Vol. 60 No. 2 (2026): in progress

Open Access

Article

Article ID: 3856

Configuration and fault location method for network with limited traveling wave recorder based on hypothetical fault

by Yongqi Liu, Jianbo Nie, Luyao Xie, Chao Zhu, Youbing Zhang

Sound & Vibration, Vol.60, No.2, 2026;

Fault location is crucial for enhancing power supply reliability and shortening power outage duration. Traditional power frequency-based fault location methods are limited by the distributed generation integration and the complex grid topology of renewable energy systems, while traveling wave (TW) fault location technology has become a research hotspot due to its high accuracy and fast response. The mainstream TW methods (single-ended, double-ended) have inherent drawbacks. This paper proposes a hypothetical fault-based fault location method: Acquire data from each sensor, obtain the time information of wavefronts via the db6 wavelet transform, and then construct a time matrix accordingly. Randomly assume a fault point, calculate the TW arrival time difference matrix between the hypothetical fault (based on shortest-path propagation) and the actual fault, derive the time information difference degree by comparing the two matrices, and iteratively update the hypothetical fault point via an optimization algorithm until the matrices coincide. Meanwhile, based on the hypothetical fault method, the mathematical expressions for the line fault observability constraints are derived, the optimal configuration model of traveling wave recorders in the network is established, and the solution is completed. This method achieves accurate fault location, assists in judging whether the network is measurable, and further enables the design of a planning and configuration model to realize the optimal configuration of TWRs under the condition of full-network fault observability without analyzing and deconstructing the network structure. Simulations are conducted on the IEEE 30-bus and IEEE 57-bus systems, respectively, to verify the method’s effectiveness.

Open Access

Article

Article ID: 3872

A PSO-based isogeometric singular boundary method for shape optimization of sound barriers

by Qingya Zhang, Fajie Wang, Hanqing Liu, Lin Qiu, Xingxing Yue

Sound & Vibration, Vol.60, No.2, 2026;

In this paper, we propose a novel meshless method for shape optimization of sound barriers by combining the Burton-Miller singular boundary method, the isogeometric analysis (IGA), and the particle swarm optimization (PSO). The method addresses th+e spurious frequency issue by introducing the Burton-Miller formulation. The geometric features of sound barriers are accurately described by means of non-uniform rational B-splines, while the PSO algorithm is adopted as the optimization solver. The proposed method only requires the external boundary information of sound barriers. It constructs sound barrier models using NURBS (Non-Uniform Rational B-Splines) and achieves the optimal layout of boundary control points by optimizing the objective function. This method features three distinct advantages: (1) It integrates the IGA technique, enabling the generation of optimization models with only control points; (2) it eliminates the need for sensitivity analysis and avoids tedious mathematical derivations, allowing for the direct shape optimization of sound barriers with complex geometric structures; (3) its numerical calculation process naturally obviates the inherent mesh generation requirement of the finite element method and completely circumvents the common singular integral calculation in the boundary element method. It can seamlessly integrate with computer-aided design systems, bringing convenience to engineers. Numerical experiments confirm its accuracy and effectiveness, showing its obvious advantages as a simple and efficient new way for sound barrier structural optimization design.

Open Access

Article

Article ID: 3941

Multi-criteria decision-making for sound and vibration reduction platforms for financial and marketing optimization in energy

by Alexey Mikhaylov, Murat Ikramov, Nilufar Nabiyeva, Boris Sokolov, Wenyi Zhang, Valentin Nazarov, Mukhabbat Ergasheva, Sardar Turaev, Dilnoza Meilyeva, Daria Dinets, Yuri Sotskov, N. B. A. Yousif

Sound & Vibration, Vol.60, No.2, 2026;

