Vol. 60 No. 5 (2026): In Progress

Open Access

Article

Article ID: 4406

The Effect of music genre on work productivity in repetitive tasks: An experimental study for sound and vibration applications

by Heri Setiawan, Pawenary, Micheline Rinamurti, Sani Susanto

Sound & Vibration, Vol.60, No.5, 2026;

The physical work environment significantly influences worker performance, with workplace acoustics playing an important role in cognitive functioning and productivity. This study investigated the effect of music genre as an engineered acoustic intervention on productivity during repetitive industrial tasks. Unlike previous studies emphasizing psychological outcomes, this research integrates occupational acoustics, industrial ergonomics, and productivity engineering to evaluate music as a controllable workplace sound variable. A repeated-measures experimental design was conducted under four auditory conditions: no music, jazz, pop, and instrumental music. Productivity was assessed using output and work cycle time during repetitive manual tasks. Data were analyzed using one-way repeated-measures analysis of variance (RM-ANOVA) followed by Bonferroni-adjusted pairwise comparisons. Mauchly's test confirmed that the sphericity assumption was satisfied (W = 0.964, p = 0.119). Music genre had a significant effect on productivity (F(3,897) = 412.68, p < 0.001, partial η² = 0.58). Pop music produced the greatest productivity improvement (33.82%), followed by jazz (13.03%) and instrumental music (10.45%). Bonferroni comparisons showed that pop music significantly outperformed all other auditory conditions, whereas instrumental music did not differ significantly from the control condition. These findings demonstrate that appropriately designed auditory environments can enhance productivity during repetitive work. The study contributes to occupational acoustics by positioning music as an engineered environmental variable that supports human-centered industrial design and operational performance.

Open Access

Article

Article ID: 2029

Influence of parameter changes on honeycomb structure debonding detection based on band gap method

by Ye Yuan, Bin Liu, Chengyou Lei, Zhiguo Zhang

Sound & Vibration, Vol.60, No.5, 2026;

Honeycomb structures have been widely used in many industrial fields due to their excellent properties. However, it is always challenging to rapidly and accurately detect defects such as debonding in the structure, especially in the in-service situation. In response to this, we have proposed an acoustic testing method without coupling agents based on the acoustic band gap feature in the structure. However, the influence of test parameters such as signal excitation and reception on the band gap feature has not been comprehensively and thoroughly investigated, and the parameters have not been optimized. In this paper, the transmission frequency response (TFR) curves were measured, and the band gap features were investigated at different parameters. The results demonstrated that the band gap feature changes a little with the pressure between the probes and the specimen, the amplitude of the exciting signal, the sweep duration, and the detection direction. While it changes significantly with the exciting-receiving distance. Experimental results demonstrated that to form a stable band gap feature, the wave should propagate through at least three honeycomb unit widths before being received. Further analysis indicates that the defect resolution of the proposed method is about two honeycomb unit widths. This work can be used to select the proper detection parameters and further improve the reliability and efficiency of this technique.

Open Access

Article

Article ID: 4413

A practical approach for improving the robustness of MVDR beamformers

by Nguyen Thi Huyen Chau, Quan Trong The, Pham Van Ha

Sound & Vibration, Vol.60, No.5, 2026;

Microphone array (MA) owns the convenience of alleviating the background noise field, interference, and third-party speakers while preserving the original speech component with a high directivity index perspective. MA beamforming utilizes prior spatial information about the direction of arrival of useful signals, the characteristics of the surrounding noise field, the designed geometry of MA, and the obtained parameters after processing received array signals to achieve the advantages of speech enhancement and noise reduction. Minimum Variance Distortionless Response (MVDR) beamformer has the capability of attenuating the surrounding noise field, interference, or third-party talker while saving the original speech component of the desired talker at a specified location. However, under realistic recording scenarios, due to the complex and annoying situation, the movement of the talker during conversation, the error of internal settings for capturing the noisy mixture, the error of sampling frequency, the different time of starting recording of two microphones, the overall effectiveness of the MVDR beamformer is often degraded because of speech distortion and musical noise. In this article, the author proposed an efficient method for enhancing the robustness of the MVDR beamformer under complex and annoying situations. The numerical simulations have shown that the speech distortion was reduced to 5 dB, the musical and residual noise were suppressed to 15.2 dB, and the speech quality was increased from 12.1 to 12.9 dB.

Open Access

Article

Article ID: 4458

Meta-lens for acoustic concentration and enhanced sensing via transformation acoustics

by Botao Yang, Li Cai, KunSheng Xing, Shixin Yu, Huajie Hong

Sound & Vibration, Vol.60, No.5, 2026;

Detecting weak acoustic signals requires broadband energy concentration, but the acoustic power coupled into a device can be strongly curtailed by impedance mismatch at the inlet. Here, we develop a transformation-acoustics-based acoustic meta-lens in which a rectangular virtual domain is mapped to a trapezoidal physical domain, directing incident energy toward a narrow output aperture. In contrast to an air-filled trapezoidal horn with the same outer envelope, the meta-lens reshapes the wavefront through a spatially varying anisotropic mass-density tensor and an equivalent bulk modulus. A cubic-polynomial transition layer is introduced at the inlet to bridge the parameter jump between air and the anisotropic equivalent medium. Finite-element simulations from 200 to 3,000 Hz show positive sound transmission gain for the original design, with a mean value of 3.582 dB. With the transition layer, the mean gain increases to 5.470 dB, the minimum gain rises from 2.695 dB to 3.672 dB, and the mean inlet reflection coefficient decreases from 0.5644 to 0.3239, corresponding to a reduction of 42.6%. A genetic algorithm optimization of the lens length, inlet width, outlet width, and transition-layer thickness further increases the maximum gain from approximately 6.54 dB to 7.36 dB and the minimum gain from approximately 3.67 dB to 4.14 dB. These results indicate that inlet impedance grading and geometric optimization can work together to provide more robust broadband acoustic concentration for weak-signal sensing.

