Peak Noise Research Articles

Decrease in volcano jet noise peak frequency as crater expands

Volcanic jet noise is the sound, often <20 Hz and termed infrasound, generated by momentum-driven fluid flow through a volcanic vent. Assuming the self-similarity of jet flows and audible jet noise extends to infrasonic volcanic jet noise, the Strouhal number, St, connects frequency changes to those in jet length (expanded jet diameter) and/or velocity scale (jet velocity). We examine the infrasound signals from the June 2019 eruptions of Raikoke, Kuril Islands and Ulawun, Papua New Guinea volcanoes with changes in crater geometry. We use data from the International Monitoring System infrasound network and pre- and post-eruption satellite data (PlanetScope imaging). We observe a decrease in infrasound peak frequency during the transition to a more intense phase, which remains through the end of both eruptions. With the PlanetScope data, we measured a crater area increase of ∼50 000 m2 at Raikoke and ∼31 000 m2 at Ulawun. We use crater diameter as a proxy for expanded jet diameter. Our analysis suggests that the increases in crater diameter alone cannot account for the decreases in peak frequency for a constant St. This suggests the jet velocity also increased, which fits satellite data, and or the fluid properties (e.g., particle loading, nozzle characteristics, etc.) changed. This is reasonable as the eruptions intensified, which likely involved an increase in jet velocity and erosion of the crater walls. This is the first study to corroborate the decrease in infrasound peak frequency with documented increase in crater area.

Improving the Visualization of the Adrenal Veins Using Virtual Monoenergetic Images from Dual-Energy Computed Tomography before Adrenal Venous Sampling

(1) Background: This study explored the optimal energy level in advanced virtual monoenergetic images (VMI+) from dual-energy computed tomography angiography (DE-CTA) for adrenal veins visualization before adrenal venous sampling (AVS). (2) Methods: Thirty-nine patients were included in this prospective single-center study. The CT value, noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured in both adrenal veins and abdominal solid organs and were then compared between VMI+ within the range of 40-80 kiloelectron volt (keV). The visualization rate of the adrenal veins and the overall image quality of solid organs were subjectively compared among different keV VMI+. The AVS success rate was recorded for 20 patients. (3) Results: For the adrenal veins, 40 keV VMI+ had the peak CT value, noise and CNR (p < 0.05). Subjectively, the visualization rate was the highest at 40 keV (100% for the right adrenal vein, and 97.4% for the left adrenal vein) (p < 0.05). For solid organs, the CT value, noise and CNR at 50 keV were lower than those at 40 keV (p < 0.05), but the SNR was similar between 40 keV and 50 keV. The overall subjective image quality of solid organs at 50 keV was the best (p < 0.05). The AVS success rate was 95%. (4) Conclusions: For VMI+, 40 keV was the preferential energy level to obtain a high visualization rate of the adrenal veins and a high success rate of AVS, while 50 keV was the favorable energy level for the depiction of abdominal organs.

Deep learning on lateral flow immunoassay for the analysis of detection data.

Lateral flow immunoassay (LFIA) is an important detection method in vitro diagnosis, which has been widely used in medical industry. It is difficult to analyze all peak shapes through classical methods due to the complexity of LFIA. Classical methods are generally some peak-finding methods, which cannot distinguish the difference between normal peak and interference or noise peak, and it is also difficult for them to find the weak peak. Here, a novel method based on deep learning was proposed, which can effectively solve these problems. The method had two steps. The first was to classify the data by a classification model and screen out double-peaks data, and second was to realize segmentation of the integral regions through an improved U-Net segmentation model. After training, the accuracy of the classification model for validation set was 99.59%, and using combined loss function (WBCE + DSC), intersection over union (IoU) value of segmentation model for validation set was 0.9680. This method was used in a hand-held fluorescence immunochromatography analyzer designed independently by our team. A Ferritin standard curve was created, and the T/C value correlated well with standard concentrations in the range of 0-500 ng/ml (R 2 = 0.9986). The coefficients of variation (CVs) were ≤ 1.37%. The recovery rate ranged from 96.37 to 105.07%. Interference or noise peaks are the biggest obstacle in the use of hand-held instruments, and often lead to peak-finding errors. Due to the changeable and flexible use environment of hand-held devices, it is not convenient to provide any technical support. This method greatly reduced the failure rate of peak finding, which can reduce the customer's need for instrument technical support. This study provided a new direction for the data-processing of point-of-care testing (POCT) instruments based on LFIA.

