Sound & Vibration

The three-dimensional aircraft-runway coupled vibration response based on double-layer plate for semi-rigid base

2024-12-10T06:45:00+00:00

As global aviation expands, airport infrastructure faces growing pressure to accommodate larger and heavier aircraft. A key challenge is managing the vibration interaction between aircraft and runway during takeoff, taxiing, and landing, which affects runway durability and aircraft safety. While most research focuses on the surface layer, the role of the semi-rigid base, commonly used in China, is often overlooked. This study addresses this by analyzing the semi-rigid base’s role in three-dimensional aircraft-runway coupled vibrations. Taking into account the semi-rigid base layer and the subgrade shear stiffness, the study establishes a three-dimensional aircraft-pavement coupled model, using the measured roughness data from Shanghai Pudong International Airport as model input. The new explicit integration method is employed to solve the model. The study examines how structural parameters influence dynamic responses like load factors, strain, and displacement. Numerical simulations reveal that the support function of the semi-rigid base and the shear stiffness of the subgrade play a crucial role in improving runway stiffness and performance. The impact of aircraft taxiing speed is also significant. Specifically, increasing the base layer modulus from 1.50 GPa to 2.50 GPa results in a significant strain reduction (from 16.5 με to 12.8 με), and increasing the base thickness reduces strain by up to 17.8%. Moreover, enhancing the subgrade shear stiffness leads to improved resistance to deformation, further reducing strain and displacement. Additionally, as taxiing speed increases, the mean dynamic load coefficient decreases due to the lift generated by the aircraft, while strain fluctuations in the pavement increase. However, changes in pavement structure have minimal impact on aircraft center-of-gravity acceleration. This research provides critical insights for optimizing aircraft and runway design, enhancing safety, and extending runway lifespan through a coordinated focus on the surface layer, semi-rigid base layer, and subgrade with shear stiffness.

Adaptive parameter-optimized NLM algorithm to denoise vibration signals of hydropower units

2024-12-10T06:47:08+00:00

Monitoring and diagnosing the operating state of hydropower units is crucial, which becomes a hot research topic in the industry. the vibration signals provide a reliable indication to detect the abnormal working conditions of hydropower units. however, the vibration signals is affected by the environment noise inevitably, making it difficult to truly reflect the operating state of hydropower units. the non-local means (NLM) algorithm is proved to be effective in denoising the vibration signals, however, whose parameters depend on the human experience, which hinders its application and development. in the present work, based on the Bayesian parameter optimization (BPO), the parameters of NLM are set adaptively, the BPO-NLM denoising algorithm is proposed. by conducting the simulation, the denoising effectiveness of BPO-NLM is improved remarkably than that of the traditional NLM. at different snr, RMSE of the signal denoised by BPO-NLM is much smaller than that of the traditional NLM, while snr of the signal denoised by BPO-NLM is much larger, namely, the effective component of the signal is enhanced, while the noise component is suppressed.

A framework for hydro-power vibration dynamic measurement and decision-making based on natural language processing

2024-12-10T06:48:19+00:00

The safety management construction of the hydro-power units is necessary to improve the level of engineering quality and economic beneﬁts. However, the traditional hydro-power units lack a uniﬁed safety management decision-making platform, making knowledge retrieval and recommendation difficult. To improve the safety management level of the hydro-power units, the present article provides a framework of intelligent query and auxiliary decision-making in the traditional hydro-power operations. Based on the natural language processing technologies, the auxiliary decision-making platform is composed of three parts, namely, deep semantic similarity model, bidirectional long short-term memory network model and neural collaborative ﬁltering algorithm. Lastly, a case study is conducted, and the auxiliary decision-making platform can provide the user the relevant knowledge guidance to the problem, including defect causes, handling methods, dangerous point analysis and operation preparation, which is helpful to improve the safety management level of the hydro-power units.

