Noise Level Research Articles

Combining Fusion-Based Thresholding and Non-Linear Diffusion for Improved Speckle Noise Mitigation in SAR Images

The primary concern of synthetic aperture radar (SAR) images is speckle noise, an inherent property. The creation of speckle noise is in a granular form and its nature is multiplicative. To reduce such noise from the radar images, the researchers’ primary motive is to suppress granular pattern while preserving the quality of the obtained images, thereby facilitating easier feature extraction and classification. Existing speckle-noise reduction methods often fail to preserve fine details such as edges and textures. This study proposes a fusion-based method that integrates non-linear transform-based thresholding with advanced noise reduction techniques. The proposed method is implemented on two simulated SAR images at noise variance levels of σ = from 5 to 40. The fundamental and most significant step is to analyze the effect of granular patterns in radar images before despeckling. Different performance metrics, classified into with-reference and without-reference indexes, are considered to investigate the effectiveness of the proposed despeckle method. The Signal-to-Noise Ratio (SNR) for SAR-1 at σ = 20 was observed at 16.22 dB, outperforming the next best result of 12.89 dB from the Log Compression filter. The Universal Image Quality Index (UIQI) reached 0.6987, indicating high visual quality retention across various noise levels. The proposed despeckling method demonstrated superior performance in comparison to different filters, achieving a Peak Signal-to-Noise Ratio (PSNR) improvement of up to 29.37 dB on SAR-2 at a noise variance of σ = 5, significantly higher than the best filter method’s 26.70 dB. Additionally, the method achieved a Structural Similarity Index Measure (SSIM) of 0.6538, indicating superior image quality preservation.

Three-dimensional spatiotemporal wind field reconstruction based on LiDAR and multi-scale PINN

In this numerical study, we use a multi-scale version of physics-informed neural network (PINN) for wind field reconstruction from LiDAR measurements. The reference velocity field is obtained from high-fidelity large-eddy simulation of neutral atmospheric boundary layer, and the LiDAR measurement strategy is restricted to that of a real LiDAR. The multi-scale PINN reconstructs the velocity field by minimizing a combination of the L2-error with respect to the LiDAR measurements and residuals of the governing equations. Our most significant finding is that adding a multi-scale layer to PINN enables us to: (i) capture wider range of scales, (ii) reconstruct the flow field outside the LiDAR scanning area, and (iii) reach faster convergence. We also find that for volumetric flow reconstruction and to deal with uncertainty in the wind direction, the reconstruction accuracy can be greatly improved by employing multiple LiDAR devices. Overall, our results show that the normalized errors in the reconstructed wind field are lower than 5% for all the experiments conducted in this study and that the errors do not increase even in the presence of measurement noise levels of typical LiDAR. These findings show the feasibility of three-dimensional dynamic wind field reconstruction across large wind farms using LiDAR devices.

Directional wind turbine noise prediction plots and prevalence histograms for community consultation

In Australia, wind turbine noise is predicted using international standards and guidelines with a set of conservative assumptions. For example, wind turbine noise predictions using the ISO 9613-2 method are based on a scenario in which each receiver is simultaneously downwind of every wind turbine. As such, winds that are outside of the downwind direction range will result in lower wind turbine noise levels than predicted using ISO 9613-2. These predictions are also based on the assumption that each turbine is simultaneously generating their maximum noise emissions, whereas variations in winds speeds across the site will frequently result in individual turbines producing lower noise levels than assumed in the modelling. The net effect of these conservative assessment choices is that actual wind turbine noise levels would be lower than presented in noise assessments in many cases. Providing an indication of how frequently predicted noise levels would likely occur can assist community consultation and provide useful context to noise modelling data. This paper presents analysis utilising directional noise modelling to assess the effect of wind direction, combined with an analysis of historic wind records, to determine the range of predicted noise levels and how frequently they may occur.