Development of a Gaussian-Based Alignment Algorithm for the Ultrahigh-Resolution Mass Spectra of Dissolved Organic Matter

The alignment of ultrahigh-resolution mass spectra (UHR-MS) is critical to inspect the presence of unique and common peaks across multiple UHR-MS spectra. However, few attempts have been conducted to develop an automated alignment method. In this study, a novel automated alignment algorithm, namely, FTMSCombine, that follows a Gaussian distribution of mass errors was developed and then integrated with existing FTMSCalibrate and TRFu algorithms to establish an open-source analysis platform, namely, FTMSAnalysis, for the UHR-MS analysis of the dissolved organic matter. The developed FTMSCombine was capable of automatically aligning peaks across different UHR-MS spectra by averaging the m/z values of each peak cluster, although the alignment should be restricted to Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) spectra collected by instruments under similar conditions. The FTMSCombine exhibited an insignificant difference in the reproducibility of chemical formulae but significantly higher mass accuracy than the ICBM-OCEAN. In addition to improving the overall mass accuracy of the whole UHR-MS dataset, the FTMSCombine could effectively exclude scatters or noise peaks using an optional rule that restricts peaks (continuously) detected in at least a certain number of spectra in the UHR-MS spectra dataset. The successfully established FTMSAnalysis (freely available in the Supporting Information of this study) is of great potential in automatically analyzing UHR-MS spectra for dissolved organic matter (DOM) and will largely facilitate the elucidation of DOM chemodivesity by UHR-MS techniques including FTICR-MS.

Biometric authentication security enhancement under quantum dot light-emitting diode display via fingerprint imaging and temperature sensing

We improved biometric authentication security using dual recognition based on fingerprint image detection and skin-temperature-change sensing under quantum dot light-emitting diode (QLED) displays. QLEDs are more advantageous than organic light-emitting diodes (OLEDs) in terms of the contrast classification of patterns such as those in fingerprint recognition, owing to their narrow full-width-half-maximum. In this work, scattered, transmitted, and reflected light was captured from the top of the QLED, improving the digital luminance by 25%, as compared with that of OLEDs, because the electroluminescence spectra of the QLED were sustained, whereas those of the OLED were distorted by the generated noise peaks. A QLED with eight apertures sized up to tens of micrometers, mimicking the actual wiring structure of commercialized smartphones, was implemented to detect human fingerprints. The QLED using reduced graphene oxide as the temperature sensor detected temperature changes instantaneously upon finger touch, showing a 2% temperature response based on the human body temperature; however, the temperature change was less than 0.1% for spoof fingerprints printed on paper. Thus, this study successfully enhanced biometric authentication security, through fingerprint recognition based on image sensing using an optical system with micrometer-sized apertures and skin-temperature detection under QLED displays.

Study of Conducted EMI Noise Peak in 10MHz-30MHz Band

Study of Conducted EMI Noise Peak in 10MHz-30MHz Band

Experimental and numerical study on noise reduction of airfoil with the bioinspired ridge-like structure

In general, the serrated blade edge can reduce the aeroacoustic noise of the thin airfoil, but the blade's integrity and pneumatic efficiency cannot be guaranteed. This research proposes a bioinspired ridge-like structure that won't affect the strength of the blade, and it has more potential to be employed as an innovative noise reduction configuration for engineering applications. The experimental data shows a significant peak noise reduction of nearly 26 dB and a magnitude decrease of more than 10 dB in the overall sound pressure level (OASPL) at a freestream velocity of 20 m/s with the attack angle 0˚. Based on the computational fluid dynamic simulation, the mechanism for the noise reduction employing the ridge-like structure is qualitatively and quantitatively examined. In summary, the ridge-like structures on the leading edge may enhance the transition to move an upstream position. Under the synergy of the ridge-like structures on the leading and trailing edges, the turbulent kinetic energy (TKE) value close to the airfoil surface is reduced, and the spanwise coherence of the surface pressure fluctuation source weakens. The phase spectra analysis indicates that the phases of the fluctuation pressure signals beside the center of the two adjacent ridge-like structures are opposite, and therefore the phase interference in the biomimetic airfoil between two adjacent ridge-like structures is significantly enhanced in the frequency range from 100 Hz to 800 Hz. For the biomimetic airfoil described in this paper, the phase interference between adjacent ridge-like structures immediately results in noise.