A remaining useful life prediction method based on CNN-BiLSTM feature transfer in a high-noise environment

2024-12-10T06:42:17+00:00

Prognosis and health management (PHM) is a comprehensive technique for fault detection, prediction, and health management. However, achieving accurate predictions of remaining useful life (RUL) under complex working conditions such as is still High-Noise Environment a challenge. Therefore, this paper proposes a feature transfer model based on Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory Neural Networks (BiLSTM) to predict RUL. In the feature extraction stage, On the basis of signal decomposition using local mean values，CNN is used to extract the degradation features. Secondly, the health factors are constructed by monotonicity and correlation to filter the features again. Thirdly, it uses BiLSTM to model the time series data in the RUL prediction stage. Then, it introduces the transfer learning algorithm to solve the problem of different data distribution due to the inconsistent working conditions of mechanical equipment data and estimates the confidence interval of the RUL by the Monte Carlo simulation technique. Finally, the effectiveness of our constructed framework via CNN-BiLSTM model on a publicly available degradation simulation dataset of turbine engines.

Experimental and theoretical analysis of nonlinear acoustic characteristics of perforated acoustic liners

2024-12-10T06:38:53+00:00

Perforated acoustic liner is one of the key components commonly used to suppress combustion oscillation in afterburners of military aircraft engines. The acoustic pressure generated by combustion oscillation is relatively high, and the nonlinear characteristics of these liners are significant. This paper employs both experimental and theoretical methods to study the nonlinear absorption coefficient and acoustic impedance of perforated acoustic liners in the range of 0 to 200 Pa. The results indicate that nonlinear effects increase the primary absorption frequency up to 70 Hz as the acoustic pressure amplitude rises from 2 Pa to 200 Pa. For small acoustic pressure amplitudes, it is recommended to use acoustic liners with smaller perforations, whereas for larger amplitudes, the perforation diameter should be increased (d > 4 mm). For liners with a perforation diameter of 1.1 mm, the inclination angle has little effect on the absorption coefficient. When the acoustic pressure amplitude is small, the acoustic liner has an optimal backing cavity height. However, at larger acoustic pressure amplitudes (200 Pa), increasing the backing cavity height is beneficial for the absorption coefficient. When the backing cavity height increased from 20 mm to 130mm, the absorption coefficient more than doubled. The nonlinear acoustic characteristics of perforated acoustic liners can provide valuable insights for the design of anti-vibration screens in afterburners.

Finite element modeling and vibration control of composite beams with partially covered active constrained layer damping

2024-12-10T06:39:25+00:00

This paper analyzes the active vibration control of sandwich beams using Active Constrained Layer Damping (ACLD). The finite element model of the viscoelastic sandwich beam combines finite element method with the Golla Hughes McTavish (GHM) model, using a 2-node 8 degrees freedom element. The finite element model is validated by the first four natural frequencies of the model in the literature, and the governing equations of sandwich beams are generated based on the Hamiltonian principle. The physical space dynamic condensation technique and state space complex mode decoupling method are employed to reduce the order of the structural model. This is necessary because free degree of the finite element model is too high to directly control the structure’s vibration. It shows that the fundamental physical characteristics of the structure may remain largely unchanged while the physical and state spaces are jointly reduced. We investigated how the positions and coverages of ACLD patches impact on the active control, vibration damping of viscoelastic sandwich beams.

Renovation of the reverberation room at Ocean University of China based on ODEON simulation

2024-12-10T06:36:12+00:00

The reverberation room is a crucial laboratory for determining the sound absorption properties of materials. The reverberation room at the Laoshan Campus of Ocean University of China lacks complete acoustic design. Using computer-aided simulations, defects in the sound field can be clearly revealed and the design proposals’ effectiveness can be pre-validated. This study focuses on renovating the reverberation room by conducting acoustic performance tests and constructing a three-dimensional model. Leveraging the advantages of ODEON for simulating sound fields, it analyzes the uniformity of sound field diffusion, considering not only reverberation time distribution but also linear decay curves and deviations in sound pressure level distribution. Subsequently, the room undergoes simulated renovation in accordance with national standards of China and international standards, and diffusion body design schemes, including semi-cylindrical and semi-conical hard wall diffusers and suspended plexiglass diffusers, are compared through simulations to arrive at the final optimized renovation plan. The simulations show that the deviation in sound field uniformity can be reduced to less than 1.5 dB after renovation, and the reverberation time is also significantly extended. These findings can inform the actual renovation of the Laoshan Campus reverberation room and serve as a reference for other reverberation room renovations and indoor acoustic simulations.

