Applied Acoustics最新文献

英文中文

A zero-shot model for diagnosing unknown composite faults in train bearings based on label feature vector generated fault features

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-02-03 DOI: 10.1016/j.apacoust.2025.110563

Deqiang He , Yuan Xu , Zhenzhen Jin , Qi Liu , Ming Zhao , Yanjun Chen

The composite faults in train traction motor bearings are diverse and often unknown. Current approaches heavily rely on extensive training datasets to guarantee the dependability of diagnostic outcomes. However, obtaining training samples of unknown composite faults in train bearings under real-world conditions is challenging. To tackle this problem, this study introduces a zero-shot diagnostic framework that utilizes acoustic signals captured by voiceprint sensors for diagnosing unknown composite faults. The approach builds upon a model that generates fault features from label feature vectors (LFV), enabling the diagnosis of unknown composite faults based on knowledge of single faults. First, a feature extraction approach using a spatially enhanced convolutional neural network is designed, introducing a spatial attention mechanism to strengthen the model’s attention to critical aspects of the features. Subsequently, a definition method for LFV is established to map the relationship between the extracted features and the LFV. A Wasserstein-generating adversarial network with a second-order dynamic gradient penalty is then proposed to generate virtual features based on the LFV. The designed second-order dynamic gradient penalty function helps the model explore the parameter space more efficiently and find the optimal solution, reducing the discrepancy between generated and real features. Finally, two independent acoustic datasets verified the model’s robustness. Without training on composite fault data, the model achieved a classification accuracy of 69.84% for four types of unknown composite faults in bearings, surpassing other methods for bearing composite fault diagnosis.

{"title":"A zero-shot model for diagnosing unknown composite faults in train bearings based on label feature vector generated fault features","authors":"Deqiang He , Yuan Xu , Zhenzhen Jin , Qi Liu , Ming Zhao , Yanjun Chen","doi":"10.1016/j.apacoust.2025.110563","DOIUrl":"10.1016/j.apacoust.2025.110563","url":null,"abstract":"<div><div>The composite faults in train traction motor bearings are diverse and often unknown. Current approaches heavily rely on extensive training datasets to guarantee the dependability of diagnostic outcomes. However, obtaining training samples of unknown composite faults in train bearings under real-world conditions is challenging. To tackle this problem, this study introduces a zero-shot diagnostic framework that utilizes acoustic signals captured by voiceprint sensors for diagnosing unknown composite faults. The approach builds upon a model that generates fault features from label feature vectors (LFV), enabling the diagnosis of unknown composite faults based on knowledge of single faults. First, a feature extraction approach using a spatially enhanced convolutional neural network is designed, introducing a spatial attention mechanism to strengthen the model’s attention to critical aspects of the features. Subsequently, a definition method for LFV is established to map the relationship between the extracted features and the LFV. A Wasserstein-generating adversarial network with a second-order dynamic gradient penalty is then proposed to generate virtual features based on the LFV. The designed second-order dynamic gradient penalty function helps the model explore the parameter space more efficiently and find the optimal solution, reducing the discrepancy between generated and real features. Finally, two independent acoustic datasets verified the model’s robustness. Without training on composite fault data, the model achieved a classification accuracy of 69.84% for four types of unknown composite faults in bearings, surpassing other methods for bearing composite fault diagnosis.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"232 ","pages":"Article 110563"},"PeriodicalIF":3.4,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143261699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on jet control and noise reduction mechanism of sound source for leading bogie region

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-02-03 DOI: 10.1016/j.apacoust.2025.110567

Li Zhuo-ming , Li Qi-liang , Yang Zhi-gang

In order to achieve sound source reduction in the leading bogie region, turbulent flow and near-filed acoustic pressure were solved based on large eddy simulation and acoustic perturbation equations. The noise control effectiveness of the jet control was confirmed through 1:5 scale high-speed trains model wind tunnel test and the numerical simulation method was validated. The effect of jet control at different positions, velocities and directions were evaluated. Notably, the Bogie-Jet-0.35 V scheme, which involves applying a jet flow at 0.35 times the incoming flow velocity at the leading edge of the bogie, exhibited superior control performance. Compared to the base condition, the optimal scheme achieved optimized control of acoustic and turbulent pressures, resulting in reductions of 2.0 dB and 2.7 dB, respectively. An improved reduced order method based on sample entropy was developed to explore the jet control mechanism. It was found that in the snapshots with high acoustic energy, the acoustic energy was primarily concentrated at the front and rear edges of the bogie. Jet flow reduced the turbulent pressure fluctuation energy near the front wheelset of the bogie. Additionally, jet flow reduced the probability of unsteady flow state transitioning to clusters with high acoustic pressure.