Vermilion flycatchers avoid singing during sudden peaks of anthropogenic noise

Vermilion flycatchers avoid singing during sudden peaks of anthropogenic noise

Experimental Assessment of the Acoustic Performance of Nozzles Designed for Clean Agent Fire Suppression

Discharge through nozzles used in gas-based fire protection of data centers may generate noise that causes the performance of hard drives to decay considerably; silent nozzles are employed to limit this harmful effect. This work focuses on proposing an experimental methodology to assess the impact of sound emitted by gaseous jets by comparing various nozzles under several operating conditions, together with relating that impact to design parameters. A setup was developed and repeatability of the experiments was evaluated; standard and silent nozzles were tested regarding the discharge of inert gases and halocarbon compounds. The ability of silent nozzles to contain the emitted noise—generally below the 110 dB reference threshold—was proven effective; a relationship between Reynolds number and peak noise level is suggested to support the reported increase in noise maxima as released flow rate increases. Hard drives with lower speed were the most affected. Spectral analysis was conducted, with sound at the higher frequency range causing performance decay even if lower than the acknowledged threshold. Independence of emitted noise from the selected clean agent was also observed in terms of released volumetric flow rate, yet the denser the fluid, the lower the generated noise under the same released mass flow rate.

Evaluation of acoustic performance of cascaded cylindrical micro-perforated panel

A cylindrical micro-perforated panel (MPP) can be used to absorb the sound of a flow system in a circular duct of a vacuum cleaner. A cascaded cylindrical MPP is a special class type where two cylindrical MPPs are arranged in a series to improve sound attenuation. The manufacturing of MPP primarily involves the machining of micro-perforations, because small holes are not readily made using injection moulding due to the complexity of the die, flow control of the molten polymer through the small orifices and dimensional stability, making it unsuitable for mass production. This limitation can be overcome with the use of additive manufacturing (AM) technology, where the micro-perforations can be designed and manufactured, with relatively larger tolerances. Experimental validation ensures that the manufactured prototype in this study is performed according to design. Results show that the transmission loss of the model and the experimental outcomes agree. The cascaded arrangement of the cylindrical MPP results in a wider effective frequency range and an increased transmission loss. Parametric studies of the combined effects of the perforation diameter, perforation ratio and the depth of air cavity on the diameter of the duct and length ratio are conducted using a transfer matrix method. A case study is demonstrated here in the design. Moreover, an AM of cascaded cylindrical MPP is performed to attenuate peak noise at 1650 Hz, where the optimum parameters of the cascaded cylindrical MPP are obtained using a genetic algorithm. The manufactured cascaded cylindrical MPP is installed on a vacuum cleaner duct, and the measurement of sound power level shows a reduction of 4 dB(A).

Aeroacoustic Benchmarking of Trailing-Edge Noise from NACA Airfoil with Trailing-Edge Serrations

Experimental results on trailing-edge (TE) noise from a NACA airfoil are presented for a chord-based Reynolds number range between and . Far-field TE noise from the baseline airfoil with a straight TE and TE serrations is measured with varying , angle of attack, and serration shape and flap angle. Additionally, aerodynamic coefficients and boundary-layer parameters at the TE are also reported. To cover such a broad range, two NACA airfoil models were tested in two different wind tunnels. The measurements include the emitted noise with natural and forced transition locations. For the straight TE, the forced transition location results in up to 5 dB increase of the far-field TE noise level, compared to the natural one. Scaling of the far-field noise spectra from the baseline TE shows that the Strouhal numbers at which the peak noise level is measured reduce as increases. TE noise spectra for the cases with the TE serrations are found to be dependent on the airfoil lift and . The present data are to be included in the framework of the Benchmark Problems for Airframe Noise Computations category I and are publicly available in a repository with the following digital object identifier (DOI): https://doi.org/10.4121/20940646.

