Applied Acoustics最新文献_第4页

Low bit-rate speech coding with predictive multi-level vector quantization

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-15 DOI: 10.1016/j.apacoust.2025.110538

Xingye Yu, Ye Li, Peng Zhang, Lingxia Lin, Tianyu Cai

{"title":"Low bit-rate speech coding with predictive multi-level vector quantization","authors":"Xingye Yu, Ye Li, Peng Zhang, Lingxia Lin, Tianyu Cai","doi":"10.1016/j.apacoust.2025.110538","DOIUrl":"10.1016/j.apacoust.2025.110538","url":null,"abstract":"<div><div>During the development of modern communication technology, although wideband speech coding can provide high-fidelity speech transmission, its high bandwidth requirements limit its application in resource-constrained environments. Narrowband speech coding still holds research value. However, traditional narrowband low bit-rate speech coding methods usually cannot generate satisfactory speech quality. To address this issue, this paper proposes a narrowband low bit-rate speech coding architecture called PMVQCodec, with the following major improvements. Firstly, we design a predictive multi-level vector quantization (PMVQ) technique, which employs a predictor to effectively capture the correlations between latent frame vectors and combines it with multi-level vector quantization to enhance quantization efficiency. Additionally, we also introduce a full-band feature extractor to effectively reduce the computational complexity. In our experiments, both subjective and objective evaluations demonstrated the effectiveness of the proposed PMVQCodec architecture. Our proposed method can achieve higher quality reconstructed speech than Encodec and HiFiCodec at 1.2 kbps and 2.4 kbps, and even outperforms LyraV2 at 6 kbps.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110538"},"PeriodicalIF":3.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095928","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

Enhancing underwater single snapshot DOA estimation for limited dataset with modified knowledge distillation

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-14 DOI: 10.1016/j.apacoust.2025.110531

Qinzheng Zhang , Haiyan Wang , Xiaohong Shen , Yongsheng Yan , Yingying Zhu , Jesper Rindom Jensen

{"title":"Enhancing underwater single snapshot DOA estimation for limited dataset with modified knowledge distillation","authors":"Qinzheng Zhang , Haiyan Wang , Xiaohong Shen , Yongsheng Yan , Yingying Zhu , Jesper Rindom Jensen","doi":"10.1016/j.apacoust.2025.110531","DOIUrl":"10.1016/j.apacoust.2025.110531","url":null,"abstract":"<div><div>In recent years, the progress in DOA estimation using deep learning algorithms has attracted significant attention. However, their heavy reliance on extensive datasets poses a critical limitation, particularly in underwater settings where data collection is arduous. Furthermore, the lack of temporal correlation and statistical properties inherent in single-snapshot information lead to low accuracy in single-snapshot DOA estimation. To confront the above hurdles, this paper introduces an approach to improve the accuracy of underwater single snapshot DOA estimation with limited underwater datasets. By modifying the process structure and model characteristics of knowledge distillation (KD), we construct a new distillation structure that can bridge the gap between single snapshot data and multi-snapshot data sharing identical labels, achieving a breakthrough in compressing multi-snapshot data. This enhances the neural network's capacity to process both few-snapshot datasets and single-snapshot datasets. In addition, we designed novel input features to reduce the difficulty of CNN fitting by extracting the real and imaginary parts of the analytical signals, and integrated the array structure information to improve the generalization ability of our network in different scenarios. Besides, based on these innovations, we build a mapping framework between synthetic and real underwater datasets. This work involves second-order joint training of KD and transfer learning, which can help deal with small samples. The experiment results of our method show significant improvements in underwater DOA estimation accuracy, coupled with a marked reduction in overfitting risks associated with limited datasets. This work not only advances the application of deep learning in challenging underwater scenarios but also lays a foundation for future data-driven inference strategies.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110531"},"PeriodicalIF":3.4,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095421","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

Application and control mechanism of thin film metamaterials in underwater sound-absorbing materials at low frequency under high hydrostatic pressure

