Applied Acoustics最新文献

{"title":"Active sonar target recognition based on sub-beam filling and time-frequency fusion tensor","authors":"Zezhou Dai ,&nbsp;Hong Liang ,&nbsp;Tong Duan ,&nbsp;Lei Yue ,&nbsp;Wenbo Gou ,&nbsp;Wenlong Zhu","doi":"10.1016/j.apacoust.2025.110864","DOIUrl":"10.1016/j.apacoust.2025.110864","url":null,"abstract":"<div><div>This paper addresses the issues of low signal-to-noise ratio (SNR), the loss of spatial information in conventional beamforming, and small sample in underwater active sonar detection and recognition. A feature extraction method based on sub-beam filling (SBF) and time-frequency tensor feature fusion is proposed to enhance the feature extraction capability of underwater sonar echoes, which integrates frequency-weighted time-frequency features from STFT, CWT, and SPWVD. To further improve the recognition performance, an improved ConvNeXt architecture, ConvNeXt-DCA, is proposed, incorporating asymmetric convolution kernel decomposition and a lightweight Channel Aggregation (CA) module. Experimental evaluations on both pool and sea trial datasets demonstrate the superiority of the proposed method. Compared to standard beamforming, SBF improves average accuracy from 67.1% to 80.6%. The ConvNeXt-DCA model achieves the highest recognition accuracy of 92.1% on the sea trial dataset and maintains 87.7% under -10 dB SNR in the pool dataset. These results confirm the effectiveness and robustness of the proposed framework in actual sonar recognition scenarios.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110864"},"PeriodicalIF":3.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195243","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}

{"title":"Detection of acoustic vortex generation from rotors using a virtual rotating receiver method","authors":"Lianyun Liu ,&nbsp;Zhigang Chu","doi":"10.1016/j.apacoust.2025.110870","DOIUrl":"10.1016/j.apacoust.2025.110870","url":null,"abstract":"<div><div>Acoustic vortices with orbital angular momentum (OAM) exhibit significant potential in high-speed communication, particle manipulation, and analogue physics. However, existing methods of acoustic vortex generation, whether passive or active, are often cumbersome and rely on supplementary electronic devices to provide sound sources. In this study, we propose that acoustic vortex generation is an intrinsic characteristic of rotating rotors and develop a theory for the generation of acoustic vortices from rotor tonal sources. The theory indicates that the operating frequency and topological charge of the acoustic vortices can be tuned by the rotational frequency and number of blades of rotors. To validate the proposed theory, we employ the virtual rotating receiver (VRR) method to measure the rotational Doppler-shifted spectra of sound fields generated by single and coaxial twin rotors. Analyses of both the Doppler frequency shift and the phase differences between adjacent VRRs reveal an extreme Doppler shift at the location of the OAM handedness reversal, conclusively demonstrating that the generated sound fields are acoustic vortices. Our work has potential applications in multiplexing OAM beams for acoustic communication, contactless detection of rotor speed and number of blades during rotor operation, as well as noise reduction and energy harvesting through the manipulation of acoustic OAM.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110870"},"PeriodicalIF":3.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195242","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}

{"title":"Perceptual and psychoacoustical characteristics of birdsongs","authors":"Joo-Young Hong ,&nbsp;Bhan Lam ,&nbsp;Zhen-Ting Ong ,&nbsp;Kenneth Ooi ,&nbsp;Woon-Seng Gan","doi":"10.1016/j.apacoust.2025.110869","DOIUrl":"10.1016/j.apacoust.2025.110869","url":null,"abstract":"<div><div>Birdsongs are widely recognized for their positive effects on human perception and well-being, making them valuable components of soundscape design. This study investigates the perceptual and psychoacoustic characteristics of birdsongs and their potential application in soundscape designs. A total of 100 birdsongs were collected and analyzed using psychoacoustic indicators (<em>loudness</em>, <em>sharpness</em>, <em>roughness</em>, and <em>fluctuation strength</em>). Subjective assessments of the birdsongs were then conducted using 13 semantic differential attributes in a laboratory setting to identify the main perceptual components of the birdsongs and to cluster them based on these components. Principal component analysis identified three principal perceptual components: PC1 (<em>Gentleness</em>), PC2 (<em>High-pitch</em>), and PC3 (<em>Liveliness</em>). Psychoacoustic analysis revealed that gentleness was negatively correlated with <em>loudness</em>, <em>sharpness</em>, and <em>roughness</em>, whereas liveliness exhibited positive associations with these parameters. Cluster analysis based on the perceptual components categorized the birdsongs into four distinct clusters, with Clusters 3 and 4 being most suitable for soundscape enhancement due to their calm and engaging qualities. Linear discriminant analysis classified birdsongs into clusters with moderate accuracy (64%), demonstrating the potential of psychoacoustic parameters for predicting perceptual characteristics. Cluster 3 achieved the highest classification accuracy (73%), while Cluster 4 had the lowest (50%), suggesting overlapping psychoacoustic attributes. These findings provide a perception-driven approach for incorporating birdsongs into soundscape design.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110869"},"PeriodicalIF":3.4,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195244","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}