Open Access

Article

Article ID: 4407

Acoustic characterization and modeling of padel courts in urban residential environments

by Aracelly Núñez-Naranjo, Jose Gabriel Vasquez, Paulina Ayala, Marcelo V. Garcia

Sound & Vibration, Vol.60, No.5, 2026;

Padel courts are now common in many residential and mixed-use projects, but the published measurement base for their outdoor noise impact is still small. Recent work has flagged siting conflicts and padel-related acoustic concerns, yet few studies place padel and tennis side by side under the same site conditions. This paper addresses that gap through field measurements and acoustic modeling at one mixed-use development in Abu Dhabi, United Arab Emirates. A padel court and a tennis court were each recorded for a single 15-minute period, and the resulting levels fed an outdoor propagation model. At 10 m, the padel court reached LAeq = 64.2 dB(A) and LAmax = 71.3 dB(A), against LAeq = 58.4 dB(A) and LAmax = 63.6 dB(A) for tennis. Padel showed stronger octave-band content at mid- and high frequencies, consistent with ball-wall impacts and reflections off its rigid glass and metal enclosure. These levels were then carried into a CadnaA model built on ISO 9613-2 to trace propagation toward the nearest residential facades. With 4 m barriers around the padel courts, predicted facade levels at the most shielded positions fell by 4 to 5 dB(A). A single site and one recording per sport bound these conclusions: they describe a case study rather than a general emission standard for padel. What the data do provide is a matched padel-versus-tennis comparison and a worked example of how a small field set can steer acoustic planning early in residential design.

Open Access

Article

Article ID: 4224

Weak fault feature extraction and system fault analysis under strong noise

by Tiejun Cui, Zijian Cui, Shasha Li

Sound & Vibration, Vol.60, No.5, 2026;

To tackle the intractable problems including weak fault feature extraction and evolution uncertainty quantification for complex systems in strong noise environments, a novel method for weak fault diagnosis and evolution analysis is proposed. This method integrates the fuzzy structured element (FSE), cloud model (CM), and Space Fault Network (SFN). The method centers on adaptive wavelet denoising, fault feature cloudification, and SFN probability propagation. The fault signal under strong noise is reconstructed by optimizing the wavelet threshold with the FSE. The uncertainty encapsulation of the peak factor of fault features is realized based on the CM to establish the feature CM. The fault event topology is constructed relying on the SFN. The quantitative transfer of uncertainty in the fault evolution is achieved combined with cloud algebra. Verified by the inner ring pitting fault of axle box bearings, the results demonstrate that the proposed method can extract the fault characteristic frequency of 250.5 Hz. The derived fault probability CM (0.680, 0.059, 0.023) accurately quantifies the system risk level. This result is consistent with the actual fault evolution law in engineering practice. This method provides technical support for early fault warning and maintenance of complex industrial system. Furthermore, comparative experiments confirm its superiority over traditional methods in noise suppression and feature retention. Parameter analysis is also discussed to improve engineering generalization.

(This article belongs to the Special Issue Vibration and System Fault Analysis)

Open Access

Article

Article ID: 4180

Audio signal approximation and fuzzy logic-based acoustic noise-risk assessment using Fourier–Dirichlet analysis and hyperbolic series representations

by Yogeesh Nijalingappa, Asokan Vasudevan, Soon Eu Hui, Zetty Pakir Mastan, Choo Wou Onn, Mohammed Almakki

Sound & Vibration, Vol.60, No.5, 2026;

This paper presents an acoustics-oriented study that combines classical Fourier–Dirichlet signal approximation with a fuzzy logic-based noise-risk interpretation layer. The harmonic-analysis part revisits Fourier series for periodic and quasi-periodic audio waveforms under classical Dirichlet conditions and restates these conditions in a form that is practically checkable on sampled audio segments; no new convergence theorem is claimed. A complementary hyperbolic-series representation is used as an illustrative analytical tool for discussing compact representations of selected waveform classes. The applied contribution of the paper is a Mamdani fuzzy inference system that converts uncertain acoustic measurements into an interpretable Noise-Risk Index using A-weighted equivalent sound level, daily exposure duration, and source–receiver distance. The fuzzy model uses triangular/trapezoidal memberships, an interpretable rule base, min–max inference, and centroid defuzzification. To show the practical usefulness in sound and vibration practice, one waveform-reconstruction example and a twelve-scenario acoustic-risk dataset with regard to traffic, workshop, generator room, and public address contexts are reported in the study. The resulting fuzzy system generates a range of risk scores from 22 to 92, lying within the safe, caution, high, and critical level categories and depicts smooth transitions as we approach decision boundaries where a crisp threshold can often be challenging to decode. This work thus establishes Fourier analysis as the underlying level for acoustic signals and fuzzy inference as a decision-support level in the context of uncertainty-based exposure assessment. The current coupling is linear instead of feature-driven: the Fourier-based signal description forms the basis for exposure descriptors, and the fuzzy system processes these descriptors given uncertainty.