Reduce Noise Levels Research Articles

Improvements to gearbox acoustics via thrust collars

Thrust collars relieve the gearbox housing of the axial force and tilting moments generated by helical gears. The different transfer path also reduces the vibration excitation of the housing due to meshing, which could lead to improved acoustics. This paper presents measurements of noise level reduction of an experimental gearbox. A gearbox dynamics simulation model is used to investigate the effects resulting from the inclusion of thrust collars.

An Improved Next Generation Gravity Mission

There is an opportunity to make a major reduction in the acceleration noise level for the first Next Generation Gravity Mission by replacing the accelerometers used on the GRACE Follow-On Mission by a highly simplified version of the Gravitational Reference Sensors flown very successfully on the LISA Pathfinder mission of ESA. The reduced measurement noise level can make possible much-improved measurements of the short-period and short-wavelength variations in the geopotential. This would be particularly from the along-track analysis of the results, which can permit repeat measurements about half a day apart along ground tracks within 200 km of each other over a substantial part of the globe. Such a mission would permit considerably improved testing of geophysical models for the geopotential variations due to changes in the Earth’s mass distribution.

Joint inversion of gravity and gravity gradient data: A systematic evaluation

Gravity and gravity gradiometry measurements are commonly used to map density variations in the subsurface. Gravity measurements can characterize gravitational anomalies at long and short wavelengths effectively, but the cost of collecting a sufficiently spatially dense survey to characterize the short wavelengths can be prohibitive. Gravity gradient data can be quickly collected with short-wavelength information at a low noise level, but they have decreasing sensitivity to longer wavelengths. We have described a method to jointly invert gravity and gravity gradient data that takes advantage of the differing frequency contents and noise levels of the two methods to create an improved image of the subsurface. Previous work treated the inversion as a multiple component gravity inversion; however, this can cause unintended errors in the recovered models because each data set is not guaranteed to be fit within its noise level. Our joint inversion methodology ensures that the gravity and gravity gradient data sets are fit within their individual noise levels by incorporating a relative weighting parameter, and we describe how to find that parameter. This method can also be used to create an improved broadband gravity anomaly map that has a reduced noise level at long wavelengths using a joint equivalent source reconstruction. We first build a synthetic model using a Minecraft world editor that has different wavelength anomalies, and find the improvement with joint inversion. These results are also confirmed using a real-world example at the R. J. Smith test range in Kauring, Australia.

Efforts to improve sleep quality in a medical intensive care unit: effect of a protocol of non-pharmacological interventions.

This study aimed to evaluate the effect of a protocol of nonpharmacological interventions to improve sleep quality in the intensive care unit (ICU). Due to its close relationship with sleep quality, the effects of the same interventions on noise levels and delirium rates were also evaluated in this study. This pretest-posttest design with a control group was carried out in a medical ICU over 8months. Data were collected using Acute Physiology and Chronic Health Evaluation II, the Glasgow Coma Scale, the Richmond Agitation-Sedation Scale, the Richards-Campbell Sleep Questionnaire (RCSQ), the Confusion Assessment Method for the Intensive Care Unit, and noise measurement devices. In the first phase of the study, patients receiving standard care in the ICU were followed. After the first stage, a training session was held for nurses to raise awareness and information. Then, the sleep-promoting protocol created by the researchers was applied. The ambient noise level was measured continuously. A total of 78 patients with a mean age of 70.0 ± 13.2years were followed in the ICU for an average of7.3 ± 3.8days. With protocol implementation, the ambient noise level in the ICU was reduced from 70.9 ± 3.8dB(A) to 62.7 ± 3.5dB(A) (p < 0.01); the RCSQ scores of the patients increased from 48.3 ± 1.4 to 62.1 ± 1.8 (p < 0.01). Although statistically nonsignificant, efforts to improve sleep quality also reduced the development of delirium by 15%. It is possible to improve sleep quality and reduce noise levels in anICU with a protocol consisting of multicomponent nonpharmacological interventions.

Performance and quality assurance of medical image using hybrid thresholding wavelet transform with Wiener filter

ABSTRACT Medical images like X-ray, computed tomography, ultrasound, and magnetic resonance imaging (MRI) are produced using different techniques; during this process, noise is added that decreases the image quality and image analysis. Image denoising is an important task in image processing; use of wavelet transform improves the quality of an image and reduces noise level. We propose in this research, a denoising approach basing on discrete wavelet transform (DWT) using Hybrid Thresholding (bayesShrink) with Wiener filter technique for enhancing the quality image. This technique improved a better balance between smoothness and accuracy than the traditional wavelet DWT and are less redundant than stationary wavelet transform (SWT). In addition, the Structural Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) were used to analyse the denoised images quality.