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-13 DOI: 10.1016/j.apacoust.2025.110535

Tian Yan , Kejian Wang

{"title":"Application and control mechanism of thin film metamaterials in underwater sound-absorbing materials at low frequency under high hydrostatic pressure","authors":"Tian Yan , Kejian Wang","doi":"10.1016/j.apacoust.2025.110535","DOIUrl":"10.1016/j.apacoust.2025.110535","url":null,"abstract":"<div><div>This study focused on developing a composite structure that utilizes thin film metamaterials to realize low-frequency (0.1–1 kHz) underwater sound-absorbing. The sound-absorbing performance of the composite structure was assessed by investigating the effects of thin film materials, thickness, and mass block distribution using a combined approach of numerical simulation and experimentation. Results demonstrated that thin film metamaterials with lower modulus, such as silicon rubber (SR) thin film, have lower natural frequencies. In addition, a thicker SR film had a higher elastic strain energy density. Symmetrical mass block distribution was able to widen the absorbing bandwidth of the first three natural frequencies: improvements of 6 Hz, 2.8 Hz and 2.6 Hz were observed, respectively. Acoustic sample was fabricated and tested to verify the accuracy of numerical simulation. This study provided new insights into designing underwater sound-absorbing structures containing thin film metamaterials and supported the development of better stealth capabilities for underwater vehicles, especially in the context of low-frequency active sonar.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110535"},"PeriodicalIF":3.4,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095419","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

Effective method for calculating acoustic radiation of an underwater target with a complex isolation system

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-13 DOI: 10.1016/j.apacoust.2025.110534

Yi-Ni Yang , Ming-Song Zou , Ze-Qi Lu , Zhi-Yong Yin , Qiang Xi

{"title":"Effective method for calculating acoustic radiation of an underwater target with a complex isolation system","authors":"Yi-Ni Yang , Ming-Song Zou , Ze-Qi Lu , Zhi-Yong Yin , Qiang Xi","doi":"10.1016/j.apacoust.2025.110534","DOIUrl":"10.1016/j.apacoust.2025.110534","url":null,"abstract":"<div><div>This paper introduces an efficient method for determining the acoustic radiation of underwater targets equipped with an intricate isolation system. Using the mode superposition method and the spherical source distribution method, the fluid–structure coupling vibration and underwater acoustic radiation of the main structure, such as the main hull, pedestal, and reinforced rib, were computed after the main structure was isolated from the internal floating raft and vibration isolator. The finite element model was used to establish the floating raft, and the modal synthesis superelement method was employed to condense the degree of freedom, forming the mass and stiffness matrices. The four-terminal parameter method was used to establish the vibration transmission model of the isolator. The introduction of the virtual mode leads to the establishment of the coupling dynamic equation via the boundary connection state. The spherical source distribution method simplifies the three-dimensional (3D) acoustic problem by placing source points along a straight line within the target, effectively transforming it into a quasi-one-dimensional distinct element issue. Naturally, irregular frequency issues are absent, rendering it suitable for addressing the acoustic-vibration coupling of any 3D elastic underwater target. This paper discusses the basic principles, computation formulas, and findings of several numerical examples of the proposed method.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110534"},"PeriodicalIF":3.4,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095423","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-period impulse cyclic spectrum based on optimized RSSD for bearing compound fault diagnosis

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-13 DOI: 10.1016/j.apacoust.2024.110525