Frequency formulation for nonlinear oscillators (part 1)

2024-12-10T06:46:07+00:00

The perturbation method is a prevalent approach for nonlinear oscillators; however, the outcomes are only applicable to situations with weak nonlinearity. Other analytical methods, such as the variational iteration method and the homotopy perturbation method, can yield a satisfactory approximate solution; however, each method necessitates the completion of multiple calculations. Hereby is recommended a one-step frequency formulation for nonlinear oscillators, and this part 1 focuses itself on odd nonlinearity.

Focusing properties of linear phase-conjugate array

2024-12-10T06:52:52+00:00

Phase conjugation generates a backpropagating field that refocuses on the original source, rendering it an effective technique for sound source localization. In addition, linear arrays are widely used in underwater source localization. Therefore, investigating the focusing properties of a linear phase-conjugate array is crucial. This study analyzes the backpropagating field produced by phase-conjugate arrays, proposing indicators for focus bias (FB), focal point size (FS), and sidelobe interference (SLI) to quantitatively characterize these properties. Numerical simulations of the focusing properties of monopole phase-conjugate (PCM), dipole phase-conjugate (PCD), and perfect phase-conjugate (PCP) arrays for a single-frequency point source are conducted to evaluate the effects of array aperture, element spacing, source-to-array distance, and source bias on the different focusing properties of each array. The results indicate that focus bias and focal point size are primarily associated with the array angular aperture (determined by array aperture, source-to-array distance, and source bias); element spacing is the primary factor influencing sidelobe interference. Under identical array configurations, the focus bias of the three phase-conjugate arrays is similar, while the PCM array exhibits the smallest focal spot size, and the PCD array displays the least sidelobe interference.

Acoustic multi-objective optimization of porous media properties of a diesel particulate filter

2024-12-10T06:53:57+00:00

Studies on emission control systems have proliferated because of increasing environmental regulations in recent decades. One of the most important emission control systems in vehicles is the Diesel Particulate Filter (DPF). DPFs are important for not only the harmful emission of soot particles but also acoustic emissions. In this study, the acoustic behavior of DPFs was investigated. The study presents an acoustic multi-objective optimization of the porous media properties of a DPF. The multi-objective optimization was performed using the Non-Dominated Sorting Genetic Algorithm (NSGA-II) to obtain an optimum DPF design. In this study, we aimed to maximize the acoustic transmission losses (TL) of the DPF and minimize the pressure drop according to the porous media properties. The DPF wall permeability, channel width, channel wall thickness and channel number were chosen from the porous media properties as design variables for the optimization problem. Test studies have been conducted to validate the mathematical model utilized in optimization. Following these investigations, it has been concluded that the mathematical model, verified through experimental research, is now considered a viable model for resolving the optimization problem. As a result, an optimum DPF design that provides both objective functions was proposed.

Acoustic assessment in urban residential environments: A GINI-OOB approach

2024-12-10T06:40:30+00:00

Urban sustainable development faces significant challenges, with low Resident Value Perception (RVP) acting as a major barrier to the rapid growth and sustainability of cities. This study aims to identify the key factors influencing RVP and assess their impacts, focusing on Wuhan as the case study. An RVP indicator system is developed, integrating three dimensions, and the Fuzzy Comprehensive Evaluation-Attribute Hierarchy Model (FCE-AHM) method is employed to calculate the RVP index. Additionally, a novel GINI-out-of-bag (GINI-OOB) coupling assessment method is introduced to determine the influence of each indicator, using data from Wuhan’s 2022 social satisfaction survey in China. Special emphasis is placed on the relationship between these factors and the acoustic environment. The research findings highlight the following: (1) The proposed methodology effectively identifies the key factors influencing residents’ value perceptions and quantifies their levels of influence; (2) Hospital waiting times, housing price acceptability, and parking management emerge as the top three factors affecting residents’ value perception, with a combined GINI-OOB index score of 0.4914. Notably, parking management has a significant influence, directly exacerbating traffic noise issues. These factors collectively impact the acoustic environment, thereby influencing residents’ quality of life and overall satisfaction. This study introduces an innovative theoretical framework for evaluating urban sustainability, offering valuable insights for enhancing the assessment of residents’ value perceptions and supporting policy recommendations aimed at optimizing urban acoustic environments.

