Vol. 60 No. 3 (2026): In Progress

Open Access

Article

Article ID: 3908

Inverse engineering of micro-perforated plates for targeted acoustic characteristics

by Binxia Yuan, Xiangyang Li, Tianqi You, Tianzhong Chen, Rui Zhu

Sound & Vibration, Vol.6, No.3, 2026;

The inverse design of micro-perforated panels (MPPs) for target sound absorption remains challenging due to the complex nonlinear relationship between structural parameters and acoustic performance. This study proposes a tandem neural network (TNN) framework to achieve efficient inverse design of single-layer MPPs. A forward multi-layer perceptron (MLP) is first trained to accurately predict the absorption coefficient curve from three key structural parameters: perforation diameter, panel thickness, and cavity depth. The forward model achieves superior accuracy compared to GA-SVR, GridSearch-SVR, and random forest models, with an R² of 0.999 and MAE of 0.007. Subsequently, an inverse design network is connected in series with the frozen forward network, taking a target absorption curve as input and outputting the corresponding structural parameters. The activation function of the output layer constrains the parameters within physically feasible ranges. The framework is validated by designing an MPP with a distinct absorption peak in the 300–600 Hz range. The predicted parameters (diameter 0.93 mm, thickness 0.9 mm, cavity depth 9.9 mm) yield an absorption curve that matches the target with an R² of 0.997. This work demonstrates that deep learning can effectively automate the inverse design of MPPs, offering a flexible and efficient alternative to traditional trial-and-error methods.

Open Access

Article

Article ID: 4070

Fuzzy-stochastic coupled models for broadband noise radiation from flexible

by Suleiman Ibrahim Mohammad, Yogeesh Nijalingappa, Basem Abu Zneid, Shashikumar Honnavalli Channabasavaiah, Asokan Vasudevan, Jayaprakasha Pathiyappanapallya Chandraiah

Sound & Vibration, Vol.6, No.3, 2026;

Broadband noise radiation from flexible panels is governed by the coupling of random excitation fields with uncertain structural and boundary parameters. This paper develops a fuzzy-stochastic vibro-acoustic framework that separates (i) aleatory uncertainty in the broadband pressure field from (ii) epistemic uncertainty in panel properties and mount conditions. The panel dynamics are modeled in the frequency domain using a modal or finite-element representation of the thin-plate operator, while acoustic radiation is evaluated through a baffle-mounted radiation model leading to radiated sound power spectra. Random excitation is represented by the pressure cross spectral density, enabling direct propagation of spectral statistics to displacement and velocity cross-spectra via linear transfer functions. Epistemic uncertainty in Young's modulus, thickness, and loss factor is represented by fuzzy numbers and propagated through α-cuts, yielding interval-valued parameter sets at each α level. The coupling is implemented using an α-cut outer loop with a stochastic inner solver that computes mean and variance of radiated sound power; α-level interval extrema then provide fuzzy envelopes of stochastic response metrics. Verification is performed through modal truncation, frequency-grid stability, and α-grid refinement. Numerical demonstrations using representative datasets show that epistemic uncertainty can induce wide bands in band-integrated sound power level (≈9.9 dB in the 100–1,000 Hz band at α = 0), and that percentile metrics (e.g., 95th percentile under a lognormal approximation) provide conservative bounds for design decision-making. The proposed framework offers a transparent and computationally tractable route to uncertainty-aware broadband vibro-acoustic prediction for panels in vehicles, buildings, and machinery enclosures.

Open Access

Article

Article ID: 4017

Optimization and experimental study of low-frequency sound absorption performance for modified sonic black hole

by Ziyan Chen, Qibo Mao, Lihua Peng

Sound & Vibration, Vol.6, No.3, 2026;

The design of a sound absorber with simultaneous broadband and low-frequency absorption is still difficult to achieve. Most existing noise reduction techniques target only a single aspect of the acoustic performance. The difficulty lies in the inherent trade-off between compact size, broad bandwidth, and effective low-frequency absorption. To overcome these issues, this study proposes a modified sonic black hole (SBH) to enhance the conventional SBH structure's low-frequency broadband sound absorption capabilities. By introducing the concept of equivalent length, this study adjusts only the opening area of the SBH structure without increasing its length, thereby equating the modified SBH to an original SBH with a longer geometric length. This equivalent extension enhances the coupling between the structure and low-frequency sound waves, thereby improving the low-frequency sound absorption performance. Theoretical modeling and simulation analysis demonstrate that reducing the SBH inlet diameter (or ring maximum inner diameter) can effectively improve the SBH low-frequency sound absorption effect. Furthermore, experimental comparisons of modified SBHs under different inlet diameters reveal that reducing the diameter from a fully open (95 mm) to 30 mm reduces the SBH’s first natural frequency from 615 Hz to 225 Hz, demonstrating a marked improvement in low-frequency sound absorption performance. The proposed modified SBH concept provides a promising solution for low frequency and broadband noise control.

