Vol. 58 No. 1 (2024)

Open Access

Article

Article ID: 2641

Sound Transmission Loss of Helmholtz Resonators with Elastic Bottom Plate

by Liang Yang, Jie Zhang, Jinfeng Xia, Siwen Zhang, Yang Yang

Sound & Vibration, Vol.58, No.1, 2024;

Helmholtz resonators are widely used to control low frequency noise propagating in pipes. In this paper, the elastic bottom plate of Helmholtz resonator is simplified as a single degree of freedom (SDOF) vibration system with acoustic excitation, and a one-dimensional lumped-parameter analytical model was developed to accurately characterize the structure-acoustic coupling and sound transmission loss (STL) of a Helmholtz resonator with an elastic bottom plate. The effect of dynamical parameters of elastic bottom plate on STL is analyzed by utilizing the model. A design criterion to circumvent the effect of wall elasticity of Helmholtz resonators is proposed, i.e., the structural natural frequency of the wall should be greater than three times the resonant frequency of the resonator to avoid the adverse effects of wall elasticity. This study can provide guidance for the rapid and effective design of Helmholtz resonators.

Open Access

Article

Article ID: 2642

GestureID: Gesture-Based User Authentication on Smart Devices Using Acoustic Sensing

by Jizhao Liu, Jiang Hui, Zhaofa Wang

Sound & Vibration, Vol.58, No.1, 2024;

User authentication on smart devices is crucial to protecting user privacy and device security. Due to the development of emerging attacks, existing physiological feature-based authentication methods, such as fingerprint, iris, and face recognition are vulnerable to forgery and attacks. In this paper, GestureID, a system that utilizes acoustic sensing technology to distinguish hand features among users, is proposed. It involves using a speaker to send acoustic signals and a microphone to receive the echoes affected by the reflection of the hand movements of the users. To ensure system accuracy and effectively distinguish users’ gestures, a second-order differential-based phase extraction method is proposed. This method calculates the gradient of received signals to separate the effects of the user’s hand movements on the transmitted signal from the background noise. Then, the second-order differential phase and phase-dependent acceleration information are used as inputs to a Convolutional Neural Networks-Bidirectional Long Short-Term Memory (CNN-BiLSTM) model to model hand motion features. To decrease the time it takes to collect data for new user registration, a transfer learning method is used. This involves creating a user authentication model by utilizing a pre-trained gesture recognition model. As a result, accurate user authentication can be achieved without requiring extensive amounts of training data. Experiments demonstrate that GestureID can achieve 97.8% gesture recognition accuracy and 96.3% user authentication accuracy.

Open Access

Article

Article ID: 2643

Computational Verification of Low-Frequency Broadband Noise from Wind Turbine Blades Using Semi-Empirical Methods

by Vasishta BhargavaNukala, Chinmaya PrasadPadhy

Sound & Vibration, Vol.58, No.1, 2024;

A significant aerodynamic noise from wind turbines arises when the rotating blades interact with turbulent flows. Though the trailing edge of the blade is an important source of noise at high frequencies, the present work deals with the influence of turbulence distortion on leading edge noise from wind turbine blades which becomes significant in low-frequency regions. Four quasi-empirical methods are studied to verify the accuracy of turbulent inflow noise predicted at low frequencies for a 2 MW horizontal axis wind turbine. Results have shown that all methods exhibited a downward linear trend in noise spectra for a given mean wind speed except at very low frequencies. With an increase in turbulence intensity from 6% to 14%, the sound power was found to increase almost linearly, and the standard error for sound power was reduced for all methods studied. The computed results were validated and agreed well with experiment noise data from Siemens SWT-2.3MW 93 wind turbine.

Open Access

Article

Article ID: 2644

Analysis of the Relationships between Noise Exposure and Stress/Arousal Mood at Different Levels of Workload

by Rohollah FallahMadvari, Hamideh Bidel, Ahmad Mehri, Fatema Babaee, Fereydoon Laal

Sound & Vibration, Vol.58, No.1, 2024;

Noise is one of the environmental factors with mental and physical effects. The workload is also the multiple mental and physical demands of the task. Therefore, his study investigated the relationship between noise exposure and mood states at different levels of workload. The study recruited 50 workers from the manufacturing sector (blue-collar workers) as the exposed group and 50 workers from the office sector (white-collar workers) as the control group. Their occupational noise exposure was measured by dosimetry. The Stress-Arousal Checklist (SACL) and the NASA Task Load Index (NASA-TLX) were used to measure mood and workload, respectively. The equivalent noise exposure level of the exposed group at high and very high workload levels was 85 and 87 dBA, respectively. The mean mood score of the exposed group was 76 at very high workload. The correlation coefficient between noise exposure level and mood state based on workload levels ranged from 0.3 at medium workload to 0.57 at very high workload. Noise exposure at high workload levels can increase its adverse effects, so controlling and optimizing the multiple demands of the task in the workplace can be used as a privative measure to reduce the adverse effects of noise.