{"title":"Topology optimization of sub-chambers in a reconfigurable modular origami silencer for tunable and broadband sound attenuation","authors":"Xiaomeng Jin ,&nbsp;Hongbin Fang ,&nbsp;Qiwei Zhang ,&nbsp;Xiang Yu ,&nbsp;Li Cheng","doi":"10.1016/j.apacoust.2025.110868","DOIUrl":"10.1016/j.apacoust.2025.110868","url":null,"abstract":"<div><div>Origami offers abundant design possibilities and exceptional reconfigurability, making it a rich source of inspiration for acoustic device design. In this paper, we propose an innovative design of modular acoustic silencers by incorporating topology optimization techniques with origami-inspired concepts. Specifically, the internal fillers in the silencer sub-chambers are topologically optimized to target specific frequencies for effective sound attenuation, aiming to achieve over 10 dB attenuation across a broad frequency range from 600 Hz to 1800 Hz. Unlike conventional methods that only alter chamber sizes, our approach utilizes advanced topology optimization tools to shape the internal fillers, enabling precise tuning of the effective frequency range without modifying the external size of the silencer. This ensures modular stacking and acoustic programmability. By cascading multiple topologically optimized modules, we can further achieve broadband sound attenuation over a much wider frequency band. The transmission loss behavior can also be strategically adjusted through the folding mechanism. As a proof-of-concept, we fabricate modular origami silencer prototypes with internal fillers by using 3D-printing technology. Experiments are conducted to validate our simulations and the topology optimization process, demonstrating the effectiveness of broadband sound attenuation through cascading multiple chambers, and the distinctive adjustability offered by folding. Overall, this research brings about fresh perspectives for the design, optimization, deployment, and customization of acoustic silencing devices.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110868"},"PeriodicalIF":3.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195902","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}

{"title":"Milling machine fault detection and identification based on a novel vitality index and temporal-residual network","authors":"Zahoor Ahmad ,&nbsp;Saif Ullah ,&nbsp;Andrei S. Maliuk ,&nbsp;Jong-Myon Kim","doi":"10.1016/j.apacoust.2025.110861","DOIUrl":"10.1016/j.apacoust.2025.110861","url":null,"abstract":"<div><div>This paper presents a novel technique for diagnosing faults in milling machines based on a new health indicator called the vitality index and a temporal-residual network (T-ResNet). Health monitoring of milling machines is crucial for ensuring production reliability and minimizing downtime, and acoustic emission (AE) signals offer a sensitive and effective means for early fault detection in this context. However, traditional features extracted from the acoustic emission signal, such as root mean square and kurtosis, are widely used for fault detection, but their sensitivity is compromised by noise. Furthermore, acoustic emission hit (AEH) features have received little attention in milling machine diagnosis. Therefore, in this study, AE signals are acquired from a milling machine for extraction of AEH features. The signals include both continuous and burst type AEHs. Burst-type hits are distinct due to their clear rise and decay, whereas continuous hits lack such differentiation from background noise. A new adaptive thresholding technique is used to effectively extract AEH features. The new technique adapts itself to the AE signal and takes into account both types of AEHs. The distribution of those features varies with the milling machine’s health status. To identify a distribution change, the Mann-Whitney test is applied to the features at multiple scales to obtain a new health indicator called the vitality index (VI). The vitality index changes significantly as the milling machine transitions from a normal operating state to a faulty condition. To identify the defect in the milling machine, the index is classified using a T-ResNet. The proposed method is validated using real-world industrial milling machine data and demonstrates fault detection superior to existing techniques.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110861"},"PeriodicalIF":3.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144195241","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}