Noise modeling of UAM around the urban vertiport

The present study aims to investigate the noise distribution around urban vertiport caused by UAM(Multicopter) and helicopter. Noise modelings were carried out using SoundPLAN software at the some vertiports in Seoul, Korea. Sound source model of UAM and helicopter were used as a form of hemisphere. Noise predictions were undertaken with three different operations including depart, level flight and landing. In order to evaluate the noise impact on the buildings around the vertiport, noise levels at the outer wall of nearby buildings were calculated as the three noise units including Leq, Lmax and Lden. Also, noise maps were drawn around the vertiport. As a result, it was found that average noise level of UAM is approximately 12 dB lower than the helicopter noise levels. Regarding the noise frequency distribution, most high noises are made at the mid-frequencies during landing hours while low frequency noise level around 63 Hz was dominant at take-off time.

The challenges of mapping quiet urban areas from mobile sound surveys

Detailed spatial data on noise levels are needed to identify quiet areas. Yet noise maps derived from sound propagation models based on traffic flows or sensor networks are often incomplete. Surveys using mobile sound recording coupled with machine learning modelling have offered a possible solution, but so far have focused on averaged noise levels. We argue that quiet areas should ideally be consistently quiet, rather than simply quiet on average, yet mobile survey data usually lack the full temporal profile needed to quantify consistency in noise levels. Using data from our Southampton study area, we show that modification of the loss function used in machine learning modelling of mobile survey data can yield information on the likely range of noise levels at any location across an entire city. We use this approach not only to identify locations that are consistently quiet, but also to help understand which urban features may be associated with quiet, average and noisy events at any given location.

An innovative approach for enclosure design of power generators to meet noise regulation targets

The use of diesel-powered engine generators as a power source is very common for various industrial and residential applications. There are strict regulatory requirements and legislations to limit the noise levels from these generators below statutory limits. The purpose of the paper is to present an approach using statistical energy analysis (SEA) augmented by experimental inputs for the prediction of noise levels for the generators and propose strategies for optimized enclosure design that effectively mitigate noise to achieve regulatory requirements. The study begins by developing an SEA model that represents the acoustic behavior of the generator and enclosure. The airborne sources such as engine, alternator, radiator fan and exhaust are modelled explicitly using experimental noise source characterization. Based on the established SEA model and excitation sources, noise levels are predicted through the calculation of energy flow between subsystems. The predicted sound levels for an existing Diesel Generator with enclosure were validated with its test data to ensure correctness of SEA model. Parametric studies were carried out using simulations on key variables, including critical noise paths, panel thickness, and noise control treatments. These investigations helped identify optimal process parameters that reduce noise levels emitted by genset in adherence to noise regulations.

Comparing acoustic models with measured noise levels in a Polypropylene production industrial complex

This paper presents a detailed comparison between the final noise source data, as documented in the Project Report, produced noise map during design phase, and the field-measured noise values, along with the empirically generated noise map during the plant's operational phase. The study investigates into the accuracy and reliability of the assessed noise map, evaluating its alignment with actual noise levels recorded on-site, identifies discrepancies between both the noise maps, pinpointing areas for improvement in predictive modelling. The goal is to see how well the predicted noise levels match up with the real-world situation, helping improve noise control strategies, specifically focus on noisy equipment, checking if the expected or calculated noise levels are the same with field measured values. By shedding light on these disparities, this study contributes to refining noise prediction models and improving the effectiveness of noise control measures in industrial settings.

Assessment of sleep effects at a hospital near Tan Son Nhat Airport, Vietnam

This paper presents an analysis of sleep patterns and environmental noise levels recorded from 21 participants wearing smartwatches and 5 participants using ECG devices in patient rooms (A3) and outdoor areas on the 4th floor of an inpatient ward. Sleep data revealed variations in sleep stages among participants, with an average distribution of 60% wake, 10% REM, 22% light, and 8% deep sleep. Environmental noise levels were measured at different times of day, showing higher levels during the day and lower levels at night, with an average LAeq of 53.4 dB for 24 hours. Comparisons between indoor and outdoor areas and different times of day indicate fluctuations in noise levels, with outdoor areas generally exhibiting higher noise levels. These findings contribute to understanding sleep patterns and noise exposure in healthcare settings, highlighting the need for further research to explore the impact of environmental factors on sleep quality and patient well-being.

