Mechanical Noise Research Articles

Enhanced micro-perforated wall-treatments for reducing the boundary layer noise in a low-speed wind-tunnel: modelling, characterization and optimization studies.

Micro-perforated aero-acoustic liners are robust non-fibrous wall-treatments able to achieve significant axial attenuation in low-speed ducted flows, if their input impedance is suitably optimized. They are also potential candidates for broadband reduction of the flow-induced noise, useful to increase the signal-to-noise ratio in wind-tunnels test section or for fan noise control when inserted in casing treatments. The current theoretical and experimental study determines under which range of frequencies, holes diameter and free stream flow velocity, micro-perforated partitions are able to efficiently reduce the boundary layer noise, either by absorption or transmission mechanisms, depending on the spectral content of the aero-acoustic excitation. The formulated analytical models, either modal- or wavenumber-based, are validated against wind-tunnel measurements of the overall power injected by a low-speed boundary layer into a micro-perforated partition and its aerodynamic transmission loss. A hole-based Strouhal number is found below which little back-scattering of the wall-pressure components occurs. Optimization studies are performed to determine the range of parameters that enhance the total absorption or transmission of boundary layer noise, with special emphasis on the low frequency content of the wall-pressures.

Stabilizing a centrifugal force microscope to study DNA folding

A centrifugal force microscope (CFM) is a highly cost-effective and user-friendly method to apply force with a desktop centrifuge. Applying force in a biophysical assay allows for studying the mechanics of motor proteins or the folding pathway of DNA or proteins. However, in comparison to other methods—such as atomic force microscopy, optical tweezers, and magnetic tweezers—measurements of position in the CFM are limited. Position is measured by video microscopy which is affected by the shaking of the centrifuge when it begins to rotate and the unfocusing of the camera. To improve stability, we followed the original designs from Yang (Methods in Molecular Biology 2016) and then worked to enhance focus stability over longer periods of time; investigated sample illumination; and altered the counterbalance scheme to reduce mechanical noise. An enhanced stability would allow reliable collection of position data to be used to produce a force-extension curve of DNA.

Assessing human activity noise in workspaces using machine learning and numerical models

Acoustic comfort of workspace environments is deeply dependent on the balance between indoor background noises. For example, colleagues' speaking might affect task performances by downgrading privacy and productivity. Conversely, HVAC noise can reduce the employee's distraction since such continuous mechanical noise is detrimental to speech comprehension. Therefore, in the analysis of workspaces' acoustic comfort, different background noise sources identification becomes essential. In this regard, machine learning techniques are resourceful for clustering sound pressure level patterns among the unlabeled data. A previous work by the authors provided reliable results on separating noise sources via Gaussian Mixture Model and K-means clustering. Nevertheless, such method was applied to a single workspace, and thus it needs further investigation on a wider sample of environments. For this reason, in the present work long-term monitoring was carried out in various active workspaces extending previous results and confirming the procedure's robustness. Moreover, simulations of the acoustic conditions by summing up the human activity contribution to the mechanical noise allowed obtaining more reliable speech intelligibility criteria at the workstations. Refining the numerical models' setup through background noise levels obtained through machine learning analysis enhance the assessment of workers' privacy condition in realistic scenarios.

Data-driven determination of low-frequency dipole noise mechanisms in stalled airfoils

An aeroacoustic investigation of planar time-resolved particle image velocimetry (PIV) measurements in the streamwise surface-normal plane of a NACA 0012 airfoil in static stall is presented at chord-based Reynolds number textrm{Re}_c=7.1times 10^4. Instantaneous planar pressure reconstructions are obtained using a Poisson solver and the dipole noise emanating from the surface is extrapolated via Curle’s acoustic analogy. To correlate structure in the velocity field to the generation of noise, a data-driven framework utilising the proper orthogonal decomposition (POD) and the spectral Linear Stochastic Estimation (sLSE) is employed. The flow structures responsible for noise are found to concentrate in proximity to the trailing edge. In addition, a conditional analysis for the extreme noise events reveals that downwash and upwash events in proximity to the trailing edge, coupled with slow and fast-moving fluid at the incipient shear layer, are correlated to local maxima and minima in the acoustic fluctuations, respectively.Graphical abstract

Numerical analysis of acoustic noise from an electronic cooling fan at flow disturbed by an external obstacle