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引用次数: 0

Broaden noise reduction range in low frequency by a HR + MPP structure based on impedance matching method

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-02-01 DOI: 10.1016/j.apacoust.2025.110572

Hanbo Shao, Weiyu Chen, Dong Jiang

Broadening the noise reduction range in low frequency has always been an important problem in the research of acoustic metamaterials. Traditional muffler like Helmholtz resonance cavities (HR) only have high absorption coefficient in its resonant frequency. By designing multi-layer or gradient air cavities, the range of frequency broadened is still limited. As is well known, microperforated plate (MPP) has a wide sound absorption frequency in the middle and low frequency. Taking advantage of the physical property of HR and MPP structure, we designed a composite structure by the method of surface impedance matching. Based on the noise reduction coefficient higher than 0.9, this structure realized a 967 Hz width noise reduction in the frequency below 1000 Hz. More than twice as the multi cavity HR structure we researched before. It is demonstrated that, by the impedance matching method, there is almost no reflection in the contact surface between HR and MPP. Therefore, the low resonant frequency and relatively medium frequency can be well absorbed in HR and MPP structures respectively.

{"title":"Broaden noise reduction range in low frequency by a HR + MPP structure based on impedance matching method","authors":"Hanbo Shao, Weiyu Chen, Dong Jiang","doi":"10.1016/j.apacoust.2025.110572","DOIUrl":"10.1016/j.apacoust.2025.110572","url":null,"abstract":"<div><div>Broadening the noise reduction range in low frequency has always been an important problem in the research of acoustic metamaterials. Traditional muffler like Helmholtz resonance cavities (HR) only have high absorption coefficient in its resonant frequency. By designing multi-layer or gradient air cavities, the range of frequency broadened is still limited. As is well known, microperforated plate (MPP) has a wide sound absorption frequency in the middle and low frequency. Taking advantage of the physical property of HR and MPP structure, we designed a composite structure by the method of surface impedance matching. Based on the noise reduction coefficient higher than 0.9, this structure realized a 967 Hz width noise reduction in the frequency below 1000 Hz. More than twice as the multi cavity HR structure we researched before. It is demonstrated that, by the impedance matching method, there is almost no reflection in the contact surface between HR and MPP. Therefore, the low resonant frequency and relatively medium frequency can be well absorbed in HR and MPP structures respectively.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"232 ","pages":"Article 110572"},"PeriodicalIF":3.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143261704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the effect of construction noise frequency on mental workload of construction workers with varying task difficulty using EEG data

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-02-01 DOI: 10.1016/j.apacoust.2025.110571

Samuel Oluwadamilare Olatunbosun , Francis Xavier Duorinaah , Chan-Hoon Haan , Chang-Yong Yi , Min-Koo Kim

Noise pollution is a critical concern on construction sites because it adversely affects the cognitive performance of workers. While prior research has explored the effect of construction noise on workers’ cognitive performance, gaps remain in understanding how these effects change under varying task difficulty and noise frequency. To address this limitation, this study investigates the combined effects of construction noise frequency and task difficulty on mental workload using EEG. To this end, a 3-level N-back memory task was conducted under three noise conditions while EEG data of participants was recorded simultaneously. Furthermore, behavioral and subjective data were collected. This study found that low-frequency noise has a more negative impact on mental workload. The frontal and left occipital-parietal brain regions show more responses to changes in mental workload. This study is expected to help in the development of mental workload assessment models and construction noise regulations for safety interventions.

{"title":"Assessing the effect of construction noise frequency on mental workload of construction workers with varying task difficulty using EEG data","authors":"Samuel Oluwadamilare Olatunbosun , Francis Xavier Duorinaah , Chan-Hoon Haan , Chang-Yong Yi , Min-Koo Kim","doi":"10.1016/j.apacoust.2025.110571","DOIUrl":"10.1016/j.apacoust.2025.110571","url":null,"abstract":"<div><div>Noise pollution is a critical concern on construction sites because it adversely affects the cognitive performance of workers. While prior research has explored the effect of construction noise on workers’ cognitive performance, gaps remain in understanding how these effects change under varying task difficulty and noise frequency. To address this limitation, this study investigates the combined effects of construction noise frequency and task difficulty on mental workload using EEG. To this end, a 3-level N-back memory task was conducted under three noise conditions while EEG data of participants was recorded simultaneously. Furthermore, behavioral and subjective data were collected. This study found that low-frequency noise has a more negative impact on mental workload. The frontal and left occipital-parietal brain regions show more responses to changes in mental workload. This study is expected to help in the development of mental workload assessment models and construction noise regulations for safety interventions.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"232 ","pages":"Article 110571"},"PeriodicalIF":3.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143261700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Acoustic eigenvalue estimation using Rayleigh quotient iteration with a sparse matrix pencil