Assessment of environmental noise capacity for Indian Highways

India is one of the rising nations with a diverse traffic mix. Heterogeneity of traffic is a key factor in determining the noise environment around roadways. This study aims to assess the environmental noise capacity of Indian highways. To gather data for the study, Indian highways, namely NH-334, NH-7, and NH-344, were selected, specifically focusing on the sections, settlements near the highway. Four specific locations along these highways were chosen to measure the noise levels and collect comprehensive traffic data. The vehicles were classified into two categories: light vehicles and heavy vehicles. Traffic volume was assessed using videography, while traffic speed was determined using a radar gun. Sampling occurred at 15-minute intervals, encompassing both peak and off-peak hours on weekdays and weekends. A total of 460 data sets were collected to facilitate the prediction of equivalent noise levels (Leq). Environmental noise capacity (ENC) was calculated at all selected locations, revealing that the ENC value exceeded zero. This indicates that the noise levels in all areas surpassed the designated capacity. This study provides valuable insights for policymakers in developing strategies to mitigate the impacts of increasing highway noise.

Comparison of noise exposure cost and annoyance-related indicators in microscopic traffic simulations

Road traffic noise is one of the major sources of environmental noise and has been shown to increase risk of adverse health effects. For this reason, noise mapping is an efficient tool to assess and monitor city-wide noise levels in accordance with the Environmental Noise Directive (END). To relate these noise levels to the associated health effects, the noise map may be further analysed using exposure-response models, or with cost models that calculate the noise-related externalities of the traffic. With the use of microscopic traffic simulations, this assessment may be performed at a vehicle-specific level. A recently introduced methodology, the noise exposure cost, calculates the vehicle-specific contribution to the long-term social cost estimated at a macro-level based on the vehicle-specific noise contributions. However, the noise exposure cost methodology may not reflect the relative noise impact of individual vehicles, but rather solely reflect the noise contribution regardless of its relative impact to the noise levels at the time. The aim of this study is to investigate the possibility to use the linear sensitivity indicator as a basis for a non-linear weighting function in the noise exposure cost methodology, to allow the vehicle-specific noise exposure cost to better reflect the relative impact.

Assessing indoor and outdoor noise quality and associated health impacts at selected schools in Surat, India

An optimal ambient environment is crucial for healthy development, yet the excess of vehicles and inadequately planned educational infrastructures compromise cognitive growth in children. This study evaluates the impact of ambient noise on student cognition in five schools situated along city arterial and sub-arterial roads. A total of 717 students from grades 7, 8, 9, and 11 participated. Noise levels were measured in prevailing noisy conditions (PC) and controlled silence conditions (SC) within classrooms using the Kimo dB300 sound level meter. The observed differences in noise levels between PC and SC varied across grades, showing reductions of 4.7 ± 3.5 dB, 6.1 ± 0.7 dB, 6.7 ± 1.3 dB, and 4.4 ± 3.46 dB for grades 7, 8, 9, and 11, respectively. Statistical analyses revealed significant differences in the average noise levels under both conditions. Furthermore, cognitive task performance in PC and SC was significantly different, as evidenced by paired t-tests in tasks such as multiplication, word formation, reasoning, and sentence construction. Dimension reduction techniques identified room acoustics, task difficulty, speech intelligibility, mental deficiency, and annoyance as critical factors affecting learning abilities. Teachers reported that major impacts of noise include annoyance, sleeplessness, headache, and hearing impairment.

WIND power noise systematically underestimated in Sweden

This paper outlines a numerical study of measurement faults in regard to wind power turbines in Sweden. For this purpose, seven (7) reports of noise level from four (4) wind power stations, with between seven (7) and 47 on shore turbines, and between 145 m and 230 m high, were examined. Parallel studies were performed with analytic methods. Technically the noise level was undervalued by more than five (5) dB(A). The effect of the wind speed at 10 m height, according to the IEC64100-11 regulations, was generally not taken into account. In some cases, only the wind speed at the turbine hub was regarded. Thereby the correct wind speed at 10 m height was overstated by up to five (5) meters per second. In one case the measurement of wind power noise was measured at wind speed between three (3) and four (4) meters without the wind turbine blades moving at all. In summary the wind power noise levels were suppressed by about 5 dB(A) for the wind power stations analyzed in Sweden. The study results in a differentiated model as compared to the required rule in IEC64100-11. The projects were carried out between the years 2012 and 2024.