Study of Resonant Peak Characteristics of Flow-Induced Noise in Small-Aperture Cavity

The influences of the length and width of small-aperture cavity are calculated with the [Formula: see text]–[Formula: see text] model and large eddy simulation on the frequencies of resonant peaks of flow-induced cavity noise at different flow velocities in water. The calculated results show that the semi-empirical Rossiter formulas are only suitable for large-aperture models. For small-aperture cavity models, the resonance peak frequencies predicted by these formulas deviate greatly from the corresponding numerical results. In addition, as the length of cavity opening decreases, the minimum flow velocity gradually increases, at which a resonant peak just appears. Finally, the range of this minimum flow velocity is given for the different opening lengths.

Prediction and environmental appraisal of traffic noise intensity by auto-regressive integrated moving average technique

Auto-regressive integrated moving average (ARIMA) assessment of traffic noise was conducted on different routes in Port Harcourt, Nigerian metropolis. This was achieved by measuring the traffic noise on the various routes of asphalt flexible and concrete rigid pavement structures with a meter for sound measurement with regards to the volume of traffic, vehicle movement rate, and location away from the midpoint of the highway. The average peak noise of traffic was obtained at selected distances of 5m, 10m, and 15m from the middle of the highway, for locations 1, 2, 3 and their mean average case 4 (Trunk A flexible pavement), for location 5 (Trunk C flexible pavement), and for location 6 (Trunk C rigid pavement). The results of the investigation show that the values of traffic noise at locations 1 to 3 and their mean average case 4 had the same range of high noise intensity as Trunk A flexible pavement and classified as heavy-traveled roads; while conversely, location 5 (Trunk C) had the same range of lower noise intensity, which was classified as light-traveled road. For Trunk C, the noise generated in a flexible pavement was less than that from a rigid pavement. Generally, the R2 values of the ARIMA models showed very good performance along selected travel routes. For case-specific distances, the ARIMA models performed very efficiently and had very high R2 values.

Investigation of ZVS Criteria and Optimization of Switching Loss in a Triple Active Bridge Converter Using Penta-Phase-Shift Modulation

Triple active bridge (TAB) as an isolated multiport dc–dc converter is a promising solution for integrated energy management systems to maintain an efficient power flow between the ports. This article presents the design, modeling, and switching loss optimized phase-duty-controlled PWM modulation scheme of a TAB converter composed of three full-bridge modules and a high-frequency planar transformer. The work aims at the derivation and analysis of the zero-voltage switching (ZVS) conditions for a TAB, where the turn-on switching loss is mitigated along with attaining an improved EMI performance, comprising of reduced noise peaks. Moreover, an optimized five-variable control-based TAB PWM modulation technique is proposed in this article in order to achieve minimized switching loss and the overall system loss for a wide voltage gain and load range. The instantaneous switching currents, responsible for the switching losses at the devices, are derived from the transformer winding current expressions, formulated employing the generalized harmonic approximation (GHA) technique. The various loss minimization techniques and the theoretically obtained criteria for ZVS are experimentally verified using a laboratory-developed prototype of an 800-W TAB converter. With the implementation of the proposed optimal phase-duty control, the experimental results show a nonunity gain light-load efficiency increment up to 10% compared to the conventional phase-shift modulation alone.

A hybrid feedforward/feedback multi-channel active control system with optimization for cancelling road noise inside a vehicle cabin

A hybrid feedforward/feedback multi-channel system was developed for active road noise control (ARNC) inside a vehicle cabin. First, a centralized feedforward subsystem was present with a multi-channel normalized weighted error FxLMS algorithm, including a simplified reference signal normalization method, a reconstructed filter bank for filtering the reference signals, and a newly defined cost function of A-weighting error signals. Second, a distributed feedback subsystem was presented with multiple feedback single-channel simplified normalized FxLMS algorithms. By combining the two subsystems, a hybrid ARNC system was developed. Furthermore, data related to the ARNC system were collected from the test vehicle. Next, a nondominated sorting genetic algorithm-II was introduced to optimize the system parameter. Multi-objective optimization models of the feedforward and hybrid ARNC systems were established respectively, and the optimal Pareto solution sets for their parameters were obtained. Real-time experiments show that, when the test vehicle driving at 60 km/h on the small brick pavement, the developed hybrid ARNC system can achieve an overall noise reduction of 5.87 dBA in the time domain, and a peak noise reduction of 7.43 dBA in the frequency-domain. Compared with the feedforward ARNC system, road noise reduction is much improved. It still has a good noise reduction effect at other speeds and on different roads.

