Background Noise Research Articles

Improving ambient noise cross-correlations using a polarization-based azimuth filter

Seismic interferometry is widely used to image and monitor earth structures at different scales by extracting an empirical Green’s function (EGF) from the cross-correlation of ambient noise under the assumption of diffuse wavefields or energy equipartitioning. The EGFs, however, may be incorrectly estimated and lead to a misunderstanding of subsurface structures, because the distribution of ambient noise sources is neither isotropic nor stationary. To extract reliable EGFs from the non-ideal ambient noise data, we propose a polarization-based azimuth filter (PAF) to attenuate the ambient noise energy of non-stationary sources to improve the quality of cross-correlation functions. The PAF is a time-frequency domain azimuth filter for three-component seismic data, which uses time-frequency polarization analysis to measure azimuths of ambient noise signals, and then filters the three-component data to obtain signals from desired directions. Based on the stationary-phase theory, we use the PAF to extract the ambient noise signals from the stationary-phase zones (SPZs), which improves the quality of the cross-correlation function and gets rid of the requirement for long observations. A synthetic test and two short-time engineering examples demonstrate that uneven source distributions might cause serious spurious signals in EGFs and we show the improvement in EGFs using our method. In addition, the PAF may allow for the complete separation of the fundamental and higher mode of Rayleigh waves, which uncovers more information implicit in the ambient noise data.

Crossmodal semantic congruence guides spontaneous orienting in real-life scenes.

In real-world scenes, the different objects and events are often interconnected within a rich web of semantic relationships. These semantic links help parse information efficiently and make sense of the sensory environment. It has been shown that, during goal-directed search, hearing the characteristic sound of an everyday life object helps finding the affiliate objects in artificial visual search arrays as well as in naturalistic, real-life videoclips. However, whether crossmodal semantic congruence also triggers orienting during spontaneous, not goal-directed observation is unknown. Here, we investigated this question addressing whether crossmodal semantic congruence can attract spontaneous, overt visual attention when viewing naturalistic, dynamic scenes. We used eye-tracking whilst participants (N = 45) watched video clips presented alongside sounds of varying semantic relatedness with objects present within the scene. We found that characteristic sounds increased the probability of looking at, the number of fixations to, and the total dwell time on semantically corresponding visual objects, in comparison to when the same scenes were presented with semantically neutral sounds or just with background noise only. Interestingly, hearing object sounds not met with an object in the scene led to increased visual exploration. These results suggest that crossmodal semantic information has an impact on spontaneous gaze on realistic scenes, and therefore on how information is sampled. Our findings extend beyond known effects of object-based crossmodal interactions with simple stimuli arrays and shed new light on the role that audio-visual semantic relationships out in the perception of everyday life scenarios.

A comparative review of the application value of FAPI PET/CT and 18F-FDG PET/CT in lung cancer.

Fibroblast activation protein inhibitor (FAPI) positron emission tomography/computed tomography (PET/CT) is a multimodal imaging technique that combines PET and CT, utilizing FAP inhibitors as radiotracers. Fibroblast activation protein, a serine protease highly expressed in many epithelial tumor-associated fibroblasts, plays a crucial role in tumor stroma formation and remodeling. Through the detection of FAP expression, FAPI PET/CT facilitates the diagnosis and staging of both benign and malignant pulmonary tumors. In contrast to traditional fluorine-18-fluorodeoxyglucose (18F-FDG) PET/CT focusing on glucose metabolism, FAPI PET/CT offers benefits such as enhanced specificity, reduced background noise, accelerated imaging speed, and decreased radiation exposure. This review provides an overview of the progress in applying FAPI PET/CT and 18F-FDG PET/CT in pulmonary malignancies and discusses current challenges and future prospects.

Cortical and Subjective Measures of Individual Noise Tolerance Predict Hearing Outcomes with Varying Noise Reduction Strength

Noise reduction (NR) algorithms are employed in nearly all commercially available hearing aids to attenuate background noise. However, NR processing also involves undesirable speech distortions, leading to variability in hearing outcomes among individuals with different noise tolerance. Leveraging 30 participants with normal hearing engaged in speech-in-noise tasks, the present study examined whether the cortical measure of neural signal-to-noise ratio (SNR)—the amplitude ratio of auditory evoked responses to target speech onset and noise onset—could predict individual variability in NR outcomes with varying strength, thus serving as a reliable indicator of individual noise tolerance. In addition, we also measured subjective ratings of noise tolerance to see if these measures could capture different perspectives on individual noise tolerance. Results indicated a significant correlation between neural SNR and NR outcomes that intensified with increasing strength of NR processing. While subjective ratings of noise tolerance were not correlated with the neural SNR, noise-tolerance ratings could predict outcomes with stronger NR processing and account for additional variance in the regression model, although the effect was limited. Our findings underscore the importance of accurately assessing an individual’s noise tolerance characteristics in predicting perceptual benefits from various NR processing methods and suggest the advantage of incorporating both cortical and subjective measures in the relevant methodologies.