Open Access

Article

Article ID: 2645

Numerical Study of the Effect of Splitter Blades on the Flow-Induced Noise of Hydraulic Turbine

by Fengxia Shi, Guangbiao Zhao, Yucai Tang, Haonan Zhan, Pengcheng Wang

Sound & Vibration, Vol.58, No.1, 2024;

In order to study the effect of splitter blades on the internal and external sound field of the hydraulic turbine, the paper chose a centrifugal pump with a specific speed ns = 33 reversed as a hydraulic turbine as the research object, and added the short blades on the original impeller to form a new splitter impeller. Based on the Re-Normalization Group (RNG) k-ε turbulence model to conduct numerical simulation for the hydraulic turbine, this thesis calculated the internal and external acoustic field by means of the acoustic boundary element (BEM) and finite element (FEM) and analyzed the noise radiation characteristics of the two models under different working conditions. The results show that the blade frequency is the main factor affecting the inlet and outlet sound pressure, and the optimized model decreases the inlet and outlet sound pressure levels by 6.84 and 7.24 dB in optimal working conditions. Rotor-stator interaction is the main reason for the flow-induced noise of hydraulic turbine volute appearing, the optimized model can effectively reduce the impeller and volute rotor-stator interaction and the flow-induced noise of volute. Outfield maximum sound pressure appears at the inlet and the volute tongue, which decreased by 1.84, 6.07, and 5.24 dB at each operating condition. To sum up, splitter blades can improve hydraulic characteristics and flow field noise in the hydraulic turbine.

Open Access

Article

Article ID: 2646

Enhancing Sound Absorption in Micro-Perforated Panel and Porous Material Composite in Low Frequencies: A Numerical Study Using FEM

by Mohammad JavadSheikhMozafari

Sound & Vibration, Vol.58, No.1, 2024;

Mitigating low-frequency noise poses a significant challenge for acoustic engineers, due to their long wavelength, with conventional porous sound absorbers showing limitations in attenuating such noise. An effective strategy involves combining porous materials with micro-perforated plates (MPP) to address this issue. Given the significant impact of structural variables like panel thickness, hole diameter, and air gap on the acoustic characteristics of MPP, achieving the optimal condition demands numerous sample iterations. The impedance tube’s considerable expense for sound absorption measurement and the substantial cost involved in fabricating each sample using a 3D printer underscore the advantage of utilizing simulation methods to attain the optimal state. This study focuses on optimizing low-frequency enhancement by investigating key parameters. Using the Finite Element Numerical Method (FEM) in COMSOL software, a composite panel was constructed comprising date palm fiber layers, an intervening air layer, and MPP. The study explored the arrangement of these layers and the impact of parameters like hole diameter, plate thickness, and perforation ratio on acoustic behavior. The selected optimal parameter at each stage was consistently maintained for subsequent steps. Results revealed that layer arrangement significantly influenced acoustic characteristics. Placing the MPP layer before the porous material yielded superior low-frequency performance. Optimizing low-frequency behavior involved reducing hole diameter and perforation ratio while increasing plate thickness. Elevating the porous material’s thickness relative to the air layer behind the MPP enhanced absorption peak and resonance frequency. In conclusion, halving the porous layer’s thickness while incorporating an air layer and single MPP proved more effective than using a thick porous material. This approach not only reduces costs and space requirements but also enhances low-frequency performance. The study highlights the precision of numerical methods like FEM, reducing the need for resource-intensive direct methods and associated laboratory expenses.

Open Access

Article

Article ID: 2647

Prediction and Analysis of Vehicle Interior Road Noise Based on Mechanism and Data Series Modeling

by Jian Pang, Tingting Mao, Wenyu Jia, Xiaoli Jia, Peisong Dai, Haibo Huang

Sound & Vibration, Vol.58, No.1, 2024;

Currently, the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise. Consequently, an in-depth investigation into automobile road noise holds substantial practical importance. Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models. While mechanism models offer robust controllability, their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling, and the effective utilization of accumulated data remains elusive. In contrast, data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge, but they impose stringent requirements on both data quality and quantity. In response to these considerations, this paper introduces an innovative approach for predicting vehicle road noise by integrating mechanism-driven and data-driven methodologies. Specifically, a series model is devised, amalgamating mechanism analysis with data-driven techniques to predict vehicle interior noise. The simulation results from dynamic models serve as inputs to the data-driven model, ultimately generating outputs through the utilization of the Long Short-Term Memory with Autoencoder (AE-LSTM) architecture. The study subsequently undertakes a comparative analysis between different dynamic models and data-driven models, thereby validating the efficacy of the proposed series vehicle road noise prediction model. This series model, encapsulating the rigid-flexible coupling dynamic model and AE-LSTM series model, not only demonstrates heightened computational efficiency but also attains superior prediction accuracy.