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-01-31 DOI: 10.1016/j.apacoust.2025.110573

Albert G. Prinn , Emanuël A.P. Habets

Various methods for estimating acoustic eigenvalues from a measured signal can be found in the literature. Among these methods, the matrix pencil method is a popular choice. The matrix pencil method provides reasonable eigenvalue estimates, albeit alongside several spurious estimates. This work uses Rayleigh quotient iteration to avoid these spurious values. Additionally, a sparse matrix structure is used to write the matrix pencil. The approach is verified using simulated data and validated using measured data. When reliable initial guesses for a few eigenvalues are available, the proposed method provides efficient and accurate eigenvalue estimates.

引用次数: 0

MFF-Net: A multi-scale feature fusion network for birdsong classification

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-01-31 DOI: 10.1016/j.apacoust.2025.110561

Hongfang Zhou , Kangyun Zheng , Wenjing Zhu , Jiahao Tong , Chenhui Cao , Heng Pan , Junhuai Li

In this paper, we propose a novel birdsong classification network, MFF-Net(Multi-scale Feature Fusion Network), which enhances classification performance through multi-scale feature fusion. The network is composed of four components. The first one is a multi-scale feature extraction module that extracts different scale features from the original sound. The second one is a feature fusion module utilizing a channel attention mechanism to integrate these features effectively. The third one is a feature replacement module designed to replace low-weight features and enhance feature representation. And the fourth one is a classifier module that performs birdsong classification. The proposed method was evaluated on two publicly available birdsong datasets and an urban sound dataset(Urbansound8k) to test its generalization performance. Experimental results showed that MFF-Net achieved a classification accuracy of 96.83 % on the BirdCLEF-13 dataset and demonstrated good generalization performance on the urban sound dataset (UrbanSound8k), achieving competitive results. These results highlight the robustness and effectiveness of MFF-Net in noisy and diverse environments.

{"title":"MFF-Net: A multi-scale feature fusion network for birdsong classification","authors":"Hongfang Zhou , Kangyun Zheng , Wenjing Zhu , Jiahao Tong , Chenhui Cao , Heng Pan , Junhuai Li","doi":"10.1016/j.apacoust.2025.110561","DOIUrl":"10.1016/j.apacoust.2025.110561","url":null,"abstract":"<div><div>In this paper, we propose a novel birdsong classification network, MFF-Net(Multi-scale Feature Fusion Network), which enhances classification performance through multi-scale feature fusion. The network is composed of four components. The first one is a multi-scale feature extraction module that extracts different scale features from the original sound. The second one is a feature fusion module utilizing a channel attention mechanism to integrate these features effectively. The third one is a feature replacement module designed to replace low-weight features and enhance feature representation. And the fourth one is a classifier module that performs birdsong classification. The proposed method was evaluated on two publicly available birdsong datasets and an urban sound dataset(Urbansound8k) to test its generalization performance. Experimental results showed that MFF-Net achieved a classification accuracy of 96.83 % on the BirdCLEF-13 dataset and demonstrated good generalization performance on the urban sound dataset (UrbanSound8k), achieving competitive results. These results highlight the robustness and effectiveness of MFF-Net in noisy and diverse environments.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"232 ","pages":"Article 110561"},"PeriodicalIF":3.4,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143261701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deconvolution of the modal phase velocity spectrum for source depth estimation in shallow water

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-01-31 DOI: 10.1016/j.apacoust.2025.110566

Duo Zhai, Fenghua Li, Bo Zhang, Wen Li, Dai Liu

The modal energies have been used to estimate source depth in shallow water. The performance of source depth estimation based on mode filtering would be severely impacted if the aperture of the horizontal array is not sufficient, given the closeness of modes in the wavenumber domain. In this paper, we use the fact that the phase velocity spectrum of the source does not truly represent the modal energy distribution, but rather one that is convolved with the array response functions. Thus, the source depth is estimated by deconvoluting the phase velocity spectrum. During the deconvolution, modal energy ratios are selected from the replica field, and an iterative process is used to search for phase velocities of modes to minimize the residual error between the measured and reconstructed phase velocity spectra. Simulation results demonstrate that the proposed method provides better performance with relatively small apertures and low signal-to-noise ratios compared to the maximum a posteriori filter. Real data collected from a horizontal array on the seafloor confirms that the proposed method is capable of accurately estimating source depth in a shallow water environment.