Factors associated with difficult intravenous access in the paediatric emergency department: A prospective cohort study.

Although it is the most performed invasive procedure, peripheral intravenous catheter (PIVC) insertion in children can be difficult. The primary objective of the study was to identify the factors associated with difficult intravenous access (DIVA) in the paediatric ED, including patient, proceduralist and situational factors. This was a single-centre prospective observational cohort study conducted over 28 consecutive days. Research assistants observed PIVC insertion attempts for children under 16 years of age and recorded data for variables relating to the patient, proceduralist and event. Univariate logistic regression modelling was performed to identify factors associated with DIVA, defined as unsuccessful PIVC insertion on the first attempt. A total of 134 participants were recruited; 66 were male (49%) with a median age of 5.7 years. Fifty-two (39%) were classified as having DIVA. There was a total of 207 PIVC insertion attempts with two or more attempts needed for 48 children (36%). Patient factors associated with DIVA included age of 3 years or less and limited vein options. Proceduralist factors included gestalt of 50% or less chance of success, use of a larger gauge (smaller bore) PIVC and less PIVC insertion experience. Situational factors included a combative child, higher pain score and loud ambient noise. The present study identified multiple patient, proceduralist and situational factors that were associated with DIVA in the paediatric ED. Future studies should explore the development and implementation of a package to address DIVA in children, with the patient-centred goals of reducing pain and improving success.

One-Pot Preparation of Ratiometric Fluorescent Molecularly Imprinted Polymer Nanosensor for Sensitive and Selective Detection of 2,4-Dichlorophenoxyacetic Acid

The development of fluorescent molecular imprinting sensors for direct, rapid, and sensitive detection of small organic molecules in aqueous systems has always presented a significant challenge in the field of detection. In this study, we successfully prepared a hydrophilic colloidal molecular imprinted polymer (MIP) with 2,4-dichlorophenoxyacetic acid (2,4-D) using a one-pot approach that incorporated polyglycerol methacrylate (PGMMA-TTC), a hydrophilic macromolecular chain transfer agent, to mediate reversible addition-fragmentation chain transfer precipitation polymerization (RAFTPP). To simplify the polymerization process while achieving ratiometric fluorescence detection, red fluorescent CdTe quantum dots (QDs) and green fluorescent nitrobenzodiazole (NBD) were introduced as fluorophores (with NBD serving as an enhancer to the template and QDs being inert). This strategy effectively eliminated background noise and significantly improved detection accuracy. Uniform-sized MIP microspheres with high surface hydrophilicity and incorporated ratiometric fluorescent labels were successfully synthesized. In aqueous systems, the hydrophilic ratio fluorescent MIP exhibited a linear response range from 0 to 25 μM for the template molecule 2,4-D with a detection limit of 0.13 μM. These results demonstrate that the ratiometric fluorescent MIP possesses excellent recognition characteristics and selectivity towards 2,4-D, thus, making it suitable for selective detection of trace amounts of pesticide 2,4-D in aqueous systems.

Visual arsenic detection in environmental waters: Innovating with a naked-eye biosensor for universal application

Arsenic contamination in environmental water sources poses a significant threat to human health, necessitating the development of sensitive and accessible detection methods. This study presents a multidimensional optimization of a bacterial biosensor for the susceptible and deoxyviolacein (DV)-based visual detection of arsenic. The research involved screening six different arsenic resistance (ars) operons and optimizing the genetic circuit to minimize background noise. Introducing an arsenic-specific transport channel enhanced the sensor's sensitivity to 1 nM with a quantitative range from 0.036 to 1.171 μM. The pigment-based biosensor offers a simple colorimetric approach for arsenic detection without complex instrumentation. The preferred biosensor demonstrated characteristics of anti-chelating agent interference, consistently quantified As(III) concentrations ranging from 0.036 to 1.171 μM covering the World Health Organization (WHO) drinking water limit. Innovatively, it effectively detects arsenic in seawater within a linear regression range of 0.071 to 1.125 μM. The biosensor's selectivity for arsenic was confirmed, with minimal cross-response to group 15 metals. Our naked-eye biosensor offers a novel approach for the rapid, on-site detection of arsenic in various water sources. Its simplicity, cost-effectiveness, and versatility make it a valuable tool for environmental monitoring and public health initiatives.