{"title":"Improving heavy-weight floor impact sound FEA predictions in box-frame concrete apartments: slab damping and elastic modulus","authors":"Seong-Bok Lee ,&nbsp;Myung-Jun Kim","doi":"10.1016/j.apacoust.2025.110863","DOIUrl":"10.1016/j.apacoust.2025.110863","url":null,"abstract":"<div><div>Predicting heavy-weight floor impact sound in reinforced concrete apartment buildings is crucial for ensuring acoustic comfort. This study aims to enhance the accuracy of finite element analysis based predictions of heavy-weight floor impact sound by evaluating the damping ratio and elastic modulus of concrete slabs. Field measurements were conducted in a newly constructed box-frame reinforced concrete apartment building in South Korea, where the damping ratio of slabs was measured using both an impact hammer and a standard heavy-weight impact source, rubber ball over a frequency range of 1–800 Hz. The results revealed significant variations in damping ratios depending on the impact source, with damping increasing at lower frequencies.</div><div>To assess the effect of elastic modulus variations on prediction accuracy, FEA simulations were conducted with elastic modulus values set at 70 %, 80 %, 90 %, and 100 % of the design value, 25 GPa. The predicted and measured results were compared using Pearson correlation coefficients and root mean squared error analysis. Among the four floor plan types analyzed, three exhibited the highest accuracy at 70 % of the design elastic modulus, while one type showed better agreement at 100 %.</div><div>This study confirms that using the damping ratio obtained from the same impact source as the measurement improves prediction accuracy. Additionally, accounting for the natural vibration mode of the slab when selecting the elastic modulus enhances the precision of heavy-weight floor impact sound predictions. These findings contribute to the optimization of floating floor system designs by mitigating resonance phenomena in reinforced concrete apartment buildings.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110863"},"PeriodicalIF":3.4,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185634","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}

{"title":"The effect of frequency on the propagation of L (0, 1) guided waves in the prestressed strand anchorage segment","authors":"Can Wang,&nbsp;Wenjie Xiao,&nbsp;Jiang Xu","doi":"10.1016/j.apacoust.2025.110859","DOIUrl":"10.1016/j.apacoust.2025.110859","url":null,"abstract":"<div><div>In prestressed anchorage systems, steel strands are typically encased within protective materials which restricts guided wave excitation from the external free segment. Effective assessment of internal strand integrity requires wave propagation through the anchorage segment. This study investigated the effect of frequency on the propagation characteristics of L (0, 1) guided waves in prestressed strand anchorage segments. Semi-analytical finite element models were developed for both the free and tensile segment of the steel strand to analyze the displacement distribution of the L (0, 1) guided wave within the frequency range of 80–320 kHz.. The results show that the energy of the L (0, 1) guided waves is more concentrated at the cross-section center in the outer helical steel wires with the increasing of the frequency. These phenomena indicates that the higher frequency L (0, 1) guided waves are less affected by the anchor constraint boundary conditions. To further investigate wave behavior in the anchorage segment, a finite element simulation model was established to investigate the transient propagation characteristics of L(0,1) guided waves through the anchorage. The simulation results show that the strong interface reflection echoes are induced when the L (0, 1) guided waves propagate through the anchorage segment from the free segment. In addition, due to energy leakage from the steel wire into the anchorage, a trailing leakage wave packet is generated after the guided wave passes through the anchorage. However, as the frequency of the L (0, 1) guided wave increases from 80 kHz to 320 kHz, both the reflection and leakage phenomena in the anchorage segment gradually diminish. Finally, a guided wave through-anchorage detection experiment was conducted, and the results demonstrated that the reflection coefficient reaches 0.57 at 80 kHz and decreases rapidly with increasing frequency to 0.12 at 200 kHz and then stabilizes. In contrast, the transmission coefficient shows a non-monotonic trend due to interference between leakage and transmitted waves, increasing from 0.37 to 0.45 in the 80–120 kHz range, decreasing to 0.17 between 120–240 kHz, and then recovering to 0.43 in the 240–320 kHz range, which aligns well with the simulation results. This study provides a basis for selecting guided wave modes and frequencies for detecting steel strand defects within anchorage systems.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110859"},"PeriodicalIF":3.4,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185635","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}