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引用次数: 0

Noise exposure and auditory risk from air-filled balloon bursts

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-01-31 DOI: 10.1016/j.apacoust.2025.110568

Luis Gomez-Agustina , Antonella Bevilacqua , Pedro Vazquez-Barrera

Latex party balloons filled with air are widely used in a variety of activities including acoustic measurements, educational demonstrations, and leisure. In acoustic research and professional practice, the burst of the balloon is employed as an impulse sound source to obtain room acoustic parameters. Due to its presumed harmless appearance and leisure connotations, acoustic practitioners and lay users often inflate and pop balloons unprotected and unsuspectingly without being aware of the serious auditory risk that those bursts may entail to their hearing health. This research investigates for the first time the noise exposure from popping air-filled latex balloons for a range of likely settings and assesses the risks of hearing damage against a range of relevant international occupational health regulations. Twenty-seven representative exposure scenarios involving peak sound pressure level measurements from three balloon sizes’ bursts were taken at three exposure distances in three different rooms. Results were analysed to estimate unprotected and protected exposure, auditory risks, critical distances, and an estimated permissible number of unprotected burst events. It was found that the exposure of an unprotected person holding and puncturing balloons of two commonly used sizes exceeded various regulatory exposure limits and carried a risk of permanent hearing damage. Wearing standardised hearing protection would reduce the exceeded exposure to eliminate the risk. The exposure of unprotected persons standing at 3 m or further from any balloon size burst was well below regulatory limits and the risk of hearing damage was small. It is expected that the findings, insights and safety guidance provided will help to raise awareness, change attitudes and practices of users. This will reduce the risk of hearing damage and aid professionals to comply with applicable occupational health and safety regulations.

{"title":"Noise exposure and auditory risk from air-filled balloon bursts","authors":"Luis Gomez-Agustina , Antonella Bevilacqua , Pedro Vazquez-Barrera","doi":"10.1016/j.apacoust.2025.110568","DOIUrl":"10.1016/j.apacoust.2025.110568","url":null,"abstract":"<div><div>Latex party balloons filled with air are widely used in a variety of activities including acoustic measurements, educational demonstrations, and leisure. In acoustic research and professional practice, the burst of the balloon is employed as an impulse sound source to obtain room acoustic parameters. Due to its presumed harmless appearance and leisure connotations, acoustic practitioners and lay users often inflate and pop balloons unprotected and unsuspectingly without being aware of the serious auditory risk that those bursts may entail to their hearing health. This research investigates for the first time the noise exposure from popping air-filled latex balloons for a range of likely settings and assesses the risks of hearing damage against a range of relevant international occupational health regulations. Twenty-seven representative exposure scenarios involving peak sound pressure level measurements from three balloon sizes’ bursts were taken at three exposure distances in three different rooms. Results were analysed to estimate unprotected and protected exposure, auditory risks, critical distances, and an estimated permissible number of unprotected burst events. It was found that the exposure of an unprotected person holding and puncturing balloons of two commonly used sizes exceeded various regulatory exposure limits and carried a risk of permanent hearing damage. Wearing standardised hearing protection would reduce the exceeded exposure to eliminate the risk. The exposure of unprotected persons standing at 3 m or further from any balloon size burst was well below regulatory limits and the risk of hearing damage was small. It is expected that the findings, insights and safety guidance provided will help to raise awareness, change attitudes and practices of users. This will reduce the risk of hearing damage and aid professionals to comply with applicable occupational health and safety regulations.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"232 ","pages":"Article 110568"},"PeriodicalIF":3.4,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143261658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Underwater acoustic classification using wavelet scattering transform and convolutional neural network with limited dataset

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-01-31 DOI: 10.1016/j.apacoust.2025.110564

Yongxiang Liu , Biqi Zhang , Fantong Kong , Biao Wang , Chengming Luo , Lin Ma

Underwater acoustic signal classification plays a pivotal role in maritime applications, requiring accurately identifying various acoustic sources in complex underwater environments. While deep learning has substantially enhanced performance in this domain, its success is often contingent on hand-crafted input features and intricate network architectures. The paper presents a novel method for classifying underwater acoustic signals by integrating the Wavelet Scattering Transform (WST) with Attention-augmented Convolutional Neural Networks (CNNs). The WST, based on wavelet analysis, effectively extracts multiscale features while retaining crucial time-frequency information, offering translation invariance and reducing the dependency on large training datasets. Furthermore, incorporating ResNet-18 with an attention mechanism improves extracted features by capturing richer semantic information, even from limited training data. The method was evaluated on the ShipsEar dataset, utilizing only 8.5% of samples for training, 1.5% for validation, and the remaining 90% for testing. Our approach achieved a classification accuracy of 0.93, surpassing the traditional Mel spectrogram with ResNet-18 by 9.8%. These results underscore the effectiveness of the proposed method in handling challenging underwater acoustic environments with limited training data.