The integration of Artificial Intelligence (AI) in energy infrastructure has created a new class of specialized intermediaries for environmental control, yet their opaque decision-making poses regulatory challenges. This paper proposes a novel regulatory framework for specialized sound and vibration platform operators in the energy sector and introduces a multi-criteria decision-making (MCDM) methodology to support oversight. The methodology integrates expert neuro-behavioral data, captured via Facial Action Coding System (FACS), with a quantum picture fuzzy rough set extension and the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method. The application is demonstrated through a case study of a 250 MW combined-cycle gas turbine power plant, where the goal is to select optimal noise and vibration control technologies. The analysis assesses five key technologies against compliance parameters: algorithmic transparency, data governance, system reliability, operational accountability, and consumer protection. The proposed Neuro-Quantum Picture Fuzzy Rough MCDM model achieved a forecast accuracy of 0.987 for system performance, substantially outperforming Long Short-Term Memory (LSTM (0.876)), Recurrent Neural Network (RNN (0.575)), and AutoRegressive Integrated Moving Average (ARIMA (0.551)). The primary contribution is to initiate professional dialogue on governing AI-driven energy intermediaries, balancing technological innovation with energy stability, security, and consumer welfare. The paper recommends a comprehensive regulatory framework for a new class of energy intermediaries for financial and marketing optimisation called specialised sound and vibration platform operators.

(This article belongs to the Special Issue Intelligent Systems in Sound and Vibration Analysis)

Open Access

Article

Article ID: 3889

Design optimization and comparative evaluation of oval and toroidal propeller geometries versus a conventional propeller

by Rayn Nasr, Majd Shreif, Enrico Abou Jaoude, Celine Ahmar, Jihad Rishmany

Sound & Vibration, Vol.60, No.2, 2026;

Drones are increasingly used in delivery, aerial imaging, search and rescue, and agricultural monitoring due to their low cost, low emissions, and ability to reach hazardous or hard-to-access locations. However, a major limitation is the high noise produced by conventional propellers as they interact with the air. Recently, toroidal propellers have emerged as a promising alternative, offering aerodynamic benefits that can reduce noise while maintaining or improving thrust generation. This study investigates the performance of toroidal propellers, both circular and oval, compared to a conventional propeller. The assessment focuses on thrust production, efficiency, and noise emission using both experimental testing and numerical simulations. Results indicate that toroidal propellers provide notable advantages. Experiments showed approximately a 15 dB noise reduction and up to a fourfold increase in thrust relative to the conventional design. Simulations revealed that the oval toroidal propeller achieved the lowest noise level at 29.54 dB, while the circular design produced higher noise but delivered the greatest thrust, reaching 44.08 N. Overall, the study demonstrates that toroidal propellers can significantly enhance drone performance. The optimal choice between oval and circular designs depends on specific mission requirements, balancing noise reduction against thrust demand.

Open Access

Article

Article ID: 3837

Bifurcation in compressible moving fluids and suppressing atmospheric turbulence of aircraft-flow amplifies sound

by Zuwen Qian

Sound & Vibration, Vol.60, No.2, 2026;

Quasi-accumulation solutions for acoustic waves in a compressible moving fluid are obtained by applying the Lagrange parameter variation method to solve the Lighthill equation. The results demonstrate that nonlinear interactions lead first to period-doubling, followed by odd multiple half-period bifurcations, with all-order sub-harmonics subsequently generated. The amplitudes of these sub-harmonics depend not only on the acoustic Mach number but also on the Mach number of the flow. The latter result indicates that the acoustic wave has been amplified by the momentum of the flow. Furthermore, the relationship between the amplification gain of sub-harmonics and flow velocity is a polynomial function of flow-sound Mach number ratio M/m. If the kinetic energy gained through momentum amplification exceeds the energy loss due to the acoustic attenuation, a chain-reaction of the period-doubling followed by the odd multiple half-period bifurcation can be sustained. As the order number of the approximation  increases, the number of degrees of freedom in the flow increases infinitely and the leading terms of the amplitudes for the generated sub-harmonics which are proportional to  approach to infinity, whereand , k and  are Mach number for flow and sound, the wave-number and absorption coefficient, respectively. The obtained results also indicate that the appropriate control parameter for transitioning from bifurcation to chaos should be  instead of Reynolds number. This paper also demonstrates that in the moving fluid sound waves can be amplified through nonlinear interactions, particularly, the first sub-harmonic generates, thereby explaining the experimental results we discovered decades ago. Finally, a potential strategy for suppressing aircraft-induced atmospheric turbulence is proposed based on the present theoretical findings.