Consideration and case study using a time-difference-of-arrival directional device for occupational noise measurement

To protect worker's hearing in noisy workplaces, noise levels are measured periodically, and noise sources are located based on the results of recordings or video cameras. If the noise level is above a certain level, noise abatement measures are taken, or workers are suggested to wear hearing protection. Measuring the noise level can be done simply by placing a sound level meter on the floor, but finding the noise abatement is a time-consuming task. It is necessary to listen to the recordings one by one or review the video to find the noise abatement. We believe that a simple method of estimating noise abatement is very useful, since some noisy workplaces do not allow recordings or video cameras for privacy and confidentiality reasons. In this paper, noise source identification using a time-difference-of-arrival directional device in an indoor environment is examined. The results are analyzed in the context of room properties such as reverberation time, dimensions, and device localization. The paper also reports on practical use-cases in actual sites.

Relation between measured noise levels and traffic flow

Road-traffic flow parameters are a critical input to urban noise pollution evaluation frameworks such as CNOSSOS-EU. The accuracy and resolution of the traffic flow improves the quality of the noise exposure assessment. Highly resolved traffic flow within an urban network is difficult to reliably measure or predict. The quality and availability of such traffic information may be improved using data from low-cost noise sensors that are mounted beside representative segments of the road network. A model is presented, which relates the noise levels measured at a single noise sensor with the local traffic flow conditions. The noise data is obtained from a noise sensor mounted alongside a road, which is part of a test-bed in Stockholm, Sweden. The local traffic flow is obtained from commercial vehicle-counting sensors mounted alongside the noise sensor. Effect of seasonality is observed when comparing models trained on different subsets of the training data. The effect of seasonality on the noise levels is investigated.

Case-study analysis of traffic noise at Vesterbrogade, Aarhus, Denmark

This paper analyses the livability, concerning traffic noise, in apartment buildings along one of the most heavily trafficked streets in Aarhus, Denmark. The case-study site is analyzed with noise prediction models and different improvements on the sound environment are proposed through qualitative aspects. The analyses are conducted using two different noise prediction models, opeNoise in QGIS and SoundPLAN. OpeNoise uses the noise prediction method CNOSSOS and SoundPLAN uses Nord2000. Noise maps 1,5 m above the terrain and facade noise levels are calculated. The results show noise levels on the facade far above WHO's limit, of . The noise pollution in the open space next to the roads also shows noise levels far above the recommendations, while the inner courtyard shows acceptable noise levels. Several subjective improvements of the sound environment are proposed, such as vegetation between the road and the building. Furthermore, different designs were proposed to reduce the amount of noise-polluted facades. This research work emphasizes the importance of considering qualitative parameters simultaneously with the noise prediction models.

Railway-induced vibration combined with railway noise - a systematic review with exposure-effect curves

The combined health impact of concurrent railway noise and railway vibration exposure is not yet well understood. This systematic review aimed to investigate the combined effects of vibration and concurrent noise. We converted the vibration metric to an equivalent noise level and calculated an overall noise level by energetically summing the equivalent and railway noise level. The combined health effect was determined by using published evidence-based exposure-effect formulas. Studies included in this systematic review predominately investigated annoyance and self-reported sleep disturbances; no studies on manifest diseases were identified. For the combined effects of vibration and noise on "total" annoyance, the results based on the pooled analysis of CargoVibes project are recommended as conservative approach. Our results based on epidemiological studies are corroborated by findings of laboratory studies. Converting railway vibration into equivalent noise levels in dB may offer a pragmatic approach to assess the combined health effects of railway noise and railway vibration exposure. Future studies should include cardiovascular and mental diseases in addition to vibration-induced annoyance and sleep disturbances. Furthermore, future studies should include in-depth investigations of the interaction between railway noise and railway vibration to allow for a more accurate assessment of the railway-induced burden of disease.

