Mechanical Noise Research Articles

Numerical Investigation and Validation of Noise Sources of a Distributed Propulsion System

This study delves into the exploration of a distributed propulsion system consisting of three co-rotating propellers in front of a high-lift wing system, with a primary focus on understanding its acoustic characteristics. Employing high-fidelity computational fluid dynamics simulations, the flow field is simulated in climb condition. Subsequently, acoustic transport to far-field observers is conducted using the Ffowcs–Williams and Hawkings equation. Because the noise mechanisms of such a configuration are not fully understood yet, several permeable and impermeable surfaces as input for the acoustic simulation are used, aiming to separate the various noise source contributions. Results reveal that in addition to the rotor-alone noise from the propellers, noise arising from propeller–wing interaction emerges as dominant, emitting mostly at the blade passing frequency. Moreover, a boundary element method tool is applied to observe the scattering effect of propeller-generated noise by the wing. Furthermore, this study incorporates consideration of structural components in close proximity to the model, thereby achieving a more realistic acoustic field. With this knowledge, the simulation is validated with experimental data from an open wind tunnel test campaign. An overall good agreement is observed between the simulated and experimental results, substantiating the reliability of both aerodynamic and acoustic predictions.

A Transfer Learning Model for Rolling Bearing Fault Diagnosis Based on Texture Loss Strategy and Nuclear Norm Regularization

Abstract In recent years, transfer learning (TL) approaches have seen extensive application in diagnosing bearing faults due to their exceptional performance. However, mechanical noise, equipment aging, and wear lead to notable disparities and differences in the multi-level feature distributions across the source and target domain signals. The issue is addressed by proposing a transfer learning model based on a texture loss strategy and nuclear norm regularization method. First, a Feature-Enhanced Network (MSRnet) is designed, which significantly improves the ability to capture local details and long-range dependencies by combining a multi-scale feature extraction module with a dilated residual module. Next, a texture loss strategy is proposed to align multi-scale features across domains by minimizing the Gram matrix of signal features. Finally, a nuclear norm regularization method is proposed to perform low-rank approximation on the signal matrix, facilitating the extraction of more robust feature data and mitigating the risk of overfitting. The experimental results demonstrate that the proposed method achieved an average accuracy of 98.58% on the University of Ottawa bearing fault dataset and 98.11% on the Jiangnan University (JNU) bearing dataset, surpassing eight other algorithms in bearing fault diagnosis.

During haptic communication, the central nervous system compensates distinctly for delay and noise.

Physically connected humans have been shown to exploit the exchange of haptic forces and tactile information to improve their performance in joint action tasks. As human interactions are increasingly mediated through robots and networks it is important to understand the impact that network features such as lag and noise may have on human behaviour. In this paper, we investigated interaction with a human-like robot controller that provides similar haptic communication behaviour as human-human interaction and examined the influence and compensation mechanisms for delay and noise on haptic communication. The results of our experiments show that participants can perceive a difference between noise and delay, and make use of compensation mechanisms to preserve performance in both cases. However, while noise is compensated for by increasing co-contraction, delay compensation could not be explained by this strategy. Instead, computational modelling suggested that a distinct mechanism is used to compensate for the delay and yield an efficient haptic communication.

Armouring of a Frictional Interface by Mechanical Noise

A dry frictional interface loaded in shear often displays stick–slip. The amplitude of this cycle depends on the probability that a microscopic event nucleates a rupture and on the rate at which microscopic events are triggered. The latter is determined by the distribution of soft spots, P(x), which is the density of microscopic regions that yield if the shear load is increased by some amount x. In minimal models of a frictional interface—that include disorder, inertia and long-range elasticity—we discovered an ‘armouring’ mechanism by which the interface is greatly stabilised after a large slip event: P(x) then vanishes at small argument as P(x)∼xθ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P(x)\\sim x^\ heta $$\\end{document} (de Geus et al., Proc Natl Acad Sci USA 116(48):23977-23983, 2019. https://doi.org/10.1073/pnas.1906551116). The exponent θ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta $$\\end{document} is non-zero only in the presence of inertia (otherwise θ=0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta =0$$\\end{document}). It was found to depend on the statistics of the disorder in the model, a phenomenon that was not explained. Here, we show that a single-particle toy model with inertia and disorder captures the existence of a non-trivial exponent θ>0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta >0$$\\end{document}, which we can analytically relate to the statistics of the disorder.