{"title":"Underwater acoustic classification using wavelet scattering transform and convolutional neural network with limited dataset","authors":"Yongxiang Liu , Biqi Zhang , Fantong Kong , Biao Wang , Chengming Luo , Lin Ma","doi":"10.1016/j.apacoust.2025.110564","DOIUrl":"10.1016/j.apacoust.2025.110564","url":null,"abstract":"<div><div>Underwater acoustic signal classification plays a pivotal role in maritime applications, requiring accurately identifying various acoustic sources in complex underwater environments. While deep learning has substantially enhanced performance in this domain, its success is often contingent on hand-crafted input features and intricate network architectures. The paper presents a novel method for classifying underwater acoustic signals by integrating the Wavelet Scattering Transform (WST) with Attention-augmented Convolutional Neural Networks (CNNs). The WST, based on wavelet analysis, effectively extracts multiscale features while retaining crucial time-frequency information, offering translation invariance and reducing the dependency on large training datasets. Furthermore, incorporating ResNet-18 with an attention mechanism improves extracted features by capturing richer semantic information, even from limited training data. The method was evaluated on the ShipsEar dataset, utilizing only 8.5% of samples for training, 1.5% for validation, and the remaining 90% for testing. Our approach achieved a classification accuracy of 0.93, surpassing the traditional Mel spectrogram with ResNet-18 by 9.8%. These results underscore the effectiveness of the proposed method in handling challenging underwater acoustic environments with limited training data.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"232 ","pages":"Article 110564"},"PeriodicalIF":3.4,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143261696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-gradient acoustic black hole metamaterial for near-perfect sound Attenuation: Theory, simulation and experiments

IF 3.4 2区物理与天体物理 Q1 ACOUSTICS

Applied Acoustics

Pub Date : 2025-01-25 DOI: 10.1016/j.apacoust.2025.110546

Xinhao Zhang , Mingjing Geng , Caiyou Zhao , Yajun Cao , Ping Wang

A multi-gradient acoustic black hole metamaterial module (MABHM) based on a genetic algorithm-neural network (NN-GA) is optimally designed for near-perfect sound attenuation of sub-wavelength metamaterial structures. Simulation results show that the absorption coefficient of the MABHM is up to more than 0.9 in the range of 300 Hz-20 kHz, and the MABHM has a good absorption effect for sound waves with different incident angles. The complex acoustic impedance of the MABHM has a phase loop approximating near the (1,0) coordinates. It is proved that the impedance matching effect is the key to realizing near-perfect sound absorption. The sound transmission loss curves of MABHM with different perforation ratios are the same, and the sound insulation at frequencies above 200 Hz reaches more than 35.0 dB. The experimental results of sound absorption coefficient and sound transmission loss are consistent with the simulation results. MABHM has the advantages of low-frequency broadband sound absorption and insulation, which can be used to realize nearly perfect noise reduction.

{"title":"Multi-gradient acoustic black hole metamaterial for near-perfect sound Attenuation: Theory, simulation and experiments","authors":"Xinhao Zhang , Mingjing Geng , Caiyou Zhao , Yajun Cao , Ping Wang","doi":"10.1016/j.apacoust.2025.110546","DOIUrl":"10.1016/j.apacoust.2025.110546","url":null,"abstract":"<div><div>A multi-gradient acoustic black hole metamaterial module (MABHM) based on a genetic algorithm-neural network (NN-GA) is optimally designed for near-perfect sound attenuation of sub-wavelength metamaterial structures. Simulation results show that the absorption coefficient of the MABHM is up to more than 0.9 in the range of 300 Hz-20 kHz, and the MABHM has a good absorption effect for sound waves with different incident angles. The complex acoustic impedance of the MABHM has a phase loop approximating near the (1,0) coordinates. It is proved that the impedance matching effect is the key to realizing near-perfect sound absorption. The sound transmission loss curves of MABHM with different perforation ratios are the same, and the sound insulation at frequencies above 200 Hz reaches more than 35.0 dB. The experimental results of sound absorption coefficient and sound transmission loss are consistent with the simulation results. MABHM has the advantages of low-frequency broadband sound absorption and insulation, which can be used to realize nearly perfect noise reduction.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110546"},"PeriodicalIF":3.4,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

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Applied Acoustics

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