Применение метода перенормировки с ограничением к акустическим изображениям

The paper proposes the use of the method of renormalization with limitation (MRL) for suppressing the speckle noise in acoustic images. The method is tested on various types of acoustic images. The principal possibility of a significant reduction in the speckle noise level is found due to the fact that the MRL renormalizes the spectrum of the sonar image to the universal reference spectrum (URS) model, which is a model of the spectrum of a «good» quality optical image. To increase the overall sharpness, after applying MRL, it is recommended to use post-processing suitable for each specific type of image. It is proposed to estimate the degree of suppression of speckle noise using the standard deviation from the image averaged over the sprite. The study allows us to conclude that the application of MRL to various acoustic images can significantly reduce the speckle noise

GMA phased array for active echo control of underwater target

Aiming at the special requirements of low-frequency echo control of underwater targets in high pressure environment, a low-frequency miniaturized active control unit with thickness less than 50 mm was designed based on Terfenol-D, a giant magnetostrictive material. Based on that, a kind of light and thin underwater large plate smart acoustic structure was constructed. It was used for low-frequency active echo control of underwater targets. The active control unit was constructed into a flat smart acoustic structure using a 4 × 4 array distributed design. The active control system based on multi-channel adaptive filter was used to test the echo control performance of the flat active acoustic structure, which can achieve significant noise reduction level in less than one second. And the sound absorption coefficient of 0.8 or more can be achieved at a high pressure of 1 MPa. When the sound wave was incident on the surface of the underwater target obliquely from −10° to +10°, the phased array method was used to make the pointing angle of the GMA array consistent with the incident angle, which could control the surface echo of the active structure very well, and the sound absorption coefficient is close to 0.9. The giant magnetostrictive smart structure combined with the active control system is a new type of low-frequency underwater noise reduction technology.

Technical note: High-accuracy weighing micro-lysimeter system for long-term measurements of non-rainfall water inputs to grasslands

Abstract. Non-rainfall water (NRW), defined here as dew, hoar frost, fog, rime, and water vapour adsorption, might be a relevant water source for ecosystems, especially during summer drought periods. These water inputs are often not considered in ecohydrological studies, because water amounts of NRW events are rather small and therefore difficult to measure. Here we present a novel micro-lysimeter (ML) system and its application which allows us to quantify very small water inputs from NRW during rain-free periods with an unprecedented high accuracy of ±0.25 g, which corresponds to ±0.005 mm water input. This is possible with an improved ML design paired with individual ML calibrations in combination with high-frequency measurements at 3.3 Hz and an efficient low-pass filtering to reduce noise level. With a set of ancillary sensors, the ML system furthermore allows differentiation between different types of NRW inputs, i.e. dew, hoar frost, fog, rime, and the combinations among these, but also additional events when condensation on leaves is less probable, such as water vapour adsorption events. In addition, our ML system design allows one to minimize deviations from natural conditions in terms of canopy and soil temperatures, plant growth, and soil moisture. This is found to be a crucial aspect for obtaining realistic NRW measurements in short-statured grasslands. Soil temperatures were higher in the ML compared to the control, and thus further studies should focus on improving the thermal soil regime of ML. Our ML system has proven to be useful for high-accuracy, long-term measurements of NRW on short-statured vegetation-like grasslands. Measurements with the ML system at a field site in Switzerland showed that NRW input occurred frequently, with 127 events over 12 months with a total NRW input of 15.9 mm. Drainage-water flow of the ML was not measured, and therefore the NRW inputs might be conservative estimates. High average monthly NRW inputs were measured during summer months, suggesting a high ecohydrological relevance of NRW inputs for temperate grasslands.

ASSESSING THE IMPACTS OF ROAD NOISE IN RELATION TO RESIDENTIAL AREAS AND ECONOMIC COSTS THROUGH MODELLING

This paper focuses on noise modelling and the assessment of road noise impacts in relation to residential areas and economic costs using modelling. The intention of the whole project and the authors' work is to contribute to the determination of changes in road noise levels for relevant decision-making processes with direct applicability in social sciences (regional development, sociology, demography, economics) related to health risk assessment (public health). The longevity, noise reduction levels and external cost changes of using low noise roads should therefore be appreciated. The purpose is to remove the identified disparity and to make publicly available, through a certified methodology, the data needed to assess the long-term effects of noise pollution from low-noise roads for use by regional development, thus contributing to the strategy of Directive 2002/49/EC.

