-speed area, which is consistent with the theoretical calculation results. This provides a theoretical basis for the follow-up prototype test of the double rotor permanent magnet braking device.

/pdf/the-design-and-magnetic-field-analysis-of-a-double-rotor-qsbjlxm7.pdf

The Design and Magnetic Field Analysis of a Double Rotor Permanent Magnet Braking Device

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