Clear imaging beamforming method for the noise source identification in car cabin

2024-12-10T06:41:56+00:00

Noise in car cabin has a close relationship with ride comfort and noise control plays a key role in automobile product design. The prerequisite of noise control is to accurately identify noise sources. Due to the advantages of recording comprehensive sound field information and achieving panoramic source identification, beamforming with spherical microphone array is suitable for interior sound source identification. However, classic spherical harmonics beamforming (SHB) and filter and sum (FAS) suffer from wide mainlobes and serious sidelobe contamination. This paper proposes clear imaging beamforming method, which repeatedly removes the independent contribution of each source from SHB output based on coherence between sidelobe and mainlobe to improve imaging clarity. Simulations and experiments demonstrate that the proposed method has much clearer imaging than SHB and FAS, and could effectively identify the noise sources in car cabin.

The impact of Human-AI integration on enterprise digital transformation: The mediating role of enterprise technological innovation

2024-12-10T06:40:33+00:00

The integration of Human-AI systems is swiftly reshaping the digital transformation and technological innovation landscape within Chinese enterprises. This paper investigates the influence of Human-AI integration on the process of enterprise digital transformation, with enterprises technological innovation acting as a mediating factor. Utilizing Confirmatory Factor Analysis (CFA) and Partial Least Squares Structural Equation Modeling (PLS-SEM), the study constructs and validates a research model that demonstrates how collaboration between Human-AI integration accelerates enterprise digital transformation while fostering enterprise technological innovation. Moreover, drawing on electric survey-based data from the Chinese technological firms, we performed covariance-based structural equation modeling to test the conceptual framework model. Following structural questionaries, a total of 262 observations were collected, and the data were analyzed using structural equation modelling. Consequently, through a review of theoretical frameworks and rigorous hypothesis testing, the study creates and verifies a model that demonstrates how collaboration between humans and AI accelerates digital transformation while driving innovation. As a results, the results contribute to existing knowledge by providing actionable insights for managers and professionals looking to navigate the growing role of AI in business digital transformation.

Analysis of characteristics of ground motion and typical bridge performance in the Baoshan earthquake

2024-12-10T06:10:54+00:00

A Ms5.2 earthquake occurred in Longyang District, Baoshan City, Yunnan Province on 2 May 2023. The earthquake caused some degree of damage to power facilities and roads. Since then, small and medium sized earthquakes have occurred frequently in this region. In order to better analyze the characteristics of ground motion in this area and the coping strategies of related bridges, the response spectra, omnidirectional response spectra and omnidirectional representations of other indexes of intensity measure from records of strong ground motion were analyzed using the seismic records recorded by stations near the epicenter. Four typical bridges near the epicenter were selected for modeling and seismic response analysis to derive their damages under the action of ground motion, and structural displacements of the bridges with the strong ground motion were compared to analyze directional linkages. The Incremental Dynamic Analysis (IDA) method was used to analyze the fragility of the four bridges, and the seismic capacity of different bridges under the ground motion was compared. The omnidirectional displacement response spectra of the two stations and the omnidirectional representations of other indexes of intensity measure have obvious directionality, and the predominant direction is perpendicular to the direction of the fault, reflecting the rupture directionality of the earthquake. Comparing the corresponding period of the structural displacement response with seismic action with the omnidirectional displacement response spectra, it was found that the bridge structural displacement is correlated with the predominant cycle and predominant direction of the omnidirectional displacement response spectra. Under the same seismic action, the maximum moment of the deck arch bridge in the transverse direction is larger than that in the bridge direction; the larger the span of the deck arch bridge, the larger the maximum moment at the arch footing. According to the analysis of fragility, it can be seen that the seismic capacity of the continuous rigid frame bridge is much lower than that of the deck steel truss arch bridge under this ground motion. Compared to the deck-type concrete arch bridge, the deck steel truss arch bridge has greater seismic capacity. In this paper, based on the structural analysis and fragility analysis of these four bridges close to the fault, the structural damage and damage levels in the future earthquake are speculated, which provide suggestions for the follow-up maintenance and reinforcement work, and are also conducive to the resilience evaluation and rapid repair work after the real earthquake damage.