Axial cooling fans are widely used in data center dense Hard Disk Drive (HDD) storage systems. However, these fans emit high noise levels and degrade HDD performance at certain frequencies. Flow at the fan's inlet can be highly turbulent due to the wake generated by fan components such as struts, finger guards, stators/guide vanes, shrouds, and other external system components such as connectors and mounts, power cables and components, circuits etc. The wake-fan interaction also causes high tonal noise. Therefore a proper understanding of this noise mechanism will help optimize the cooling system in next-generation high-performance HDD enclosure systems. This paper focuses on studying this phenomenon using numerical simulations of a typical data center cooling fan combined with various simplified strut geometries as the obstacle. The high-fidelity Computational Fluid Dynamic (CFD) method, Large Eddy Simulation (LES), was used to obtain a transient flow field. The Ffowcs-Williams and Hawkings acoustic analogy was used to predict far-field noise.

Data augmentation on convolutional neural networks to classify mechanical noise

Mechanical noise identification and classification are essential for automotive and machinery fault diagnosis. The scarcity of labelled audio data for noise-related mechanical issues has constrained the utilisation of complex, high-capacity machine learning models. In this research, the application of augmentation methods for labelled squeak and rattle datasets has proven that the accuracy of deep convolutional neural networks can be improved. Data augmentation has eliminated common machine learning issues such as overfitting observed in the models trained from a small dataset. The influence of different augmentation methods for the dataset was evaluated and compared based on classification accuracy. Different data augmentation methods have been tested to classify audio classes of different mechanical noises. The use of class-specific data augmentation leads to the development of more accurate machine learning models. Different combinations of data augmentations were investigated. This research showed that the new combined augmentation process could significantly improve the classifiers’ accuracy. The proposed combined data augmentation technique achieved the highest precision with the lowest error rate for both squeak and rattle datasets. The proposed method can be applied to any type of mechanical noise identification and classification.

Neural adaptive braking control for single rope winding hoisting systems with disturbance compensation

In the braking control of single rope winding hoisting systems (SRWHS), reasonable braking torque is of great significance in reducing the probability of significant hidden dangers such as overwinding, overspeeding, rope breaking, vibration, conveyance crash and so on. However, dynamic nonlinearity, time-varying disturbances, mechanical dynamic uncertainties and measurement noise severely affect the practical braking control performance. To address those problems, a neural adaptive braking torque controller with disturbance compensation is developed to enhance the braking performance for a single rope winding hoisting system in this paper. Firstly, considering the elastic of steel wire rope, the nonlinear braking model of the SRWHS is established using Lagrange equations and an extended state observer (ESO) is introduced to estimate the system’s unmeasured states and modelling error. Next, a neural adaptive controller is developed to estimate and compensate the mechanical dynamical disturbances resulted from friction forces and random external disturbances. Then, a neural adaptive network controller combined with the ESO (ESONAC) is designed to solve the modelling nonlinearity, time-varying disturbances and system’s unmeasurable states. Finally, the advantages of the ESONAC in improving the braking control performance of winding hoisting systems is verified by comparative experiments.

Mechanical Cryocooler Noise Observed in the Ground Testing of the Resolve X-ray Microcalorimeter Onboard XRISM

Low-temperature detectors often use mechanical coolers as part of the cooling chain in order to reach sub-Kelvin operating temperatures. The microphonics noise caused by the mechanical coolers is a general and inherent issue for these detectors. We have observed this effect in the ground test data obtained with the Resolve instrument to be flown on the XRISM satellite. Resolve is a cryogenic X-ray microcalorimeter spectrometer with a required energy resolution of 7 eV at 6 keV. Five mechanical coolers are used to cool from ambient temperature to about 4 K: four two-stage Stirling coolers (STC) driven nominally at 15 Hz and a Joule-Thomson cooler (JTC) driven nominally at 52 Hz. In 2019, we operated the flight-model instrument for two weeks, in which we also obtained accelerometer data inside the cryostat at a low-temperature stage (He tank). X-ray detector and accelerometer data were obtained continuously while changing the JTC drive frequency, which produced a unique data set for investigating how the vibration from the cryocoolers propagates to the detector. In the detector noise spectra, we observed harmonics of both STCs and JTC. More interestingly, we also observed the low (<20 Hz) frequency beat between the 4'th JTC and 14'th STC harmonics and the 7'th JTC and the 23--24'th STC harmonics. We present here a description and interpretation of these measurements.