Mechanisms of multi-layered Rayleigh noise in Brillouin optical correlation-domain reflectometry

In Brillouin optical correlation-domain reflectometry (BOCDR), sinusoidal modulation is applied to the output frequency of a light source, with spatial resolution inversely related to the modulation amplitude. We have developed an effective method to estimate the modulation amplitude using the width of the noise spectrum caused by Rayleigh scattering, eliminating the need for an optical spectrum analyzer or modifications to existing equipment. However, the Rayleigh noise spectrum often displays a three-layered structure, complicating the identification of the appropriate spectral components for estimating the modulation amplitude. In this work, we investigate the origins of this three-layered Rayleigh noise spectrum and identify the directivity of an optical circulator as the source of the third noise component. As replacing the circulator with alternative optical components is not easy, it remains an essential part of the system. Our analysis shows that the third noise component exhibits significantly small variation in spectral width with changes in modulation frequency compared to the first and second components. This characteristic allows for the effective separation and identification of the third noise component, thereby enhancing the accuracy and convenience of modulation amplitude estimation in BOCDR.

Edge-assisted U-shaped split federated learning with privacy-preserving for Internet of Things

In the realm of the Internet of Things (IoT), deploying deep learning models to process data generated or collected by IoT devices is a critical challenge. However, direct data transmission can cause network congestion and inefficient execution, given that IoT devices typically lack computation and communication capabilities. Centralized data processing in data centers is also no longer feasible due to concerns over data privacy and security. To address these challenges, we present an innovative Edge-assisted U-Shaped Split Federated Learning (EUSFL) framework, which harnesses the high-performance capabilities of edge servers to assist IoT devices in model training and optimization process. In this framework, we leverage Federated Learning (FL) to enable data holders to collaboratively train models without sharing their data, thereby enhancing data privacy protection by transmitting only model parameters. Additionally, inspired by Split Learning (SL), we split the neural network into three parts using U-shaped splitting for local training on IoT devices. By exploiting the greater computation capability of edge servers, our framework effectively reduces overall training time and allows IoT devices with varying capabilities to perform training tasks efficiently. Furthermore, we proposed a novel noise mechanism called LabelDP to ensure that data features and labels can securely resist reconstruction attacks, eliminating the risk of privacy leakage. Our theoretical analysis and experimental results demonstrate that EUSFL can be integrated with various aggregation algorithms, maintaining good performance across different computing capabilities of IoT devices, and significantly reducing training time and local computation overhead.

Underbody contribution simulation for vehicle wind-noise

Wind noise is one of the largest sources to the interior noise of modern electric and hybrid vehicles. This noise is encountered when driving on roads and freeways and generate considerable fatigue for passengers on long journeys. Aero-acoustic noise is the result of turbulent and acoustic pressure fluctuations created within the flow. They are transmitted to the passenger compartment via the vibro-acoustic excitation of vehicle surfaces and underbody cavities. Generally, this is the dominant flow-induced source at low frequencies. The transmission mechanism through the vehicle floor and underbody is a complex phenomenon as the paths to the cavity can be both airborne and structure-borne. This study is focused on the floor contribution to wind noise of different type of vehicles, whose underbody structure are largely different. Aero-Vibro-acoustic simulations are performed to clarify the transmission mechanism of the underbody wind noise and contribution. The external fluctuating pressure fields are simulated using computational fluid dynamics based on the Lattice Boltzmann Method (LBM). The vehicle exterior and interior vibro-acoustic coupling and transmission are simulated using subsystems modeled by the finite-element (FEM) or boundary element methods (BEM). The analysis results are discussed and a contribution analysis is proposed to identify potential improvements.