PET digitization chain for Monte Carlo simulation in GATE

Objective. We introduce a versatile methodology for the accurate modelling of PET imaging systems via Monte Carlo simulations, using the Geant4 application for tomographic emission (GATE) platform. Accurate Monte Carlo modelling involves the incorporation of a complete analytical signal processing chain, called the digitizer in GATE, to emulate the different count rates encountered in actual positron emission tomography (PET) systems. Approach. The proposed approach consists of two steps: (1) modelling the digitizer to replicate the detection chain of real systems, covering all available parameters, whether publicly accessible or supplied by manufacturers; (2) estimating the remaining parameters, i.e. background noise level, detection efficiency, and pile-up, using optimisation techniques based on experimental single and prompt event rates. We show that this two-step optimisation reproduces the other experimental count rates (true, scatter, and random), without the need for additional adjustments. This method has been applied and validated with experimental data derived from the NEMA count losses test for three state-of-the-art SiPM-based time-of-flight (TOF)-PET systems: Philips Vereos, Siemens Biograph Vision 600 and GE Discovery MI 4-ring. Main results. The results show good agreement between experiments and simulations for the three PET systems, with absolute relative discrepancies below 3%, 6%, 6%, 7% and 12% for prompt, random, true, scatter and noise equivalent count rates, respectively, within the 0–10 kBq·ml−1 activity concentration range typically observed in whole-body 18F scans. Significance. Overall, the proposed digitizer optimisation method was shown to be effective in reproducing count rates and NECR for three of the latest generation SiPM-based TOF-PET imaging systems. The proposed methodology could be applied to other PET scanners.

Anthropogenic Fingerprint Detectable in Upper Tropospheric Ozone Trends Retrieved from Satellite.

Tropospheric ozone (O3) is a strong greenhouse gas, particularly in the upper troposphere (UT). Limited observations point to a continuous increase in UT O3 in recent decades, but the attribution of UT O3 changes is complicated by large internal climate variability. We show that the anthropogenic signal ("fingerprint") in the patterns of UT O3 increases is distinguishable from the background noise of internal variability. The time-invariant fingerprint of human-caused UT O3 changes is derived from a 16-member initial-condition ensemble performed with a chemistry-climate model (CESM2-WACCM6). The fingerprint is largest between 30°S and 40°N, especially near 30°N. In contrast, the noise pattern in UT O3 is mainly associated with the El Niño-Southern Oscillation (ENSO). The UT O3 fingerprint pattern can be discerned with high confidence within only 13 years of the 2005 start of the OMI/MLS satellite record. Unlike the UT O3 fingerprint, the lower tropospheric (LT) O3 fingerprint varies significantly over time and space in response to large-scale changes in anthropogenic precursor emissions, with the highest signal-to-noise ratios near 40°N in Asia and Europe. Our analysis reveals a significant human effect on Earth's atmospheric chemistry in the UT and indicates promise for identifying fingerprints of specific sources of ozone precursors.

Adaptive complementary neighboring sub-aperture beamforming for thermoacoustic imaging.

When applied to thermoacoustic imaging (TAI), the delay-and-sum (DAS) algorithm produces strong sidelobes due to its disadvantages of uniform aperture weighting. As a result, the quality of TAI images recovered by DAS is often severely degraded by strong non-coherent clutter, which restricts the development and application of TAI. To address this issue, we propose an adaptive complementary neighboring sub-aperture (NSA) beamforming algorithm for TAI. In NSA, we introduce a coordinate system transformation when calculating the normalized cross-correlation (NCC) matrix. This approach enables the computation of the NCC coefficient within the specified kernel without complex coordinate calculations. We first conducted the numerical simulation experiment to validate NSA using a tree branch phantom. In addition, we also conducted phantom (five sauce tubes), ex vivo (ablation needle in ex vivo porcine liver), and in vivo (human arm) TAI experiments using our TAI system with a center frequency of 3GHz. In the numerical simulation experiment, the structural similarity index (SSIM) value for NSA is increased from 0.37828 for DAS to 0.75492. In the point target phantom TAI experiment, the generalized contrast-to-noise ratio (gCNR) value for NSA is increased from 0.936 for DAS to 0.962. The experimental results show that NSA can recover clearer thermoacoustic images compared to DAS. In the ex vivo TAI experiment, the full width at half maxima (FWHM) of an ablation needle (diameter=1.5mm) for coherence factor (CF) weighted DAS and NSA are 0.9 and 1.3mm, respectively. Furthermore, in the in vivo TAI experiment, CF reduces the signals within the arm compared to NSA. Therefore, compared with CF, NSA can maintain the integrity of target information in TAI while effectively suppressing non-coherent background clutter. NSA can effectively reduce non-coherent background noise while ensuring the completeness of the target information. So, NSA offers the potential to provide high-quality thermoacoustic images and further advance their clinical application.