A New Virtual Tracking Sub-Algorithm Based Hybrid Active Control System for Narrowband Noise With Impulsive Interference

Mechanical noise is usually a mixture of narrowband and impulsive noise which needs complex active noise control (ANC) algorithms to improve the de-noising performance. But the ANC algorithm with a high computation load will reduce the real-time performance of an ANC system, thus decreasing the attenuation performance and even leading to divergence. To alleviate this contradiction in narrowband ANC systems, a new virtual filtered-x L0 norm discrete Fourier cancellation (FxL0DFC) based hybrid FxNLMS(filtered-x normalized least mean square)-FxDFC framework is proposed to decrease the total computing load and keep good attenuation performance. For a fast-changing noise, the FxNLMS algorithm is employed. The new virtual FxL0DFC algorithm serves to prepare parameters for steady-state, and when this happens, the FxDFC algorithm with the parameters provided by FxL0DFC is applied. Compared to using the FxNLMS algorithm to attenuate narrowband periodical noise, the FxDFC algorithm has nearly the same tracking performance while having a low computational load. As a result, the FxL0DFC-based FxNLMS-FxDFC algorithm leads to a reduction of the total computational load. Moreover, the proposed method performs excellently in terms of tracking in simulations and experiments on actual data, particularly in environments with rapid power changes and impulsive noise.

A Study of the Ambient Noise in the Public Space on Campus and the Correlation Between the Campus Crowds’ Ambient Noise and the WiFi Log

Urban noise is becoming more serious and increasingly concerning environmental problems. This has led to numerous studies on traffic noise. However, not many studies have been done on noise from a human perspective as they go about their daily life. In another aspect, using of the crowd-sourcing platform is on the rise as the usage of personal devices (smartphones) and the deployment of Internet-of-thing increases. Thus, a large pool of data collected via mobile applications enables users to measure the environmental factor directly and provide immediate feedback for and community’s greater good. In this paper, we utilize the crowd-sourcing platform to collect noise data by volunteers to study the noise level in a campus environment, in open common areas which are frequented by students. We are able to map out the noise across the campus from the perspective of the students. The noise level increase through the day as the student gather around popular open spaces. Our study shows that the sound level on campus is due mainly to human and mechanical noise. By combining the noise data with WiFi log data, we were able to show a good correlation between sound level and human density in an area

Localization of car engine noise sources

The engine of a vehicle, particularly a passenger car, is one of the main sources of noise radiated into the environment and creates a noise load in residential areas, which has a negative impact on people. Experts in the field of acoustics perform computational and experimental acoustic studies both at the design stage, and at the stage of putting into production and directly operating the engine as part of the car to reduce engine noise. An important stage of acoustic research is the localization of the most intensely radiating noise of systems, mechanisms, nodes and engine parts. The article presents the results of experimental studies on localization of internal combustion engine noise sources of a LADA car.

Ultrasensitive Optical Rotation Detection With Closed-Loop Suppression of Spin Polarization Error

Optical rotation detection system (ORDS) utilizing quantum nondemolition (QND) measurement methods is widely applied in the field of quantum metrology and quantum information. However, the sensitivity of ORDS is limited by the uncertainty from optical-couple noise during the measurement of the atomic spin ensemble. In this study, we specifically analyze the mechanism of optical-couple noise caused by the fluctuations of probe light’s polarization in the modulated ORDS with a new model established to describe atomic spin precession in this particular condition. It is discovered that transverse electron-spin polarization errors are generated by the residual probe photon spin polarization in the ORDS, which results in extra coupling magnetic noise. In order to suppress this noise, a novel in situ method is proposed that the resultant electron-spin errors are reduced by a specifically designed closed-loop system. The results are verified through the ORDS in a co-magnetometer. After zeroing the extra probe photon spin polarization, an angular sensitivity better than <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1 \times 10 ^{\mathrm {-8}}$ </tex-math></inline-formula> rad/Hz <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{\mathrm {1/2}}$ </tex-math></inline-formula> is achieved for frequencies higher than 5 Hz, demonstrating a probe background noise of 0.26 fT/Hz <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{\mathrm {1/2}}$ </tex-math></inline-formula> @14.5 Hz, approaching electronic noise and photon shot noise (PSN). With closed-loop control, the optical rotation bias instability is promoted by 4.2 times (from 107.9 to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$25.7 \mu $ </tex-math></inline-formula> rad/h), and the angular noise of the ORDS is reduced by 2.4 times at 1–100 Hz. The measurement uncertainty of the realized ORDS nears the standard quantum limit, paving the road for long-term ultrasensitive measurements for new physics explorations.