Mid-frequency propagation path analysis on vehicle body using structural intensity

With the penetration of electric vehicles, reduction of structure-borne road noise gets important issue to realize comfortable vehicles for customers.Sound generation mechanism of structure-borne road noise on vehicle body is analyzed basically by modal analysis in low-frequency range. On the other hand, as frequency increases, modal analysis cannot clarify vibration mechanism because vibration wavelength gets shorter, mode density gets high and mode shape gets complicated. Therefore, it is difficult to identify efficient countermeasure parts and inefficient damping materials are added to response panels in mid-frequency range. So alternative analytical methods in mid-frequency range are under research to understand vibration mechanism. In this paper, Structural intensity (SI) analysis is introduced to clarify sound propagation mechanism. This analysis method makes it possible to clarify the main energy propagation path from input point to vibrating panels on vehicle body. The results show that SI analysis unveils the main energy propagation path and gives the opportunity to reduce the panel vibration efficiently by controlling the energy propagation path in body frame structure without damping materials.

Mechanical noise for architectural students

Noise control of mechanical equipment is one of the requirements established in energy certificates (LEED, BREEAM, WELL, etc.) as well as in different design standards or national codes. At the Higher Technical School of Architecture of Madrid, Technical University of Madrid (UPM), several courses are offered to students on the design of mechanical systems, from the selection of the equipment, its location, distribution, and its integration with the architecture. Its acoustic implications are not explained in any course. During the last year of the degree, in the course "Proyecto de instalaciones", (Technical Equipment Design) students are asked to fully integrate the building services (heating, cooling, ventilation, fire safety, emergency signals...) in one building designed by their own, and for the first time a 2-hour masterclass on mechanical noise for architects has been organized. In it, the main noise sources, design recommendations and the most common ways to attenuate and control it are addressed. The aim of this work is to share the learned experiences and discuss the next steps to be taken.

Numerical study on the flow and noise control mechanisms of a forced rotating cylinder

This numerical study proposes an active control method aiming to suppress aerodynamic noise from bluff bodies by employing a forced rotating cylinder and investigates its noise reduction effects and mechanisms. A three-dimensional large eddy simulation combined with the Ffowcs William–Hawkings equation was adopted to study the influence of different rotation ratios on the aerodynamic and aeroacoustic characteristics of a cylinder at a Reynolds number of 4.7×104, and to elucidate the primary mechanisms by which cylinder rotation reduces aerodynamic noise. The numerical method is validated through a comparison with previous numerical and experimental results of both flow field and far-field noise. The present numerical results indicate that cylinder rotation can not only effectively reduce aerodynamic drag but also significantly suppress aerodynamic noise across the entire frequency range, including vortex-shedding tonal noise and broadband noise. Two primary mechanisms of flow and noise control by the rotating cylinder are revealed within different ranges of rotation ratio. One mechanism stabilizes the shear layer, thereby suppressing vortex shedding. The other mechanism attenuates the Kelvin–Helmholtz instability on the upper side of the cylinder, leading to a transition into laminar flow which inhibits the formation of large-scale coherent turbulent structures.

Design and fabrication of an accelerometer structure using glass fiber reinforced epoxy resin for seismic P-wave early warning