Analysis and Control of Abnormal Vibration of End Wall on High-Speed Electric Multiple Units

In view of the abnormal vibration of the body end wall during the high-speed operation of electric multiple units (referred hereafter as EMU), the vibration and noise characteristics of the body end wall area are analyzed through the line test. Combined with the end wall modal simulation results, the generation mechanism of the abnormal vibration of the body end wall is analyzed. The results show that when the train is running at a high speed, the aerodynamic excitation of the windshield cavity outside the body end wall acts on the end wall, arousing the first-order bending natural frequency of the body end wall, resulting in resonance of the body end wall, and then causing abnormal vibration and noise in the body end wall area. In order to solve this problem, installing a deflector (guiding plate) above the windshield in the vehicle body end wall area can effectively suppress the aerodynamic excitation acting on the vehicle body end wall. After optimization, the abnormal vibration and noise in the vehicle body end wall area are significantly reduced. The corresponding peak value at 40 Hz of the vehicle body end wall vibration spectrum is reduced by 85%, and the peak noise is reduced by 12%, The correctness of the mechanism analysis of abnormal vibration in the headwall area is verified, which provides a reference basis for guiding the structural optimization and operation and maintenance of rail vehicles.

Experimental investigation on two-phase flow noise characteristics of R410A through electronic expansion valve of multi-split air conditioner

The refrigerant flowing through an electronic expansion valve (EEV) of a multi-split air conditioner is usually in two-phase state which may generate more severe flow noise than that in sub-cooled state. The purpose of this paper is to experimentally investigate the influences of the two-phase R410A operation conditions on the flow noise characteristics in the EEV, including listening sense forms, frequency distributions and sound pressure levels (SPLs). The experimental conditions cover the refrigerant mass flow rate ranging from 30 to 90 kg h–1 and the refrigerant quality ranging from 0.02 to 0.4. The results show that low mass flow rate facilitates the reduction of noise frequency, and the peak noise frequency was reduced by up to 32% as the mass flow rate decreased. Low refrigerant quality helps to reduce the SPL of flow noise, and the average SPL decreased by 6 dB as the refrigerant quality decreased. The guidance of inlet flow pattern by transforming the churn flow to the annular flow helps to simultaneously reduce the noise frequency and SPL, and the peak noise frequency as well as the averaged SPL decreased by 47% and 4 dB, respectively. Moreover, the hissing noise and the gurgling noise are the only two kinds of listening sense forms of flow noise detected in the present experiment, and the peak frequency and the average SPL of hissing noise are both higher than those of gurgling noise.

Medical Image Fusion Using CNN with Automated Pooling

Background/Objectives : The purpose of this study is to demonstrate that the most appropriate pooling is selected among different types of pooling techniques in CNN, for different applications related to image fusion. The work presents a novel method by which pooling is selected automatically as per the needs of the application. Methods: This study presents the use of multiple functions for pooling techniques which are selected automatically based on the input images to produce fused optimum output. This will make the classification process much easier and better end results are obtained. Finding: The developed automated pooling method performs better concerning processing time and produces optimal output for parameters like Peak Noise Signal Ratio, Mean Square Error, Fusion Factor, Fusion Fidelity, and Visual Information Fidelity in comparison to existing methods like Discrete Wavelet Transformation, Non-Subsampled Contourlet Transform, and Principal Component Analysis. Novelty: The novel technique presented in this paper for automated selection of pooling method provides optimal dimension reduction in both the phases of CNN, and hence allows CNN to converge faster and optimally. Keywords: Image Fusion; CNN; Machine Learning; Pooling; Medical Image Analysis