Adapting music education to the new normal: Integrative teaching strategies from a global perspective

2024-12-17T03:51:20+00:00

This study explores how music education can innovate through various integrative teaching strategies in the global “new normal”. Challenges and opportunities are identified. It highlights the need for educational reform and strengthening cultural identity in the post-pandemic world. By comparing global music education models, the positive role of cultural exchange in fostering diversity is examined. Based on the experimental findings, the study introduces “integrative teaching”, focusing on student-centered methods and interdisciplinary approaches. The experiment results show that integrating music with technology, language arts, and environmental science can enhance creativity, cultural understanding, and environmental awareness. In addition, practical examples are listed to demonstrate the effective use of virtual tools in addressing ecological issues through music creation. The study also underscores the importance of school-community collaboration and highlights successful case studies from Asia, Europe, and the U.S. How interdisciplinary strategies improve student learning outcomes are determined. More importantly, an evaluation framework focusing on diversified feedback and personalized assessments is established, proving that continuous feedback can enhance student engagement.

Coupled Helmholtz resonators for broadband Aeroacoustic noise mitigation

2024-12-18T06:52:42+00:00

As a structurally simple acoustic element, Helmholtz resonators can exhibit strong resonance when acoustic waves enter the cavity, thus providing excellent sound absorption effects. Consequently, they are widely applied in automotive engine and exhaust systems. This paper systematically investigates the noise reduction performance of multiple coupled Helmholtz resonators under conditions with and without tangential flow. A finite element simulation model with multiple Helmholtz resonators is established by employing COMSOL Multiphysics software to solve the linearized Navier-Stokes equations in the frequency domain. The simulation results demonstrate that the structure, which couples multiple Helmholtz resonators, can effectively broaden the low-frequency sound absorption band under the influence of a flow field, enhancing the transmission loss across the entire low-frequency band. This structure holds significant potential for applications in automotive exhaust systems and aero-engine noise reduction.

Research on intelligent vibration damping base of washing machine based on a stiffness-variable magnetorheological elastomer

2024-12-19T00:42:16+00:00

Traditional washing machine vibration-damping bases have a fixed stiffness, which can lead to structural resonance when the motor’s excitation frequency aligns with the machine’s inherent vibration frequency during the washing and spinning processes. This not only amplifies the noise caused by vibrations but also accelerates the wear and tear of the internal components. In this study, a pioneering approach has been introduced, developing an intelligent vibration-damping base for drum washing machines based on the dynamics of a mass-spring-damped single-degree-of-freedom system. This innovative base is designed with variable stiffness magnetorheological elastomer, utilizing the dynamics of the mass-spring-damped system to adaptively counteract vibrations. A vibration transmission rate curve specific to drum washing machines has been derived, and an intelligent control strategy for the drum washing machine’s vibration-damping base has been proposed. Dynamic testing of the drum washing machine’s vibration-damping base was conducted to verify the effectiveness of the intelligent damping base. The intelligent damping base addresses the unavoidable low-frequency resonance issues of traditional passive damping bases in washing machines and overcomes the drawback that the performance parameters of traditional passive isolation structures cannot be changed once set, providing a new direction for the damping of household appliances.