Open Access

Article

Article ID: 3994

Analysis of an existing methodology for assessing vehicle-track interaction under reliability conditions

by Shuxrat Djabbarov, Bakhrom Abdullayev, Aziz Gayipov, Abdusaid Yuldashov, Nodir B. Adilov, Irina Soboleva

Sound & Vibration, Vol.6, No.3, 2026;

This paper presents a focused analytical audit of two simplified vehicle-track interaction schemes reported in the State Standard for 1,520 mm Gauge Railways: (i) a wheel-on-rail stability scheme intended to characterize flange-climb resistance and (ii) a track lateral stability scheme intended to estimate sleeper-rail-grid shift under train loading. The aim is twofold: first, to identify the internal inconsistencies of these specific formulations; second, to derive general lessons for transparent and reproducible safety assessment in railway engineering. The audit is organized around three steps: reconstruction of the source free-body diagrams and symbol definitions, point-by-point consistency checks of the equilibrium relations, and formulation of corrected self-contained equations in a unified coordinate system. The revised presentation shows that the source schemes mix force and moment terms, use ambiguous coordinate conventions, and in several places produce self-referential or physically trivial coefficients. A compact worked example is provided to illustrate the numerical difference between a parameter-independent source-style ratio and the corrected parameter-dependent contact-equilibrium relation. The paper also clarifies the status of each figure as either adapted from the source schemes or reconstructed by the authors and condenses the normative background to the material strictly needed for interpretation. Overall, the revised workflow improves traceability, reproducibility, and engineering interpretability.

Open Access

Article

Article ID: 2034

Articulation index-based acoustic signal processing for enhanced speech intelligibility

by Mahesh Shankarrao Patil, Vijaykumar Varadarajan, Harsha Jitendra Sarode, Farook Sayyad, Rahul Krishna Sarawale, Shabnam Sayyad, Deshinta Arrova Dewi

Sound & Vibration, Vol.6, No.3, 2026;

This paper presents an innovative approach to improving speech intelligibility using the wavelet transform and the Articulation Index (AI) as an objective evaluation metric. Conventional methods such as the Modified Rhyme Test (MRT) and Mean Opinion Score (MOS) rely on subjective assessment, making them time-consuming and difficult to standardize. In contrast, AI provides a consistent and reliable measure of speech intelligibility across varying noise conditions. The proposed method applies wavelet packet transform to noisy speech signals, followed by a thresholding function to enhance signal quality and intelligibility. The processed speech is then reconstructed using the inverse wavelet transform. Experiments are conducted using the Noiseus database, which contains speech signals corrupted by real-world noises such as streets, airports, cockpits, and industrial environments like mechanical factories, with noise levels ranging from 0 dB to 15 dB. Three different enhancement methods are implemented, with the proposed method demonstrating superior performance in terms of AI values. Experimental validation is supported by plots and spectrograms, highlighting its effectiveness over existing approaches. The method leverages the multi-resolution property of the wavelet transform to preserve temporal characteristics while reducing noise across multiple frequency bands. Results show a significant improvement in AI values, indicating enhanced speech intelligibility under diverse noise conditions. This work contributes to acoustic speech enhancement by providing a robust, objective framework suitable for applications in noisy environments such as industrial communication systems, and this technique aligns closely with noise mitigation approaches used in structural and industrial surroundings. Additionally, the approach can be extended to industrial speech enhancement and environmental noise control.

Open Access

Article

Article ID: 4106

Timbre transfer of classical guitars using impulse response and a laser displacement sensor

by Che-Hsu Yeh, Chii-Chang Chen

Sound & Vibration, Vol.6, No.3, 2026;

Conventional characterization of musical instruments relies on microphones, whose measurements depend strongly on distance, sound radiation directionality, and the non-uniform frequency responses of microphones and preamplifiers, often introducing distortions. Laser displacement sensors, widely used for vibration and surface measurements, offer a higher maximum displacement–to–resolution ratio than laser Doppler vibrometry. Measuring instrument vibrations with such sensors enables the capture of a more intrinsic acoustic source. This study demonstrates timbre transfer from a hand-made guitar to a José Ramírez guitar using convolution with impulse responses obtained from both a laser displacement sensor and a microphone. Timbre similarity is evaluated via cross-correlation of acoustic spectra between original and transferred notes. For 33 notes (E2–C5), the laser-based method yields higher cross-correlation in 28 cases compared to the microphone-based approach. The results highlight the distinction between vibration-based and pressure-based timbre characterization. Microphone measurements capture far-field sound pressure along with environmental noise, whereas laser displacement sensing directly reflects the instrument’s vibrational behavior. Consequently, laser-based impulse responses provide a more intrinsic representation of acoustic spectra and enable more accurate timbre transfer. After recording a performance, the timbre of one instrument can therefore be transferred more precisely to another using impulse responses derived from laser displacement sensors.

Open Access

Article

Article ID: 4116

Hidden-state unscented Kalman filter with unknown input for the joint identification of 3D structural parameters and unknown excitation

by Lijun Liu, Yahan Yang, Shiyu Wang, Ying Lei, Yujue Zhou, Nan Gong

Sound & Vibration, Vol.6, No.3, 2026;

The unscented Kalman filter with unknown input (UKF-UI) is an effective method for the identification of structural system and unknown excitation, but for three-dimensional multi-degree-of-freedom structures, the joint identification of structural state-parameter-unknown excitation often leads to high dimensions of extended state vector. To address this issue, a hidden-state unscented Kalman filter with unknown input is proposed for the joint identification of structural parameters and unknown excitation of three-dimensional structures. In the proposed method, only the time-invariant structural parameters are included in the structural state vector, while the displacements and velocities of all structural degrees of freedom are defined as hidden states and excluded from the state vector. This explicitly avoids the conventional extended state vector containing displacement, velocity and structural parameters. By reducing the state vector dimension, the identification of joint structural state-parameter is reduced to parameter-only identification. Moreover, the unbiased minimum variance estimation is used to achieve synchronous identification of unknown excitation. It avoids prior assumptions about unknown excitation and enhances the applicability in practical engineering. The identification of a three-dimensional frame structure under unknown excitation is used to verify the effectiveness of the proposed method. Through the observation of partial acceleration and displacement response data, structural element parameters of the three-dimensional structure and the unknown excitation acting on the three-dimensional structure can be identified.