Earthquake early warning represents a vital and effective strategy for mitigating earthquake-related losses. Among the existing sensors for earthquake early warning, MEMS accelerometers involve complex manufacturing process, leading to high research and development costs and long cycles. Traditional mechanical sensors are bulky, costly, hence not suitable for large-scale, high-density monitoring network. In this study, a low-cost accelerometer using glass fiber reinforced epoxy resin is proposed for longitudinal seismic waves (P-waves) early warning. Both theorical and finite element analysis are carried out to define and optimize the initial structure of the accelerometer. A pre-deformation structure is implemented into the spring suspension system to offset the influence of the sensor’s gravity, so that a self-balanced state in the direction of gravity is achieved. The simulation results show that the accelerator can achieve an eigenfrequency of 12.67 Hz, a Q-value of 49.2, and mechanical thermal noise of 1.72×10-9g/Hz. Based on the simulation results, the accelerometer’s structure is processed using a computer numerical control (CNC) milling machine, and tested by collecting the voltage signals when the accelerometer’s structure undergoes an impact in the direction of the gravity. The measured eigenfrequency is around 10 Hz, and the signal attenuation rate closely aligns with the simulation results. The accelerometer structure has dimensions within 6 cm and a relatively simplified manufacturing process, making it a cost-effective solution for the development of large-scale, high-density earthquake early warning systems.

Optimum noise mechanism for differentially private queries in discrete finite sets

The differential privacy (DP) literature often centers on meeting privacy constraints by introducing noise to the query, typically using a pre-specified parametric distribution model with one or two degrees of freedom. However, this emphasis tends to neglect the crucial considerations of response accuracy and utility, especially in the context of categorical or discrete numerical database queries, where the parameters defining the noise distribution are finite and could be chosen optimally. This paper addresses this gap by introducing a novel framework for designing an optimal noise probability mass function (PMF) tailored to discrete and finite query sets. Our approach considers the modulo summation of random noise as the DP mechanism, aiming to present a tractable solution that not only satisfies privacy constraints but also minimizes query distortion. Unlike existing approaches focused solely on meeting privacy constraints, our framework seeks to optimize the noise distribution under an arbitrary (ϵ,δ)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(\\epsilon , \\delta )$$\\end{document} constraint, thereby enhancing the accuracy and utility of the response. We demonstrate that the optimal PMF can be obtained through solving a mixed-integer linear program. Additionally, closed-form solutions for the optimal PMF are provided, minimizing the probability of error for two specific cases. Numerical experiments highlight the superior performance of our proposed optimal mechanisms compared to state-of-the-art methods. This paper contributes to the DP literature by presenting a clear and systematic approach to designing noise mechanisms that not only satisfy privacy requirements but also optimize query distortion. The framework introduced here opens avenues for improved privacy-preserving database queries, offering significant enhancements in response accuracy and utility.

Flow Structure and Periodic Processes in a Disc-Shaped Vortex Chamber of a Hydrodynamic Cavitator

Introduction. The essence of the acoustic – cavitation processes is that the liquid is passed through sound with a pressure at the wave surface of more than 3 bar that causes local breaks of the liquid in the vacuum phase of the wave and the collapse in the manometric phase. The opposite walls of each cavern in the collapse approach at a speed exceeding two speed of sound, due to which a high energy density is achieved at the meeting point, and what is especially valuable is the mutual transitions of energies from one form to another, unattainable under normal conditions, and, moreover, as inside cavitation area and near it. The novelty of the work is confirmed by the results of a periodic information and patent analysis, and by four patents received for inventions on the topic under consideration.Aim of the Study. The study is aimed at improving the acoustic-cavitation qualities of a disk-shaped vortex chamber used as a liquid whistle.Materials and Methods. In the study, there were used numerical modeling of flows in the FlowVision program, experimental determination of flow rates using a pitot tube, film method, removal of frequency response using SpectraPLUS 5.0, and visualization of flows and processes on optically transparent devices by the method of color indicators in stroboscopic lighting high-speed video shooting.Results. The mechanism of sound generation and noise in the flow transiting through the device has been found. The corrective effect of pump pulsations f = 300 Hz on the sound generation mechanism was revealed. The disc-shaped character of the device, which encloses the input flow in cross section from three directions, contributes to creating a more expressive acoustic signal, forming two conjugate torus vortices along the shell that ensures uniformity of the circumferential flow, attenuation of longitudinal high-frequency oscillations f = 200 kHz, and the creation of periodic zones of increased pressure along the shell. The concentrated tangential entrance to the device determines the central asymmetry of the flows in it and a number of processes that create acoustic noise.Discussion and Conclusion. The frequency of the useful acoustic signal in the vortex chamber is proportional to the speed of the transit flow, and the amplitude is proportional to the dimensions of the device. Along with the useful signal created by the interaction of the peripheral and input parts of the transit flow, noise of similar frequencies is created in the device. Other sources of noise generation are due to the presence of a concentrated tangential input. The formation of two conjugate torus vortices along the shell can be used as a means of controlling the process of interaction between parts of the transit flow. The disc-shaped vortex chamber combines the functions of sound generation and the ability to create a centrifugal field, which expands its technological capabilities.