Common-Mode Driven Synchronous Filtering of the Powerline Interference in ECG

Powerline interference (PLI) is a major disturbing factor in ground-free biopotential acquisition systems. PLI produces both common-mode and differential input voltages. The first is suppressed by a high common-mode rejection ratio of bioamplifiers. However, the differential PLI component evoked by the imbalance of electrode impedances is amplified together with the diagnostic differential biosignal. Therefore, PLI filtering is always demanded and commonly managed by analog or digital band-rejection filters. In electrocardiography (ECG), PLI filters are not ideal, inducing QRS and ST distortions as a transient reaction to steep slopes, or PLI remains when its amplitude varies and PLI frequency deviates from the notch. This study aims to minimize the filter errors in wide deviation ranges of PLI amplitudes and frequencies, introducing a novel biopotential readout circuit with a software PLI demodulator–remodulator concept for synchronous processing of both differential-mode and common-mode signals. A closed-loop digital synchronous filtering (SF) algorithm is designed to subtract a PLI estimation from the differential-mode input in real time. The PLI estimation branch connected to the SF output includes four stages: (i) prefilter and QRS limiter; (ii) quadrature demodulator of the output PLI using a common-mode driven reference; (iii) two servo loops for low-pass filtering and the integration of in-phase and quadrature errors; (iv) quadrature remodulator for synthesis of the estimated PLI using the common-mode signal as a carrier frequency. A simulation study of artificially generated PLI sinusoids with frequency deviations (48–52 Hz, slew rate 0.01–0.1 Hz/s) and amplitude deviations (root mean square (r.m.s.) 50–1000 μV, slew rate 10–200 μV/s) is conducted for the optimization of SF servo loop settings with artificial signals from the CTS-ECG calibration database (10 s, 1 lead) as well as for the SF algorithm test with 40 low-noise recordings from the Physionet PTB Diagnostic ECG database (10 s, 12 leads) and CTS-ECG analytical database (10 s, 8 leads). The statistical study for the PLI frequencies (48–52 Hz, slew rate ≤ 0.1 Hz/s) and amplitudes (≤1000 μV r.m.s., slew rate ≤ 40 μV/s) show that maximal SF errors do not exceed 15 μV for any record and any lead, which satisfies the standard requirements for a peak ringing noise of &lt; 25 μV. The signal-to-noise ratio improvement reaches 57–60 dB. SF is shown to be robust against phase shifts between differential- and common-mode PLI. Although validated for ECG signals, the presented SF algorithm is generalizable to different biopotential acquisition settings via surface electrodes (electroencephalogram, electromyogram, electrooculogram, etc.) and can benefit many diagnostic and therapeutic medical devices.

Sensing Remote Bulk Defects through Resistance Noise in a Large-Area Graphene Field-Effect Transistor

The substrate plays a crucial role in determining the transport and low-frequency noise behavior of graphene field-effect devices. Typically, a heavily doped Si/SiO2 substrate is used to fabricate these devices for efficient gating. Trapping-detrapping processes close to the graphene/substrate interface are the dominant sources of resistance fluctuations in the graphene channel, while Coulomb fluctuations arising due to any remote charge fluctuations inside the bulk of the substrate are effectively screened by the heavily doped substrate. Here, we present the electronic transport and low-frequency noise characteristics of a large-area CVD graphene field-effect transistor (FET) prepared on a lightly doped Si/SiO2 substrate (NA ≈ 1015 cm-3). Through a systematic characterization of transport, noise, and capacitance at various temperatures, we reveal that the remote Si/SiO2 interface can affect the charge transport in graphene severely and any charge fluctuations inside the bulk of the silicon substrate can be sensed by the graphene channel. The resistance (R) vs back-gate voltage (Vbg) characteristics of the device show a hump around the depletion region formed at the SiO2/Si interface, confirmed by the capacitance (C)-voltage (V) measurement. A low-frequency noise measurement on these fabricated devices shows a peak in the noise amplitude close to the depletion region. This indicates that due to the absence of any charge layer at the Si/SiO2 interface, the screening ability decreases, and as a consequence, any fluctuations in the deep-level Coulomb impurities inside the silicon substrate can be observed as noise in resistance in the graphene channel via mobility fluctuations. The noise behavior on ionic liquid-gated graphene on the same substrate exhibits no such peak in noise and can be explained by the interfacial trapping-detrapping processes close to the graphene channel. Our study will definitely be useful for integrating graphene with the existing silicon technology, in particular, for high-frequency applications.