Xiaofeng Liu, Quangui Xu, Daiping Wei, Lin Bo

{"title":"Multi-period impulse cyclic spectrum based on optimized RSSD for bearing compound fault diagnosis","authors":"Xiaofeng Liu, Quangui Xu, Daiping Wei, Lin Bo","doi":"10.1016/j.apacoust.2024.110525","DOIUrl":"10.1016/j.apacoust.2024.110525","url":null,"abstract":"<div><div>A common symptom of compound faults in rolling element bearings is the presence of multi-periodic pulses in vibration signals. To solve the problem of decoupling and isolating diverse fault impulses, a novel multi-period impulse cyclic spectrum based on optimized resonance-based sparse decomposition is developed. Impulse cyclicity measure (ICM) is designed to measure the impulsivity and periodicity of fault impacts, which provides greater immunity to random transient interferences. In order to separate the multi-period impulses, the RSSD’s parameters are tuned using the multi-scale simplified particle swarm optimization algorithm with the aim of maximizing ICM value. To simultaneously display the cyclic frequencies of many fault impulses, the multi-period impulse cyclic spectrum is established on the low-frequency resonance component, which has higher sensibility to repetitive transients contaminated by noise and good physical interpretation. The simulation and application results for diagnosing bearing faults showed that the suggested method performed well in the synchronous diagnosis of bearing compound defects and avoided resonant frequency band misinterpretation caused by strong pulse interference.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110525"},"PeriodicalIF":3.4,"publicationDate":"2025-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095422","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

Gas pipeline leakage identification and location using microporous structure optical sensing cable

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-11 DOI: 10.1016/j.apacoust.2024.110524

Shichong Fu , Dan Zhang , Qun Luo , Bin Shi , Haiyang Liao , Hasanjan Yimit

引用次数: 0

Single-beacon AUV navigation algorithm under period offset conditions

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-10 DOI: 10.1016/j.apacoust.2024.110522

Qingyu Zhang , Jin Fu , Bin Qi , Nan Zou , Yongshuai Gao

{"title":"Single-beacon AUV navigation algorithm under period offset conditions","authors":"Qingyu Zhang , Jin Fu , Bin Qi , Nan Zou , Yongshuai Gao","doi":"10.1016/j.apacoust.2024.110522","DOIUrl":"10.1016/j.apacoust.2024.110522","url":null,"abstract":"<div><div>Underwater positioning and navigation technology is one of the key technologies for autonomous underwater vehicles to complete tasks efficiently. The navigation and positioning technology of single-beacon autonomous underwater vehicles has been highly valued because of its advantages such as simple and convenient placement. The existing implementation schemes are mainly based on arrival time information or arrival time difference information, and the prior knowledge they need includes synchronization time and signal cycle. However, due to the influence of the marine environment, such as low temperature and high pressure, the period of beacon transmission signal may be offset, resulting in navigation error increase or even failure. To solve this problem, this paper proposed a navigation method with looser application conditions, which is improved based on the TDOA algorithm, and it requires neither synchronization time nor signal cycle. Secondly, the influence of different motion trends on navigation accuracy and the influence of different measurement errors on the algorithm are analyzed by a full differential equation. Finally, the performance of the proposed algorithm is verified by simulation experiments and actual data. The results show that when the signal cycle is accurate, the accuracy of the proposed method is almost the same as that of the navigation algorithm based on TDOA; when the signal cycle offset leads to an increase in TDOA error or even failure, the method still has good adaptability and stability.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110522"},"PeriodicalIF":3.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095915","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

Design and analysis of a novel quantum-classical hybrid neural network for environmental sound classification

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-10 DOI: 10.1016/j.apacoust.2024.110527

Tao She , Haijian Shao , Xing Deng , Yingtao Jiang

{"title":"Design and analysis of a novel quantum-classical hybrid neural network for environmental sound classification","authors":"Tao She , Haijian Shao , Xing Deng , Yingtao Jiang","doi":"10.1016/j.apacoust.2024.110527","DOIUrl":"10.1016/j.apacoust.2024.110527","url":null,"abstract":"<div><div>In the field of Environmental Sound Classification (ESC), traditional deep learning methods face significant challenges in processing high-dimensional audio data. In response, this study innovatively proposes a quantum-classical hybrid neural network model—St-HQCNN. This model adeptly integrates the advantages of quantum superposition and quantum entanglement, which are fundamental to quantum computing, thereby significantly enhancing the model's ability to recognize and process complex sound data with greater robustness. Through the design of carefully crafted quantum circuits and misalignment reading mechanisms, St-HQCNN not only demonstrates outstanding classification performance on benchmark datasets such as UrbanSound8K, ESC-10, and ESC-50, achieving accuracy rates of 97.14%, 99.38%, and 93.75%, respectively, but also highlights the tremendous potential of quantum-enhanced neural networks in sound recognition tasks. The experimental results clearly reveal the substantial promise of quantum-assisted neural networks in this domain, laying the foundation for future research and practical applications. This study not only showcases the theoretical innovations of St-HQCNN but also focuses on its feasibility for real-world applications. Moving forward, we aim to explore the scalability of the model, address challenges in practical deployment, and advance the widespread use of quantum neural networks in the field of machine learning.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110527"},"PeriodicalIF":3.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095919","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