Simulated analysis and experimental validation of sound field distribution regularity for a large-scale non-anechoic harbor pool

The large-scale underwater space, such as large water pool or large-scale harbor pool can provide a good experimental environment for the measurement of the underwater radiated noise of vessel. However, it's not as simple as measuring the sound power of a small machine in the air, the measurement and evaluation of the low frequency mechanical noise and radiated sound power of vessel requires a specific reverberation environment in the large-scale underwater space. Therefore, in this paper, the reverberant sound field characteristics of large-scale underwater space are simulated and calculated by finite element analysis, and experimental measurements are carried out in the large-scale harbor pool. It was found the cut-off frequency of large-scale underwater space depends on the depth of the water pool, and the lower limit frequency depends on the volume of the water pool. The dock door does not reduce the spatial average sound pressure in the reverberation sound field, the floating box platform does not effect on the cut-off frequency but has an effect on the sound energy of the reverberant sound field. It is possible to select the appropriate underwater experimental environment for the measurement and evaluation of different mechanical noise sources. The sound pressure level obtained by calculating the sound source at different locations in the reverberation area is basically the same, and in a 16 × 22 hydrophone arrays, more than 160 array elements are selected, each between 0.25 m and 1 m, a stable sound pressure level can be obtained through spatial averaging. Through experimental measurement verification in the large-scale harbor pool, low-frequency sound sources are emitted from 6 different positions, three hydrophone arrays data are collected, and the measured sound pressure level error is within 1.4 dB. These conclusions are conducive to the actual measurement and evaluation of noise sources of vessel.

Influence of distribution parameters on acoustic radiation from bubble clusters

Cavitation noise is the major noise in underwater, and the study of acoustic radiation from bubble clusters is the primary means to reveal the mechanism of cavitation noise. In this study, direct numerical simulation (DNS) of bubble clusters with volume fractions of 20–40 % with different bubble sizes and bubble position distributions are performed, and the far-field sound pressure is calculated using the Ffowcs Williams–Hawkings (FW-H) method. Then, we compare the collapse and acoustic radiation of bubble clusters with equivalent bubble. The results show that the collapse times of bubble clusters at the same volume fraction are identical and close to equivalent bubble, despite the different bubble sizes and positions in the bubble cluster. Further, in terms of acoustic radiation, the layered arrangement of bubble positions results in bubble clusters exhibiting layer-by-layer collapse and emitting multiple sound pressure pulses. In contrast, a random arrangement of bubble positions lacks this feature, resulting in the collapse of the bubble cluster without a layered phenomenon and radiating only a single primary sound pulse, which is consistent with the equivalent bubble. Additionally, the distribution of bubble sizes in the bubble cluster has almost no effect on the acoustic radiation of the bubble cluster. Notably, when the volumetric fraction exceeds 25 %, the sound pressure levels of bubble clusters with different distributions in the frequency domain are nearly identical, with differences from the equivalent bubble within 5 dB.