Open Access

Article

Article ID: 3959

Study on the resistance and vibration response of projectiles penetrating into water-bearing soil

by Yanan Du, Guanglin He, Xinmin Li

Sound & Vibration, Vol.60, No.2, 2026;

In low-speed impact scenarios, the initiation of mechanical fuzes heavily depends on the reaction force generated during projectile impact, where the projectile penetration resistance plays a critical role in determining the reliability of initiation and damage accuracy. To address the challenges in accurately predicting projectile resistance during penetration into water-bearing soil, a simplified calculation model is developed by integrating theoretical derivation, numerical simulation, and experimental verification. The model explicitly considers the coupling effects of incident velocity, impact angle, and soil moisture content. Numerical simulations of projectile penetration into water-bearing soil under different incident velocities and angles reveal that, with a fixed impact angle, the overload peak increases as the incident velocity rises. Moreover, for a constant incident velocity, the timing of the overload peak is advanced with increasing impact angle, and the maximum resistance is positively correlated with the projectile diameter. Experimental results confirm that the error between the model predictions and the measured data is within 10%, indicating high reliability and applicability. In addition, this study synchronously investigates the vibration response characteristics during the penetration process, revealing the intrinsic coupling mechanism between vibration, resistance evolution, and transient overload as well as the multi-frequency and time-frequency characteristics of vibration. This research provides valuable support for the design of mechanical fuzes based on reaction force triggering mechanisms and the evaluation of projectile damage effects in impact vibration scenarios, and also offers reliable theoretical and experimental basis for the optimization of weapon systems and their mechanical performance under dynamic conditions.

Open Access

Article

Article ID: 3869

Nonlinear damping identification using extended continuous wavelet transform and long-short term memory: Application to a spur gear pair system

by Nourhaine Yousfi, Fatma Mejdoub , Ali Akrout, Lassaad Walha, Mohamed Haddar

Sound & Vibration, Vol.60, No.2, 2026;

Damping significantly affects the dynamic analysis of spur gear pair systems. The identified damping ratios may suffer from instability owing to many reasons, such as time-varying conditions and nonlinear effects. Long-short-term memory (LSTM) has been developed for damping model identification in systems with nonlinear behavior. However, owing to the poor quality of the input data, the identification results may not be reliable. In this regard, this study proposes a hybrid technique based on the Continuous Wavelet Transform (CWT) and LSTM methods. The major novelty of this study is the utilization of the time-frequency information provided by the CWT as the input data. Therefore, the LSTM network was fed these extracted features to enhance noise attenuation and improve the robustness and stability of nonlinear damping identification. Thus, the CWT technique is used as a preprocessing tool for the observed signals, enhancing the data quality by reducing the influence of noise. To verify the effectiveness of the proposed CWT–LSTM approach for damping identification, CWT representations of the simulated spur gear pair system response were used in a series of analyses. The numerical results indicate that the combined CWT–LSTM approach provides more reliable and accurate nonlinear damping estimation than the conventional LSTM model. This methodology has a strong potential for the accurate identification of damping in gear transmission systems.

Open Access

Article

Article ID: 3950

A fuzzy-neuro approach to predictive maintenance using vibration signature classification

by Asokan Vasudevan, Mohammed El Khider, Yogeesh N, Puspanathan Doraisingam, Khan Sarfaraz Ali, A. Sathishkumar

Sound & Vibration, Vol.60, No.2, 2026;

Vibration-based predictive maintenance must remain reliable under variable speed/load and noise while delivering actionable, interpretable decisions. We propose a fuzzy-neuro framework that maps windowed vibration segments to class decisions and a calibrated risk score with uncertainty. Given a sampled signal , overlapping windows  are formed and encoded into a learned signature . Physics-informed indicators  (e.g., RMS, kurtosis, band-energy and short-horizon trend) are fused with  to form . An end-to-end neuro-adaptive Takagi-Sugeno-Kang (TSK) layer produces a transparent maintenance risk  enabling rule-level explanations via dominant firing strengths . To support safe decision-making near thresholds, we estimate an interval risk  from predictive samples  using quantiles ,  and width as confidence. Using leakage-safe, unit-aware temporal splitting, experiments on public rolling-bearing benchmarks achieve 0.956 accuracy, 0.952 macro-F1, and 0.941 MCC, while the full model improves calibration and yields sharper risk intervals (mean width  0.132), translating classifier evidence into auditable "monitor/schedule/urgent" actions. These results indicate that the proposed framework is accurate, interpretable, and decision-ready for predictive maintenance.