A Hybrid SFANC-FxNLMS Algorithm for Active Noise Control Based on Deep Learning

The selective fixed-filter active noise control (SFANC) method selecting the best pre-trained control filters for various types of noise can achieve a fast response time. However, it may lead to large steady-state errors due to inaccurate filter selection and the lack of adaptability. In comparison, the filtered-X normalized least-mean-square (FxNLMS) algorithm can obtain lower steady-state errors through adaptive optimization. Nonetheless, its slow convergence has a detrimental effect on dynamic noise attenuation. Therefore, this paper proposes a hybrid SFANC-FxNLMS approach to overcome the adaptive algorithm's slow convergence and provide a better noise reduction level than the SFANC method. A lightweight one-dimensional convolutional neural network (1D CNN) is designed to automatically select the most suitable pre-trained control filter for each frame of the primary noise. Meanwhile, the FxNLMS algorithm continues to update the coefficients of the chosen pre-trained control filter at the sampling rate. Owing to the effective combination of the two algorithms, experimental results show that the hybrid SFANC-FxNLMS algorithm can achieve a rapid response time, a low noise reduction error, and a high degree of robustness.

The Urban Transport Strategy on the Example of the City Bike System in the City of Lublin in Relation to the Covid-19 Pandemic

Abstract The city bike system is now an increasingly popular form of communication. In practice, it has become a complement to the public transport system in large cities, and above all in the most crowded city centers. Importantly, the solution, which is a city bike, can contribute to the reduction of urban congestion, air pollution and to the reduction of noise levels. The paper discusses the issue of city bike system functioning in terms of meeting the transport needs in the area of the city of Lublin. The aim of the work is to describe the city bike system and to indicate the conditions for choosing this means of transport among the inhabitants of the Lublin region. A survey conducted among respondents in 2020 was used. The paper presents own research results and expectations of potential users of this system in the context of displacements, as well as the impact of the Covid-19 pandemic on the system functioning in 2020, and the strategy for operating this industry.

An Overview of Composite Standard Elastic‐Net Distribution Based on Complex Wavelet Coefficients

Statistical tools have changed significantly in the past decade; when the maximum likelihood method is usually applied, it provides an inaccurate solution due to its unsuitable properties and causes problems in fit. However, the current Ordinary Least Square (OLS) Model is more reliable in specific situations where the estimation is based on the slope only. On the other hand, some methods depend on the slope, and the intercept is recommended. These methods can be described as thresholding rules. Another often preferred method is the posterior mean (PM) technique. This procedure depends on two parts, the first part is the likelihood, and the other is the prior distribution, where the second part plays a significant role in the estimation. In this article, the standard elastic‐net distribution is assumed as the prior part, which consists of two parts, the first being the normal distribution and the second being the double exponential distribution. The reason why this model is used is that wavelet tools have different levels of resolution. Thus, this model may provide a more accurate estimation for the wavelet coefficients, which might be estimated using a normal or double exponential distribution. In the past, some properties of elastic‐net penalized were introduced and discussed. However, more properties are introduced for this distribution. In addition, two models based on the elastic‐net method are demonstrated, involving the point mass prior. The first model combines normal as likelihood, and elastic‐net distributions as prior, while the other combines the double exponential distribution as likelihood with the elastic‐net distribution as prior. Moreover, the level‐dependent components are estimated at each resolutions. A simulated investigation is studied using the Markov Chain Monte Carlo (MCMC) tool to estimate the underlying features, where real data are involved and modelled using the proposed methods. A stationary wavelet basis is also applied. As a result, the proposed procedure reduces noise levels which may be helpful since noise levels often corrupt real data, usually a significant cause of most numerical estimation problems.

A Hybrid LSTM-ResNet Deep Neural Network for Noise Reduction and Classification of V-Band Receiver Signals

Noise reduction is one of the most important process used for signal processing in communication systems. The signal-to-noise ratio (SNR) is a key parameter to consider for minimizing the bit error rate (BER). The inherent noise found in millimeter-wave systems is mainly a combination of white noise and phase noise. Increasing the SNR in wireless data transfer systems can lead to reliability and performance improvements. To address this issue, we propose to use a recurrent neural network (RNN) with a long short-term memory (LSTM) autoencoder architecture to achieve signal noise reduction. This design is based on a composite LSTM autoencoder with a single encoder layer and two decoder layers. A V-band receiver test bench is designed and fabricated to provide a high-speed wireless communication system. Constellation diagrams display the output signals measured for various random sequences of PSK and QAM modulated signals. The LSTM autoencoder is trained in real time using various noisy signals. The trained system is then used to reduce noise levels in the tested signals. The SNR of the designed receiver is of the order of 11.8dB, and it increases to 13.66dB using the three-level LSTM autoencoder. Consequently, the proposed algorithm reduces the bit error rate from 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−8</sup> to 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−11</sup> . The performance of the proposed algorithm is comparable to other noise reduction strategies. Augmented denoised signals are fed into a ResNet-152 deep convolutional network to perform the final classification. The demodulation types are classified with an accuracy of 99.93%. This is confirmed by experimental measurements.