Open Access

Article

Article ID: 2648

A Sound Quality Evaluation Method for Vehicle Interior Noise Based on Auditory Loudness Model

by Zhiheng He, Hui Guo, Houguang Liu, Yu Zhao, Zipeng Zhang, Shanguo Yang

Sound & Vibration, Vol.58, No.1, 2024;

When designing and optimizing the hull of vehicles, their sound quality needs to be considered, which greatly depends on the psychoacoustic parameters. However, the traditional psychoacoustic calculation method does not consider the influence of the real human ear anatomic structure, even the loudness which is most related to the auditory periphery. In order to introduce the real physiological structure of the human ear into the evaluation of vehicle sound quality, this paper first carried out the vehicle internal noise test to obtain the experimental samples. Then, the physiological loudness was predicted based on an established human ear physiological model, and the noise evaluation vector was constructed by combining the remaining four psychoacoustic parameters. Finally, the evaluation vector was fitted into the subjective evaluation results of vehicle interior noise by a deep neural network. The results show that our proposed method can estimate the human subjective perception of vehicle interior noise well.

Open Access

Article

Article ID: 2649

Prediction of Sound Transmission Loss of Vehicle Floor System Based on 1D-Convolutional Neural Networks

by Cheng Peng, Siwei Cheng, Min Sun, Chao Ren, Jun Song, Haibo Huang

Sound & Vibration, Vol.58, No.1, 2024;

The Noise, Vibration, and Harshness (NVH) experience during driving is significantly influenced by the sound insulation performance of the car floor acoustic package. As such, accurate and efficient predictions of its sound insulation performance are crucial for optimizing related noise reduction designs. However, the complex acoustic transmission mechanisms and difficulties in characterizing the sound absorption and insulation properties of the floor acoustic package pose significant challenges to traditional Computer-Aided Engineering (CAE) methods, leading to low modeling efficiency and prediction accuracy. To address these limitations, a hierarchical multi-objective decomposition system for predicting the sound insulation performance of the floor acoustic package has been developed based on an analysis of the noise transmission path. This approach involves introducing a 1D-Convolutional Neural Network (1D-CNN) model for predicting the sound insulation performance of the floor acoustic package, thereby avoiding the limitations of conventional CAE approaches that rely solely on “data-driven” methods. The proposed method was applied and tested using specific vehicle models, and the results demonstrated the effectiveness and superiority of the proposed approach relative to those obtained using 2D-CNN and Support Vector Regression (SVR) models.

Open Access

Article

Article ID: 2650

Soundscapes in Arab Cities: A Systematic Review and Research Agenda

by Tallal Bouzir, Djihed Berkouk, Theodore S.Eisenman, Dietrich Schwela, Nader Azab, Mohammed M.Gomma, Samiha Boucherit

Sound & Vibration, Vol.58, No.1, 2024;

In the context of Arab cities, this study explores the intricate interplay between cultural, historical, and environmental elements that shape their unique soundscapes. The paper aims to shed light on this underrepresented field of study by employing a three-fold research approach: systematic review, a comprehensive literature review, and the formulation of a future research agenda. The first part of the investigation focuses on research productivity in the Arab world regarding soundscape studies. An analysis of publication trends reveals that soundscape research in Arab cities is still an emerging area of interest. Critical gaps in the existing body of literature are identified, highlighting the importance of addressing these gaps within the broader context of global soundscape research. The second part of the study delves into the distinctive features that inform the soundscapes of Arab cities. These features are categorized into three overarching groups: (i) cultural and religious life, (ii) daily life, and (iii) heritage and history, by exploring these factors, the study aims to elucidate the multifaceted nature of Arab urban soundscapes. From the resonating calls to prayer and the vibrant ambiance of traditional cafes to the bustling markets and architectural characteristics, each factor contributes to the auditory tapestry that defines Arab cities. The paper concludes with a forward-looking research agenda, proposing sixteen key questions organized into descriptive and comparative categories. These questions emphasize the need for a more profound understanding of sound perception, sources, and the impact of urban morphology on the soundscape. Additionally, they highlight the need for interdisciplinary research, involving fields such as urban planning, architecture, psychology, sociology, and cultural studies to unravel the complexity of Arab urban soundscapes.