Machinery fault diagnosis-oriented regularization for nonlinear system identification: Framework and applications

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-10 DOI: 10.1016/j.apacoust.2025.110537

Yulai Zhao , Zepeng Liu , Zhiwei Yang , Qingkai Han , Hui Ma

{"title":"Machinery fault diagnosis-oriented regularization for nonlinear system identification: Framework and applications","authors":"Yulai Zhao , Zepeng Liu , Zhiwei Yang , Qingkai Han , Hui Ma","doi":"10.1016/j.apacoust.2025.110537","DOIUrl":"10.1016/j.apacoust.2025.110537","url":null,"abstract":"<div><div>In this article, we propose a novel framework for machinery fault diagnosis based on nonlinear system identification, called Identification for Fault Diagnosis (I4FD) The focus and necessity of the framework is that it can mitigate the effects of external environmental changes and enhance diagnostic accuracy. The framework integrates regularized data-driven modeling and frequency analysis. During the modeling process, prior physical knowledge about the diagnostic target is incorporated through a penalty parameter, leading to fault diagnosis-oriented regularization (FDoR). FDoR tailors the model specifically for fault diagnosis (FD) applications, offering new insights into FD-oriented system identification. The regularized NARX modeling in this paper does not end when a model is built by using information in a period of time, but uses the updated data for continuous dynamic modeling. After the model is identified, frequency analysis is then used to extract model-based features, which change significantly when faults occur. The effectiveness of the I4FD framework is demonstrated through simulations and real cases, highlighting its advantages over traditional methods and its industrial potential.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110537"},"PeriodicalIF":3.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095916","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

Wideband raypath separation based on covariance matrix reconstruction

IF 3.4 2区物理与天体物理

Applied Acoustics Pub Date : 2025-01-10 DOI: 10.1016/j.apacoust.2024.110518

Fengyan Zhong, Zhicheng Li, Chao Yang

{"title":"Wideband raypath separation based on covariance matrix reconstruction","authors":"Fengyan Zhong, Zhicheng Li, Chao Yang","doi":"10.1016/j.apacoust.2024.110518","DOIUrl":"10.1016/j.apacoust.2024.110518","url":null,"abstract":"<div><div>The application of covariance matrix reconstruction based algorithms is motivated by the need to improve the separation accuracy of the grid-dependent compressive sensing method in the presence of grid mismatch. However, the existing published literatures are focused on the detection of narrowband acoustic signals (or raypaths). In this paper, a wideband covariance matrix construction based algorithm is proposed for the separation of wideband raypaths. First, a wideband covariance matrix model is developed to recover the Toeplitz matrix, which possesses low-rank and positive semi-definite (PSD) properties. The separation of raypaths is then achieved from the recovered matrix by applying a conventional subspace-based method. Results from simulation and tank experiment demonstrate that the proposed algorithm offers several advantages: (1) it enables the identification of wideband and coherent raypaths with high resolution, particularly when arrival times are close; (2) it significantly improves accuracy in the presence of grid mismatch, due to the absence of a predefined grid; and (3) it allows the detection of more raypaths than can be identified through the direct application of the interspectral matrix.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"231 ","pages":"Article 110518"},"PeriodicalIF":3.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143095917","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