Assessment of Noise Levels in Different Residential, Industrial and Commercial Areas of Jammu City, India

Due to the contemporary mechanical lifestyle noise has been one of the most unwanted by-products. To assess the noise levels in different locations of Jammu city, a study was conducted twice a day i.e., day (6 – 9am) and night (9 pm – 6 am). The present study deals with assessment of noise pollution in different residential, commercial and Industrial areas of Jammu city. The noise level was measured with the help of sound meter (SL 4010) at different locations of Jammu south, north east and west from (June 2016 to May 2017). During the studyperiod, the average noise intensity at various residential sites ranges between 49.8 Leq dB (A) to 68.5Leq dB (A) during day time whereas during the night time ambient noise level ranges between 39.66 dB to 57.3 dB. The results clearly demonstrate that the noise quality at those areas is beyond the permissible limits as specified by Central Pollution Control Board CPCB thus contributing to noise pollution. Moreover, the Leq Max values are also greater than the permissible limits. Major sources of noise pollution are vehicular transport, frequent use of horns in vehicles during the day. Whereas due to traffic jam at night on congested roads and use of loudspeakers and DJ in marriage and banquet halls.

A monitoring campaign (2013–2020) of ESA’s Mars Express to study interplanetary plasma scintillation

AbstractThe radio signal transmitted by the Mars Express (MEX) spacecraft was observed regularly between the years 2013–2020 at X-band (8.42 GHz) using the European Very Long Baseline Interferometry (EVN) network and University of Tasmania’s telescopes. We present a method to describe the solar wind parameters by quantifying the effects of plasma on our radio signal. In doing so, we identify all the uncompensated effects on the radio signal and see which coronal processes drive them. From a technical standpoint, quantifying the effect of the plasma on the radio signal helps phase referencing for precision spacecraft tracking. The phase fluctuation of the signal was determined for Mars’ orbit for solar elongation angles from 0 to 180 deg. The calculated phase residuals allow determination of the phase power spectrum. The total electron content of the solar plasma along the line of sight is calculated by removing effects from mechanical and ionospheric noises. The spectral index was determined as$-2.43 \pm 0.11$which is in agreement with Kolmogorov’s turbulence. The theoretical models are consistent with observations at lower solar elongations however at higher solar elongation ($&gt;$160 deg) we see the observed values to be higher. This can be caused when the uplink and downlink signals are positively correlated as a result of passing through identical plasma sheets.

Unsteady flow behaviors and noise generation mechanisms of tandem orifices in a circular duct

Turbulent flow through tandem orifices in a circular duct is numerically modeled through dynamic delayed detached-eddy simulations to clarify the unsteady flow behaviors and noise generation mechanism. The characteristics of four configurations with different separation distances L/D = 0 (single orifice), 1, 2, and 4 are compared at a Reynolds number of 10 000. The acoustic sources and their noise-propagation behaviors are analyzed using Lighthill's acoustic analogy. The coherent flow structures (wavepackets) are determined through spectral proper orthogonal decomposition to clarify the resulting flow noise mechanism. The dominant noise sources are acoustic dipoles that are alternately energetic on the orifice's leading and trailing faces subjected to intermittent interaction with the unsteady flow. The total sound pressure level (SPL) for a single orifice is alternately dominated by the shedding and flapping behaviors of the large-scale vortical structures in the low-frequency range and Kelvin–Helmholtz (K–H) type wavepackets at high frequencies. For the tandem orifice configuration with L/D = 1, the total SPL is dominated by the contribution of the trailing face, attributable to the interactions between the K–H-type double-wavepacket structures. Both the upstream and downstream wavepackets start to split and generate four-wavepacket structures in the high-frequency range. In the cases of L/D = 2 and 4, the total SPL is dominated by the dipole sources at the downstream leading face that subjected to the intermittent interaction with the upstream separated shear layers. The dominant flow structures are independent wavepackets through each orifice at low frequencies, while at high frequencies the four-wavepacket structures break into two independent double-wavepacket structures close to each orifice.