Highly Sensitive Microfluidic Sensor Using Integrated Optical Fiber and Real-time Single-cell Raman Spectroscopy for Diagnosis of Pancreatic Cancer

Pancreatic cancer is notoriously lethal due to its late diagnosis and poor patient response to treatments, posing a significant clinical challenge. This study introduced a novel approach that combines a single-cell capturing platform, tumor-targeted silver (Ag) nanoprobes, and precisely docking tapered fiber integrated with Raman spectroscopy. This approach focuses on early detection and progression monitoring of pancreatic cancer. Utilizing tumor-targeted Ag nanoparticles and tapered multimode fibers enhances Raman signals, minimizes light loss, and reduces background noise. This advanced Raman system allows for detailed molecular spectroscopic examination of individual cells, offering more practical information and enabling earlier detection and accurate staging of pancreatic cancer compared to conventional multicellular Raman spectroscopy. Transcriptomic analysis using high-throughput gene screening and transcriptomic databases confirmed the ability and accuracy of this method to identify molecular changes in normal, early, and metastatic pancreatic cancer cells. Key findings revealed that cell adhesion, migration, and the extracellular matrix are closely related to single-cell Raman spectroscopy (SCRS) results, highlighting components such as collagen, phospholipids, and carotene. Therefore, the SCRS approach provides a comprehensive view of the molecular composition, biological function, and material changes in cells, offering a novel, accurate, reliable, rapid, and efficient method for diagnosing and monitoring pancreatic cancer.

Synchronous Match-Reassigning transform: A method for extracting time-varying features of planetary gearbox

Instantaneous frequency (IF) time-varying closely spaced and severe background noise can introduce fake components into the time-frequency representation (TFR) of most time-frequency analysis (TFA) methods, especially for the vibration signals of variable-speed planetary gearboxes. These fake components lead to a decrease in the readability of the TFR, making it difficult to extract the true IF. To address this issue, a new TFA method called Synchronous Match-Reassigning Transform (SMRT) is proposed. Firstly, a polynomial chirp rate with a single parameter adjustment is constructed to achieve precise matching of the IF. Secondly, a frequency reassignment operator is constructed for the fine refinement of the IF ridge of Synchronous Match-Reassigning Operator (SMRO). Finally, SMRO is combined with VKF to achieve adaptive reconstruction of the true IF and to remove fake components. The TFR of SMRT has high readability and low energy leakage. The superiority and effectiveness of this method have been verified through synthetic signals and actual signals.

Alaryngeal Speech Enhancement for Noisy Environments Using a Pareto Denoising Gated LSTM

Loss of the larynx significantly alters natural voice production, requiring alternative communication modalities and rehabilitation methods to restore speech intelligibility and improve the quality of life of affected individuals. This paper explores advances in alaryngeal speech enhancement to improve signal quality and reduce background noise, focusing on individuals who have undergone laryngectomy. In this study, speech samples were obtained from 23 Lithuanian males who had undergone laryngectomy with secondary implantation of the tracheoesophageal prosthesis (TEP). Pareto optimized gated LSTM was trained on tracheoesophageal speech data to recognize complex temporal connections and contextual information in speech signals. The system was able to distinguish between actual speech and various forms of noise and artifacts, resulting in a 25% drop in the mean signal-to-noise ratio (SNR) compared to other approaches. According to acoustic analysis, the system significantly decreased the number of unvoiced frames (PVF) from 40% to 10% while maintaining stable proportions of voiced frames (PVS) and average voicing evidence (AVE), indicating the accuracy of the approach in selectively attenuating noise and undesired speech artifacts while preserving important speech information.