Open Access

Article

Article ID: 3995

Predictive analysis of industrial safety based on noise, vibrations and machinery reliability

by Henry Nelson Aguilera Vidal, Ruth Isabel Torres Torres, Irene Teresa Bustillos Molina, Eudes Martínez Porro

Sound & Vibration, Vol.60, No.2, 2026;

This study develops a predictive approach for assessing industrial safety risk through the integrated analysis of physical indicators associated with machinery operation, specifically noise, vibration, and mechanical reliability. The research was conducted in industrial environments characterized by the continuous operation of rotating equipment, including motors, pumps, compressors, and transmission systems. A dataset of approximately 18,000 operational records collected over a 12-month period was analyzed, incorporating acoustic measurements, vibration parameters, machinery condition, and records of potentially unsafe operating states. Equivalent sound pressure level (Leq), Root Mean Square (RMS) acceleration, and crest factor were calculated as the main dynamic indicators, and these variables were normalized and integrated into an Industrial Risk Index (IRI) designed to represent the operational safety state of the equipment. Subsequently, a logistic regression model was developed to classify operating conditions into safe or risk states. The results showed that the combined use of acoustic and vibration indicators improves the identification of hazardous conditions compared with isolated metrics. The predictive model achieved strong classification performance, with an accuracy of 0.88, sensitivity of 0.86, specificity of 0.84, and an AUC-ROC of 0.90, demonstrating a high capacity to distinguish safe operation from risk scenarios. Sustained increases in noise and vibration, particularly when associated with signs of mechanical degradation, were found to precede unsafe states. The findings confirm that integrating dynamic condition monitoring with predictive analytics strengthens failure anticipation and supports preventive decision-making, providing a technically interpretable basis for more proactive industrial safety management systems.

Open Access

Article

Article ID: 3923

Modal FEA-EMA CrossMAC analysis of a Bell UH-1H helicopter tail rotor blade using FEA software and open source algorithms

by Daniel J. Winarski, Marc D. Lamparelli, Tyson Y. Winarski

Sound & Vibration, Vol.60, No.2, 2026;

Our challenge was the data integration between the output of two disparate commercial software packages, one for analytical finite element analysis and the other for experimental modal analysis. Our primary objective was the augmentation of two existing free open source subroutines with our own programming to create a versatile analysis tool capable of calculating the Cross-Application Modal Assurance Criterion (CrossMAC) comparison of mode shapes between experimental modal analysis and analytical finite element analysis of a stationary tail rotor blade of a Bell UH-1H helicopter. The key contribution of our work was the creation of an original GNU Octave main program with four original subroutines, along with the two existing open source subroutines and one modification to one of these existing subroutines, to integrate the experimental modal analysis done using Spectral Dynamics STAR7 software and the analytical finite element analysis using Mecway. Both the STAR7 and Mecway commercial software packages were chosen because each permitted access by our GNU Octave program to critical node locations and mode shape data for three out-of-plane flapping modes as well as a torsional mode of vibration. By changing from a fixed to an elastic support, and enabling grid refinement, our analytical modal frequencies agreed well with our experimental ones, giving a Pearson correlation of 99.1% between our experimental and analytical data. Our open source software framework and methodology offers an extensible and robust approach for validating experimental modal data against analytical finite element modeling, with direct applicability to a broad diversity of vibration applications.

