Sound & Vibration

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

2024-10-21T06:26:41+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

2024-10-28T09:14:25+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

2024-10-31T06:31:19+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

2024-11-04T06:18:50+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.

A multi-functional nine channels full-spectrum light emitting diodes color temperature palette

2024-11-05T05:41:24+00:00

A multi-functional nine channels full-spectrum light emitting diodes color temperature palette with continuously tunable color temperature at 1 K interval in 2500 K–6500 K, high color rendering of Ra > 94, R1–R15 > 90, Rf > 91, 96 ≤ Rg ≤ 104 is proposed. |Duv| < 0.001 is also achieved. The circadian effect of light source with melanopic efficacy of luminous radiation of 0.6 mW/lm–1.14 mW/lm and circadian action factor of 0.424 blm/lm–0.96blm/lm are obtained. The color temperature palette enables precise control and reproduction of color temperature of sunlight with corresponding circadian effect, which is of positive significance for visual fields such as photography or art exhibitions and regulation of circadian rhythm.

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

2024-11-05T05:55:46+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.

Integrating language arts and sound sciences: Enhancing medical and engineering education in the Arab World

2024-11-08T03:45:08+00:00

This paper explores the transformative potential of integrating language arts and sound sciences into medical and engineering education in the Arab world. Interdisciplinary education; a proven catalyst for enhancing creativity; problem-solving; and cultural competency; has been implemented successfully in various global contexts. This paper proposes that adopting similar interdisciplinary approaches in Arab universities can address educational gaps; better prepare students for the challenges of an increasingly complex world; and align with the region’s economic development goals. The discussion includes a review of case studies from Columbia University; Aalborg University; and Finland’s education system; along with recommendations for implementation in the Arab context. Methods for evaluating interdisciplinary success are also outlined, emphasizing the need for both qualitative and quantitative metrics.

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

2024-11-08T08:28:05+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.

Precise PMU locations on distribution system considering power system disruptions for elegant state estimation

2024-11-15T05:37:01+00:00

This study presents a novel approach to achieve complete system observability by optimizing the placement of Phasor Measuring Units (PMUs), reducing the risk of fault identification. The process considers both the redundancy and the cost of installation. The proposed solution methodology improves upon existing algorithms by utilizing the Butterfly Optimization Algorithm (BOA), which identifies optimal PMU locations. Resilient fault detection techniques are employed to detect and mitigate disruptions in the power grid swiftly. Addressing transmission line faults, the research integrates a Deep Learning Network (DLN) to enhance the state estimation process during fault conditions. Simulations of fault transients, including LG (Line-to-Ground), LLG (Line-to-Line-to-Ground), and LL (Line-to-Line) faults, are conducted using MATLAB Software. The Neural Network (NN) response is evaluated based on two key hyperparameters—the number of hidden layers and the number of neurons utilized for feature extraction. Results demonstrate the superiority of the proposed method, with approximately 85% fault detection accuracy and a system performance metric of 90%. Additionally, the processing time required for training the network is small in the order of micro seconds.

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

2024-11-18T00:51:06+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

2024-11-15T05:54:38+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)

2024-11-15T07:24:48+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

2024-11-18T01:10:59+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.