Laboratory measurement of the effect of exposure to ship noise on mussels

The mussel Mytilus galloprovincialis is a bivalve mollusc of high commercial interest, which frequently breeds in coastal areas with high levels of ship traffic noise. Studies on the effect of this stressor on mussels are scarce, which is why we set out to design a system to study the effect of ship noise on mussel behaviour (valve opening-closure rhythms). The proposed experimental set-up uses a high frequency non-invasive valvometry system to detect shell closure reactions related to instantaneous increases in sound level. The main findings are that mussels reacted to ship noise levels above 114 dB re 1μPa (63Hz-4kHz), that most reactions occurred within 13 s after a sudden increase in level, and that there does not appear to be a clear relationship between closure depth and noise level. Although mussels may not be sensitive to sound pressure but only to the associated particle movement, the results of this work contribute to highlighting the sensitivity of this species to noise, and the need to carry out experiments with a larger number of specimens and in conditions that allow the acoustic field to be reproduced more realistically.

Analysis of in-situ acoustical performance of a removable urban pavement with a porous top layer

A demonstrator of a new removable urban pavement with functionalized surface was implemented in the inner city of Nantes within the I-STREET CUD-SF project. Designed for easy maintenance operation, it is made of hexagonal cement concrete slabs with a dense body and a 4 cm thick porous top layer of grading 0/6 and porosity 25% for drainability. The noise performance of the pavement was assessed at urban speeds by simultaneous Coast-By and Close-Proximity noise measurements performed with a dedicated test vehicle after closure of the road to traffic. The results are compared with noise levels obtained with three reference surfaces, a DAC 0/10 and two VTAC of grading 0/4 and 0/6. The tested pavement gets ranked differently depending on the noise measurement method considered. The results are analyzed in the light of 3D texture measurements as well as sound absorption measurements performed in situ by the extended surface method and with Kundt's tube on core samples. The influence of texture irregularities at the junction between slabs and sand used for slabs stabilization is addressed. Finally, the Coast-By noise levels are compared with those obtained with the HyRoNE prediction model from 3D texture and sound absorption. The discrepancies observed are discussed.

Characterization of maritime traffic noise in two areas of the Mediterranean

One of the objectives of the European JPI Oceans DeuteroNoise project is to investigate the soundscapes within different sea basins. Measurement campaigns, including the recording of raw noise data (wave files), have been carried out in the Venice Lagoon, in the North Adriatic and on Barcelona shore. In this work we will present the first results. The data acquired were processed to obtain the characteristic spectrum and noise levels; subsequently the velocity of the particles will be acquired and analysed. The analysis of the recorded data involves the design of a taxonomy of anthropogenic noise sources, e.g. large ships, small boats or any other existing noise source. The recorded data were labelled with these sources, describing their main audio characteristics (spectral distribution, temporal evolution, etc.) for their characterization and future blind identification. Throughout the measurement period, ship and route data were acquired using AIS (Automatic Identification System) and Vessel Monitoring System (VMS) in the measurement sites. The preliminary analysis and labelling, together with ship and route data, will allow the reproduction of acoustic environments of anthropogenic origin in laboratories and the creation of acoustic maps of the basins investigated using commercial software.

Identification of strategic location for environmental noise control through the application of land use regression (lur) in a neural network platform

The significant causes of rising noise pollution within urban areas lie in extensive transportation networks, industrial operations, and commercial activities. Addressing this complexity, our study employs Land Use Regression (LUR) modelling to assess the intricate relationship between land-use features and environmental noise in urban landscape. The objective of this study is to provide a framework for predicting environmental noise levels in Delhi, India. For which, Lday, Lnight, LAeq, 24h, and Ldn noise descriptors were modelled at daily resolution data from 31 fixed-site monitors. The prediction at first stage for LUR was found to be R2 = 0.53 which was validated using the n-1 method. The model was later optimized using a NN. Output from the NN is included in the GIS environment to identify the hotspot of the noise. Previously identified engineering interventions applicable to urban contexts that were listed from the literature review were allocated as per hotspots because of the modelled output. The study also explored the avenue of using Delhi-specific transport variables developed from Google travel time data for prediction improvement of the noise level. The research contributes to advancement of noise pollution assessment and management methodologies, particularly in situations with no available validated traffic noise models.