The Emerging Future of Mobile Audiometry: A Prospective Validation Study of the Mimi Hearing Test Application.

The objective of this study is to assess the accuracy of the Mimi Hearing Test (MHT) mobile application in the detection of air conduction (AC) thresholds and in screening for moderate hearing loss. Prospective clinical study. Tertiary care center. Participants with or without a varying degree of hearing loss, aged 18 years and over, without cognitive impairment and without active otorrhea or earwax impaction at the time of the hearing assessment were included. Subjects with a ranging severity of hearing loss underwent a conventional in-booth audiogram as well as mobile-based screening with MHT in a quiet room (45.5 dB background noise) on the same day. Both regular over-the-ear and noise-canceling headphones were tested with MHT. Comparisons of AC thresholds between conventional audiometry and mobile-based audiometry at discrete frequencies and with pure-tone averages (PTA) were performed. A total of 75 adults (mean age: 56.2 yr, 54.7% male) were recruited and 63 used for analysis. Of the thresholds measured with MHT using regular headphones, 44.0% were within 10 dB of the conventional audiogram, compared to 39.3% using noise-canceling headphones. MHT demonstrated best accuracy at high frequencies (4-8 kHz). When screening for moderate hearing loss (PTA >40 dB HL), MHT demonstrated a sensitivity and specificity of 100.0% and 80.2%, respectively. MHT is reliable for identifying moderate hearing loss but lacks precision in detecting thresholds at low frequencies. Noise canceling headphones seem to improve its precision at 4,000 Hz only.

High-Performance Metabolic Profiling of High-Risk Thyroid Nodules by ZrMOF Hybrids.

Thyroid nodules (TNs) have emerged as the most prevalent endocrine disorder in China. Fine-needle aspiration (FNA) remains the standard diagnostic method for assessing TN malignancy, although a majority of FNA results indicate benign conditions. Balancing diagnostic accuracy while mitigating overdiagnosis in patients with benign nodules poses a significant clinical challenge. Precise, noninvasive, and high-throughput screening methods for high-risk TN diagnosis are highly desired but remain less explored. Developing such approaches can improve the accuracy of noninvasive methods like ultrasound imaging and reduce overdiagnosis of benign nodule patients caused by invasive procedures. Herein, we investigate the application of gold-doped zirconium-based metal-organic framework (ZrMOF/Au) nanostructures for metabolic profiling of thyroid diseases. This approach enables the efficient extraction of urine metabolite fingerprints with high throughput, low background noise, and reproducibility. Utilizing partial least-squares discriminant analysis and four machine learning models, including neural network (NN), random forest (RF), logistic regression (LR), and support vector machine (SVM), we achieved an enhanced diagnostic accuracy (98.6%) for discriminating thyroid cancer (TC) from low-risk TNs by using a diagnostic panel. Through the analysis of metabolic differences, potential pathway changes between benign nodule and malignancy are identified. This work explores the potential of rapid thyroid disease screening using the ZrMOF/Au-assisted LDI-MS platform, providing a potential method for noninvasive screening of thyroid malignant tumors. Integrating this approach with imaging technologies such as ultrasound can enhance the reliability of noninvasive diagnostic methods for malignant tumor screening, helping to prevent unnecessary invasive procedures and reducing the risk of overdiagnosis and overtreatment in patients with benign nodules.

Integration of concentration gradient generator with competitive PCR in a droplet for rapid nucleic acid quantification

Competitive PCR is an efficient way for the measurement of nucleic acids without requiring a standard curve. It uses a competitor template mimicking the target sequence for direct comparison and quantification during amplification. However, manually preparing various concentrations for competitive PCR is labor-intensive. Additionally, target and competitor DNA bands are often inadequately separated on gels due to their similar sizes. This leads to inaccurate distinction and imprecise measurement of bandwidths and intensities, resulting in high standard deviations in quantification. Thus, this study presents an alternative way to combine droplet competitive PCR with the concentration gradient generator in a microfluidic device that simplifies competitive PCR preparation and provides precise control over reaction conditions and sample handling. Generating a wide range of competitor-to-target ratios in a single experiment enhances statistical reliability and isolating individual reactions in droplets reduces background noise and increases sensitivity. Additionally, it eliminates gel electrophoresis, improves consistency and reproducibility, requires smaller sample and reagent volumes, and allows direct sample quantification through a calibration curve for fast, simple quantification. We envision that our platform can offer a promising alternative to digital PCR, addressing its challenges and driving progress in molecular biology and diagnostics.