Design optimization of vibration amplitude reduction based on virtual prototype and machine learning

2024-12-19T00:52:20+00:00

The traditional design optimization of vibration amplitude reduction mainly has the disadvantages of low modeling and prediction accuracy as well as low optimization efficiency. Therefore, this paper presents a design optimization method for vibration amplitude reduction based on virtual prototyping and machine learning, which combines the high accuracy of numerical calculations with the efficiency of machine learning, overcoming the shortcomings of traditional methods. Firstly, sample points are collected through the design of experiments and virtual prototype simulation. Then, based on the sampled data, a prediction model for the relationship between the design parameters and the amplitude of the product is established using Genetic Algorithm-Support Vector Regression (GA-SVR). On the basis of the GA-SVR prediction model, a multi-objective optimization model of product is established, and Multiple Objectives Particle Swarm Optimization -entropy weight- Technique for Order Preference by Similarity to Ideal Solution (MOPSO-entropy weight-TOPSIS) is used to solve for the optimal design parameters. Finally, the washing machine suspension system is used as an example to verify the effectiveness of the model. The results show that, compared with the original design scheme, the design scheme obtained by the model can reduce the amplitude of the washing machine suspension system by 12.68%, and reduce the total weight of the counterweight by 7.35%. This method is conducive to the intelligent and efficient design optimization of vibration amplitude reduction, and is of great significance to product life cycle design.

Sound insulation prediction and optimization of wooden support structure for high-speed train floor based on machine learning

2024-12-19T01:06:42+00:00

In order to improve the sound insulation performance of high-speed train floors, this study first obtained the necessary data for model training based on the reverberation test method, and then conducted data sorting and feature selection. Next, the maximum mutual information minimum redundancy (mRMR) feature selection algorithm was used to calculate the selected features and screen out a subset of significant features. Subsequently, the decision tree, BP neural network, and support vector machine regression (SVR) methods were applied in sequence, and the standardized feature data were used for the high-speed train floor under the same evaluation criteria of the mean square error (MSE) and coefficient of determination (R²). We conducted training and validation of the sound insulation prediction models for timber-framed support structures. The prediction accuracy of the trained model was compared and evaluated with the finite element statistical energy analysis (FE-SEA) prediction model. Finally, the SVR model was used to optimize the design under constraint conditions. The research results show that based on the research object, sample library, and model training in this article, compared with the FE-SEA model, the prediction error of the SVR model is only 0.3 dB, showing better performance. In engineering practice, the SVR model can effectively optimize the wooden support structure in the floor under certain constraints, and it predicts that the weighted sound insulation of the entire floor is 50.45 dB, which has important engineering application value.

Acoustic sensor-based field efficacy evaluation of three different insecticides—Trunk injections against the red palm weevil, Rhynchophorus ferrugineus

2024-12-19T08:02:24+00:00

Red palm weevil (RPW) is one of the major pests that has caused significant losses in date palm production worldwide in recent years. Effective management of RPW is important to minimizing its impact on date palm yields. Conventional techniques utilized to manage RPW have shown minimal effectiveness. The study aimed to evaluate the efficacy of the insecticides Fipronil, Imidacloprid, and Thiamethoxam against RPW by applying a trunk injection technique in naturally infested date palm fields. Additionally, the study monitored the efficacy of the insecticides for ten months post-treatment using an acoustic sensor. After treatment with Fipronil, Imidacloprid, and Thiamethoxam, the mean burst rate impulses from RPW sound activities inside the date palm trunk was reduced, confirming the gradually mortality of RPW. The RPW impulse burst rate was decreased within 1–2 months post-treatment with these insecticides, while it increased in the control treatment. The results reveal that Fipronil reduced the RPW impulse burst rate from 0.50/s on day 0 to 0.07/s after 50 days post-treatment. In comparison, Imidacloprid reduced the RPW impulse burst rate to 0.07/s after 70 days post-treatment, which indicates a low level of infestation. Similarly, Thiamethoxam reduced the impulse burst rate from 0.97/s on day 0 to 0.08/s after 70 days of treatment. After 4 months of insecticide treatments, the RPW impulse burst rate dropped to zero which indicates the complete cessation of the RPW sound activities. The results suggest that a balloon injector may aid in delivering insecticides directly into the date palm trees, reaching the target more effectively. Furthermore, the acoustic sensor proved to be an effective tool for detecting and monitoring RPW activities in date palms.