Demonstration of record sensitivity for water vapor detection by means of comb-locked cavity ring-down spectroscopy

We report on the development, characterization, and test of a comb-locked cavity ring-down spectrometer (CL-CRDS) operating in the spectral region around 1.39 µm. The system is based on the use of a hemispherical optical resonator with a finesse as high as ∼507000, which gives an empty-cavity ring-down time of about 285 µs. An Allan-Werle analysis on repeated acquisitions of the ring-down time at a fixed laser frequency suggests a minimum detectable absorption coefficient of 2×10−12cm−1 for the optimum integration time of 45 s. This limit can be exceeded by adopting the strategy of long-term spectral averaging. Taking advantage of the frequency stability guaranteed by the optical frequency comb, the CL-CRDS spectra were averaged over more than two days, thus removing efficiently the effect of mechanical, acoustic, and thermal noises. As a result, we could achieve a minimum detectable absorption coefficient as low as 3.7×10−13cm−1, which corresponds to a limit of detection for H2O in N2 of nine parts per trillion and a H2O partial pressure of 2×10−8 Pa (or 2×10−10 mbar). The potentialities of our approach are demonstrated by recording the absorption features of HD16O and HD18O in flows of ultra-high-purity N2 and ambient air, respectively.

Investigation of noise characteristics of electric vibrator utilizing acoustic camera and transfer path analysis

Abstract Mechanical equipment operation frequently results in noise generation, which can raise concerns regarding quality and safety. This study focuses on electric vibrators, essential electromechanical systems, with the goal of identifying the source and transfer path of noise. To achieve this objective, an acoustic camera positioning analysis was performed to approximate the distribution and characteristics of the noise. Building upon this foundation, a thorough evaluation of the transfer path and noise contribution was conducted. Subsequently, targeted noise suppression methods were implemented based on the properties of the noise. Primary noise sources were observed to be classified into wind turbulence and mechanical vibration based on operating conditions. Time-frequency analysis revealed the presence of low-frequency signals (around 50 Hz) and intermediate-frequency signals (around the resonant frequency), corresponding to wind-induced and mechanical response noise, respectively. Leveraging the characteristics of the noise and its transfer path, passive methods (Sound-absorbing rubber and Soundproof cotton) and active method (FxLMS algorithm) were employed. The findings of this study contribute to a better understanding of noise mechanisms and provide insights for noise emission strategies.

Simulating Noise, Vibration, and Harshness Advances in Electric Vehicle Powertrains: Strategies and Challenges

This study examines the management of noise, vibration, and harshness (NVH) in electric vehicle (EV) powertrains, considering the challenges of the automotive industry’s transition to electric drivetrains. The growing popularity of electric vehicles brings new NVH challenges as the lack of internal combustion engine noise makes drivetrain noise more prominent. The key to managing NVH in electric vehicle powertrains is understanding the noise from electric motors, inverters, and gear systems. Noise from electric motors, mainly resulting from electromagnetic forces and high-frequency noise generated by inverters, significantly impacts overall NVH performance. This article details sources of mechanical noise and vibration, including gear defects in gear systems and shaft imbalances. The methods presented in the publication include simulation and modeling techniques that help identify and solve NVH difficulties. Tools like multi-body dynamics, the finite element method, and multi-domain simulation are crucial for understanding the dynamic behavior of complex systems. With the support of simulations, engineers can predict noise and vibration challenges and develop effective solutions during the design phase. This study emphasizes the importance of a system-level approach in NVH management, where the entire drivetrain is modeled and analyzed together, not just individual components.

(Digital Presentation) Mechanically Driven Electromagnetic Energy Harvesting for Power System Sensing Applications