Hypo-activation of the Central Auditory System in Listeners who are Hyper-tolerant of Background Noise.

Listeners exhibit varying levels of tolerance for background noise during speech communication. It has been proposed that low tolerance of background noise may be the consequence of abnormally amplified gain in the central auditory system (CAS). Here, using a dataset of young adults with normal hearing thresholds, we asked whether central gain mechanisms might also explain cases of hyper tolerance of background noise, as well as cases of reduced, but not abnormal, tolerance. We used the auditory brainstem response to derive a measure of CAS gain (Wave V/Wave I ratio) to compare listeners' background noise tolerance while listening to speech, grouping them into three categories: hyper, high, and medium tolerance. We found that hyper tolerant listeners had reduced CAS gain than those with high tolerance. This effect was driven by Wave V not Wave I. In addition, the medium tolerant listeners trended towards having reduced Wave I and reduced Wave V amplitudes and generally higher levels of exposure to loud sound, suggestive of the early stages of noise-compromised peripheral function without an apparent compensatory increase in central gain. Our results provide physiologic evidence that (1) reduced CAS gain may account for hyper tolerance of background noise but that (2) increased CAS gain is not a pre-requisite for medium tolerance of background noise.

Overlapping Shoeprint Detection by Edge Detection and Deep Learning

In the field of 2-D image processing and computer vision, accurately detecting and segmenting objects in scenarios where they overlap or are obscured remains a challenge. This difficulty is worse in the analysis of shoeprints used in forensic investigations because they are embedded in noisy environments such as the ground and can be indistinct. Traditional convolutional neural networks (CNNs), despite their success in various image analysis tasks, struggle with accurately delineating overlapping objects due to the complexity of segmenting intertwined textures and boundaries against a background of noise. This study introduces and employs the YOLO (You Only Look Once) model enhanced by edge detection and image segmentation techniques to improve the detection of overlapping shoeprints. By focusing on the critical boundary information between shoeprint textures and the ground, our method demonstrates improvements in sensitivity and precision, achieving confidence levels above 85% for minimally overlapped images and maintaining above 70% for extensively overlapped instances. Heatmaps of convolution layers were generated to show how the network converges towards successful detection using these enhancements. This research may provide a potential methodology for addressing the broader challenge of detecting multiple overlapping objects against noisy backgrounds.

The impact of receiver arrays on suppressing seismic speckle scattering noise caused by meter-scale near-surface heterogeneity

Managing seismic scattering noise in geophysical surveying, especially from near-surface heterogeneity, presents significant challenges. We revisit the role of receiver arrays in mitigating such noise in regions with near-surface meter-scale heterogeneity. Moving beyond traditional approaches that focus on suppressing coherent noise from near-surface arrivals and random ambient noise, our research highlights the substantial impact of speckle scattering noise. This noise, resulting from near-ballistic scattering on small-scale heterogeneities, introduces considerable trace-to-trace variability in phase and amplitude, complicating data processing. By integrating a novel model of random multiplicative noise with sophisticated statistical techniques, we have demonstrated the efficacy of array stacking in significantly reducing this type of noise and decreasing the dispersion of both phase and amplitudes. Our analytical and numerical analyses reveal a notable trend: the reduction in phase and amplitude spread amplifies with the array size. A key finding of our study is the identification of a [Formula: see text] law for phase spread reduction, analogous yet distinct from the well-known [Formula: see text] law observed in amplitude attenuation of additive ambient noise. In our context, this law implies that the standard deviation of residual phase disturbances diminishes in proportion to [Formula: see text], where N denotes the array size. This insight holds particular significance for smaller arrays, such as those with nine receivers commonly used in desert environments.

Study on Cavitation Noise Monitoring and Characteristics Based on Venturi Bench Test

Cavitation phenomena are accompanied by harsh cavitation noise. Studying cavitation noise is an effective method to monitor cavitation conditions. In order to study the characteristics of cavitation noise, a Venturi test bench experiment platform is built, the cavitation flow field and cavitation noise of Venturi test bench are simulated. The frequency domain analysis of cavitation noise is carried out, and the relationship between cavitation region, flow rate and sound pressure level of cavitation noise is verified by comparison between simulation and experiment. Because the cavitation noise is easily polluted by ambient noise, wavelet transform is used to analyze the cavitation noise and background noise, and the characteristics of cavitation noise are studied by comparing the difference between them.