Amplitude-Varying Perturbation for Balancing Privacy and Utility in Federated Learning

While preserving the privacy of federated learning (FL), differential privacy (DP) inevitably degrades the utility (i.e., accuracy) of FL due to model perturbations caused by DP noise added to model updates. Existing studies have considered exclusively noise with persistent root-mean-square amplitude and overlooked an opportunity of adjusting the amplitudes to alleviate the adverse effects of the noise. This paper presents a new DP perturbation mechanism with a time-varying noise amplitude to protect the privacy of FL and retain the capability of adjusting the learning performance. Specifically, we propose a geometric series form for the noise amplitude and reveal analytically the dependence of the series on the number of global aggregations and the (ϵ,δ)-DP requirement. We derive an online refinement of the series to prevent FL from premature convergence resulting from excessive perturbation noise. Another important aspect is an upper bound developed for the loss function of a multi-layer perceptron (MLP) trained by FL running the new DP mechanism. Accordingly, the optimal number of global aggregations is obtained, balancing the learning and privacy. Extensive experiments are conducted using MLP, supporting vector machine, and convolutional neural network models on four public datasets. The contribution of the new DP mechanism to the convergence and accuracy of privacy-preserving FL is corroborated, compared to the state-of-the-art Gaussian noise mechanism with a persistent noise amplitude.

Grafting Laplace and Gaussian Distributions: A New Noise Mechanism for Differential Privacy

Grafting Laplace and Gaussian Distributions: A New Noise Mechanism for Differential Privacy

Improved Differential Privacy Noise Mechanism in Quantum Machine Learning

Quantum computing, as an emerging research field, is attracting people’s attention. It has been proven to be superior in many ways to classical computing. Differential privacy provides an easy way to achieve demonstrable privacy, and the most common method is to add noise to datasets. At this stage of quantum computers, noise is a factor that cannot be ignored. Indeed, the existence of noise will negatively affect the performance of quantum computers, but we can apply it to privacy protection. In this work, we will consider two situations: inherent noise and artificially added noise. The noise is added to the variational quantum algorithm to implement quantum machine learning with differential privacy. The importance of each type will be examined and less artificial noise is needed for a common privacy budget over classical machine learning. Composition theory will be invoked to prove the advantage of the entire quantum machine learning process.

Noise Model of Large-Format Readout Integrated Circuit for Infrared Focal Plane Array

With the upscaling of the pixel format and the downscaling of the pixel pitch of infrared focal plane arrays (FPAs), the demand for ultra-low-noise design is increasing drastically. Existing methods of noise modelling lack transistor-level analysis and are unable to provide directly effective guidance for circuit design because of extremely complicated mathematical expressions. In this work, a comprehensive noise model of large-format readout integrated circuit (ROIC) is presented, for the first time elucidating the noise mechanism with a full research framework, including transistor-, circuit-, block-, and chip-level analysis. By utilizing a novel approximation method, simplified analytical formulas with high accuracy are obtained for flicker noise and other noise. These simplified formulas clear up the confusions of how the various functional circuit blocks influence noise performance. Moreover, based on the presented noise model, the impacts of crucial parameters on FPA noise are analyzed in detail, and strategies regarding the trade-off between the signal-to-noise ratio (SNR) and other aspects of performance are proposed for low-noise design. Taking an astronomical application with a very long integration time as an example, the calculated results show that an ultralow noise of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${5}{\,e^{-}}$ </tex-math></inline-formula> can be achieved by leveraging the above approaches.

Refined DC and Low-Frequency Noise Characterization at Room and Cryogenic Temperatures of Vertically Stacked Silicon Nanosheet FETs

In this work, two types of gate-all-around (GAA) vertically stacked silicon nanosheet (NS) FETs are investigated, the main difference being the vertical distance between the stacked NSs. Principal electrical parameters are estimated at room and liquid nitrogen temperatures using a refined <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${Y}$ </tex-math></inline-formula> -function methodology, the main advantage being that no extra iterative steps are necessary. The results are confirmed using other derivative dc parameter estimation methodologies. Low-frequency noise measurements evidence variability of the flat-band voltage noise and correlation between the noise level and the low field mobility. The dominant flicker noise mechanism is related to the correlated mobility and carrier number fluctuation mechanism with access resistance noise contribution in very strong inversion. The impact of the access resistance on the estimation of the Coulomb scattering coefficient is evidenced.