Introduction Energy harvesting is a process of producing energy or usable power from the environment. Among potential ambient energy harvesting sources, electromagnetic (EM) field offers the great promise for emerging power system applications. This is because EM energies are widely available around the current-carrying wires (busbars) that connect various power devices and equipment. Most previous works on EM energy harvesting were built upon AC transmission lines [1-5], whereas modern power systems are typically driven by renewable DC energy sources. In this work, a mechanically-driven, DC-based EM energy harvesting system is designed and implemented as a lab-scale prototype to ultimately power sensing devices in the power system. Key Results: The schematic diagram and the photograph image of the EM induction experimental setup are shown in Figures 1a) and 1b), respectively. The energy harvester consists of a high permeability (μ ~ 2300) ferrite toroidal coil (cross sectional area 760 mm2) that is placed below a DC conducting (copper) slab at a distance of 1 cm. According to the Faraday’s law of induction (Equation 1), the open circuit voltage is proportional to the time rate of change of the magnetic flux (dφ/dt). This work is sharply distinguished from other works because the time variant nature originates from the physical vibration without using the AC power source. As seen in the figure, the toroidal coil is directly attached to a vibrator, thus experiencing a light-to-moderate amount of vibration. Here, the copper slab emulates the busbar in the power system, and the vibrator represents a practical scenario where the energy harvester is exposed to mechanical, machinery, and other noise sources.Figure 2 plots the open circuit voltage (VOC) as a function of the number of coil turns (N) for the experimental setup shown in Fig. 1. VOC was measured using a multimeter between two terminals of the coil for the maximum current of 3 A applied to the copper slab. As expected, a linear trend of VOC vs. N was observed with the VOC value as high as 51.4 mV for the case of 2,500 turns. Importantly, VOC is scalable to the value that is sufficiently high to drive most modern sensing devices because VOC is proportional to current (I). It is common that more than 100 A flows in the busbar of the power system, which escalates VOC to more than 1.7 V. The idea of increasing VOC by increasing current is confirmed in Figure 3; we repeated the experiments by lowering the current value in the copper slab, and obtained the linear trend line. Thus, both results shown in Figures 2 and 3 indicate a strong correlation of our energy harvester prototype with the EM theory. The maximum VOC value we obtained (51.4 mV) is separately shown in Figure 4 as a photograph image of the multimeter reading.In Table 1, we estimated the VOC values that can be readily achievable in the power system that affords the busbar current of 300 A and/or the 10,000 coil turns. For example, as compared with a previous work [3] with VOC of 1.4 V for 30 A (AC), this work features VOC of about 2 V with the 30 A DC power source. Significance: This work demonstrates the possibility of newly developing an mechano-electromagnetic energy harvester for modern power systems. Taking full advantage of EM energies and vibration present in the power system, the proposed DC-sourced energy harvesting scheme can greatly facilitate development and adoption of various sensing/monitoring/diagnosis device technologies. This is because these devices will not require separate batteries or power sources; they will be easily powered using the electromagnetic energy and mechanical vibration.

Effect of distribution parameters on the noise spectrum of bubble clusters

This study explores the effects of bubble distribution parameters on the noise spectrum of bubble clusters through direct numerical simulations across volume fractions from 0.005% to 40%. Three types of bubble cluster distributions were analyzed: layered (uniformly sized bubbles with layered positioning), random (uniformly sized bubbles with random positioning), and lognormal (log-normally distributed bubble sizes with random positioning). Using the Ffowcs Williams–Hawkings (FW–H) method, we evaluated the sound pressure levels of the clusters. We found that the arrangement of bubble positions has little impact on the collapse times of bubble clusters. At volume fractions greater than 0.5%, bubble size also shows minimal effect on collapse times. However, when the volume fraction is less than 0.5%, the collapse times gradually approach the collapse time of the largest bubble in the cluster in a free field. Noise spectrum analyses showed that the arrangement of bubble positions significantly influences the noise spectra within the volume fraction range of 0.5%–25%, but has minimal impact outside this range. Importantly, the distribution of bubble sizes shows negligible effects on the noise spectrum, demonstrated by the nearly identical sound pressure level octave decay rates for random and lognormal clusters at the same volume fractions. This consistency can be mathematically described by the fitting formula: decay rate (dB/octave) = 18.192 × α−0.047−16.264. These findings enhance our understanding of the noise spectrum across varied bubble cluster distributions and provide new insights into the mechanisms of cavitation noise.