{"title":"TBP-XFE: A transformer-based explainable framework for EEG music genre classification with hemispheric and directed lobish analysis","authors":"Suat Tas ,&nbsp;Dahiru Tanko ,&nbsp;Irem Tasci ,&nbsp;Sengul Dogan ,&nbsp;Turker Tuncer","doi":"10.1016/j.apacoust.2025.110855","DOIUrl":"10.1016/j.apacoust.2025.110855","url":null,"abstract":"<div><div>Electroencephalography (EEG) signals offer important information for machine learning. In this work, we evaluate whether EEG signals can be used to classify music genres. We use a new transformer-based feature extraction method called the Three-Body Pattern (TBP). We also collected an EEG based music dataset containing five classes and these classes are: classical, popular, rap, ballad, and resting.</div><div>Our feature engineering framework operates in four phases. First, the TBP method transforms each EEG signal to extract distinct features. Second, we use cumulative weighted neighborhood component analysis (CWNCA) to select the best features. Third, a t-algorithm-based k-nearest neighbors (tkNN) classifier assigns class labels. Finally, we apply Directed Lobish (DLob) and hemispheric symbolic languages to produce clear and explainable results.</div><div>The TBP-related explainable feature engineering (XFE) framework achieved over 90% classification accuracy on the EEG music dataset. This represents a promising advancement in EEG based music classification because it produces clear and explainable outputs.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110855"},"PeriodicalIF":3.4,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144166388","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}

{"title":"Exploiting lightweight neural post-filtering for directional speech enhancement","authors":"Tianchi Sun ,&nbsp;Xiaobin Rong ,&nbsp;Dahan Wang ,&nbsp;Yuxiang Hu ,&nbsp;Kai Chen ,&nbsp;Jing Lu","doi":"10.1016/j.apacoust.2025.110844","DOIUrl":"10.1016/j.apacoust.2025.110844","url":null,"abstract":"<div><div>Directional speech enhancement using a microphone array aims to isolate the target speaker's voice from competing speakers and background noise. While traditional signal processing-based beamformers often struggle to suppress residual interference, end-to-end methods face challenges in operating on low-resource devices and generalizing to real-world scenarios. To address these issues, we propose a hybrid approach that integrates the robust generalized sidelobe canceler (GSC) with a neural post-filter. Our method employs a lightweight network architecture as the backbone of the neural post-filter, utilizing both microphone array signals and GSC outputs, which are modeled by separate encoders. Additionally, we introduce an auxiliary decoder to learn the target components in the GSC outputs, thereby enhancing the post-filter's performance when combined with a knowledge distillation training strategy, all without introducing additional computational load during inference. Experimental results on simulated and real-world datasets demonstrate the superior performance of the hybrid system, validating the effectiveness of our proposed methods.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110844"},"PeriodicalIF":3.4,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144166389","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}

{"title":"Ultra-wideband acoustic meta-silencer to achieve target overall noise reduction levels: Design and experimental validation","authors":"Jaeho Cho ,&nbsp;Jin Woo Lee","doi":"10.1016/j.apacoust.2025.110852","DOIUrl":"10.1016/j.apacoust.2025.110852","url":null,"abstract":"<div><div>An acoustic meta-silencer was designed using a generative design technique for ultra-wideband noise reduction, and its noise attenuation performance was experimentally validated. The target frequency range of the silencer and the target noise attenuation at each frequency were determined by considering the frequency-dependent noise characteristics of the existing exhaust system and its target overall noise reduction level. Generally, an acoustic meta-structure consists of unit cells that can block sound waves in frequency ranges corresponding to the band gaps in their dispersion curve plot. A new internal partition layout of the unit cells was proposed and optimized to make their band gaps as wide as possible. Various unit cells were generated, and their dispersion curve plots were obtained through acoustic analysis. Among the generated unit cells, several were systematically selected and sequentially arrayed so that their connected band gaps should cover the target frequency range of 100 to 6000 Hz. We proposed a design exploration algorithm to facilitate optimal design selection. An acoustic meta-silencer composed of five types of unit cells was successfully designed and fabricated, and its measured insertion loss curve demonstrates high and ultra-wideband noise attenuation performance.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":"239 ","pages":"Article 110852"},"PeriodicalIF":3.4,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144166387","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}