Open Access

Article

Article ID: 4198

Coupling vibration analysis for aerial inspection robot landing on transmission line under wind disturbance

by Xiaodong Zhang, Haiming Shen, Ahmad Bala Alhassan, Haibo Xu

Sound & Vibration, Vol.60, No.2, 2026;

When the high-voltage transmission line inspection robot (HVTIR) lands amid wind disturbances, line vibrations significantly affect system stability. Therefore, this paper proposes a contact-force control strategy for HVTIR landing based on varying wind speed conditions: a nonlinear contact-force model is preferred for vibration reduction under low wind speeds, while a linear contact-force model enhances stability under medium and high wind speeds. Using a composite wind field model, the vibration bending beam model of the transmission line and the mass-stiffness-damping coupling model of the robot under wind disturbance were developed. An experimental verification system was established using wireless acceleration sensors. Results showed that under a typical low wind speed of 2 m/s, the exponential nonlinear contact-force strategy controlled vibration at 0.64 m/s², which was 90.1% more effective than direct loading. At a typical medium-high wind speed of 6 m/s, the experimental peak value using the linear contact-force strategy was reduced by 5.7% compared to the ideal peak value; the experimental RMS was reduced by 0.36%, and the linear contact-force strategy significantly reduced coupling vibrations. These experimental results demonstrate the reliability and applicability of the proposed control strategy, providing theoretical and technical support for the stable and rapid landing of the inspection robot.

Open Access

Article

Article ID: 3944

A computational and experimental study of flow-induced vibration and structural dynamics in topology-optimized redox flow battery channels

by Jacer Hamrouni, Leila Abdelgader, Chafaa Hamrouni

Sound & Vibration, Vol.60, No.2, 2026;

Unlike conventional flow field designs that prioritize electrochemical performance at the expense of mechanical reliability, the proposed framework uniquely embeds vibration control as a co-objective within the topology optimization process, demonstrating for the first time that mass transfer enhancement and flow-induced vibration suppression can be achieved simultaneously. This dual-objective innovation, validated by a 41% reduction in vibration velocity and a 23% improvement in reaction rate, establishes a new paradigm for integrating structural dynamics into electrochemical system design, directly addressing a critical gap in grid-scale energy storage reliability. This study introduces a vibration-aware topology optimization framework for the flow fields of vanadium redox flow batteries (VRFBs), targeting the mitigation of flow-induced vibration without compromising electrochemical performance. We demonstrate that optimized interdigitated flow fields fundamentally alter the fluid-structure interaction, suppressing the unsteady vortex shedding that drives mechanical excitation. Experimental validation on laboratory-scale prototypes confirms a 41% reduction in root-mean-square vibration velocity alongside a 23% improvement in electrochemical reaction rate. This work establishes a validated, CAE-driven pathway to embed vibration engineering into the earliest stages of electrochemical system design, addressing a critical gap in the development of reliable, next-generation renewable energy infrastructure.

Open Access

Article

Article ID: 4071

Uncertainty-aware order tracking using interval-valued spectral estimators

by Sulieman Ibrahim Mohammad, Yogeesh N., Mustafa Abdullah, Rosemary Varghese, Asokan Vasudevan, Ashalatha K.S.

Sound & Vibration, Vol.60, No.2, 2026;

Order tracking is central to diagnosing rotating machinery under variable speed; however, both tachometer-based and tacholess pipelines typically return point estimates of the order spectrum and therefore under-represent uncertainty due to speed estimation error, phase integration drift, resampling jitter, and finite-record spectral variance. This study develops an uncertainty-aware order tracking framework in which the diagnostic output is an interval-valued order power spectral density (PSD) envelope. The angular speed is modeled as an unknown-but-bounded process , which induces bounds on angular position . These bounds are propagated through angle-domain resampling and a Welch-type spectral estimator to obtain order-wise PSD bounds , together with interval band metrics formed by order-band integration and log-level reporting. A numerical run-up case study with physically plausible harmonic content and broadband noise shows that low-order components can remain stable in peak location, whereas higher orders exhibit measurable peak-shift intervals consistent with phase-warp amplification under bounded mapping uncertainty. The results also quantify a practical coverage-width trade-off: fast endpoint envelopes can lose inclusion under larger uncertainty, indicating when multi-map sampling or tighter set membership bounding should be applied. Overall, the proposed interval-valued spectral estimators enable decision-relevant reporting of uncertainty for order-based health indicators and reduce the risk of overconfident fault declarations in variable-speed condition monitoring.