Analysis of design, noise and vibration of shredding machinery of Lechuguilla Ixtle

The purpose of this study is to analyze the main components of a typical Lechuguilla Ixtle shredder machine, present in most of theejidos dedicated to this activity in the northeast of Mexico, and to determine the opportunities for redesign its main parts, also thesound and vibration levels for evaluate their magnitude and determine the severity and impact. To achieve this objective, the DFXmethodology was applied to Lechuguilla Ixtle shredder machine knowing the main parts that are susceptible to redesign, this typicalmachine was also compared against a bench test, carried out in a workshop with a lower power motor, with which were made testsfor noise and vibration, in both cases the analyzes are perform out with the same intention of achieving an improvement in itsefficiency. The results of the DFX methodology, as opportunities for redesign are: the safety of operation, the input and outputmechanisms, speed working when defibrating two Cogollos, lightening the structure, motor capacity depending on the design of thedefibration roller, and the form of maintenance and inspection. Finally, in the analysis of noise and vibrations, there areopportunities for improvement in the design of the machinery drum, placing a guard (cover) that helps to reduce noise levels, andreviewing the alignment of the axes the machinery so as not generate vibration outside the allowable ranges

Reduction of Noise Pollution with the Help of Roadside Collections in Coimbatore and Surroundings

Noise is the excessive and unwarranted sound that creates discomposure to human beings and abruptly disrupts the quality of the environment. The noise is magnified by the intensity of the sound produced at a particular place and is measured in decibels (dB). The noise pollution is mainly caused by the transportation of road, rail, airways and industrial activities. Increased growth and development of the cities marks the predominant source for the road travel of the people. The road traffic in main cities becomes part and parcel of life because everyone contributes to the self and development of society as a growing concern for the community. Green energy usually absorbs and disintegrates the excess noise and air pollutants that divine has given us through green belts. Therefore, the green belts helps in the natural source of noise and air pollutant reduction. The potentialities of the greenbelts are laid along the road-sides have been assessed in Coimbatore, Tamil Nadu at various selected places. Reduction of noise level was achieved up to 14 dB under the green belt area while compared to the open area. An area with a higher crown density demonstrated a lower noise level than the area with a lower crown density.

HUBUNGAN TINGKAT KEBISINGAN LALULINTAS TERHADAP V/C RASIO DI SMA NEGERI 70 JAKARTA SAAT PANDEMI COVID-19

Schools are educational facilities that must provide a sense of comfort and calm in learning activities. Noise can interfere with comfort and tranquility in learning activities. The source of school noise comes from traffic and other loud noises. Therefore, this study aims to determine the effect of traffic noise during the COVID-19 pandemic on the school environment of SMA Negeri 70 Jakarta and efforts to reduce noise levels in the school environment. Noise measurements were carried out for 14 days and carried out in the L1-L5 time segment which was carried out for 10 minutes with data reading every 5 seconds using a Sound Level Meter (SLM). The method used in determining the value of the traffic noise level is to measure the time and number of vehicles that pass through the measurement point along Jalan Raya Bulungan. From the results of the research at SMA Negeri 70 Jakarta, the noise level produced during the 14 days of the COVID-19 pandemic at SMA Negeri 70 Jakarta at points 1,2,3,5,7,8,9, and A exceeded the noise level quality standard. KepMenLH No. 48 of 1996 each has a value of 58.12 dBA; 56.18 dBA; 56.77 dBA; 56.55 dBA; 56.17 dBA; 60.10 dBA; 61.23 dBA; and 67.75 dBA. The V/C ratio at SMA Negeri 70 Jakarta shows the highest level of road service is on the 1st Sunday on Saturday, while the level of road service enters the class A category. At point A has the highest noise value of 67.75 dBA because it is located close to with a noise source, namely Jalan Raya Bulungan, while point 7 which is located far from the noise source has a noise level of 56.17 dBA.

Occupational pathology in the Chukotka and Nenets Autonomous Okrugs: risks, structure, prevalence

Introduction. Labor activity in the Arctic creates an increased risk of developing occupational diseases. In the Chukotka Autonomous Okrug (CHAO), the basis of the economy is the extraction of coal, placer and ore gold, and other non-ferrous metals, and in the Nenets Autonomous Okrug (NAO) - the extraction of oil and natural gas. The study aims to learn the risks of development, structure, and prevalence of occupational pathology among employees of enterprises in the Chukotka and Nenets Autonomous Okrugs. Materials and methods. Scientists studied the results of social and hygienic monitoring under the section "Working conditions and occupational morbidity" in the CHAO and NAO in 2008-2019. Results. In the NAO, almost two-thirds of employees work at facilities with good sanitary and epidemiological well-being indicators, while in the PRAO, only 12%. In the NAO, almost all occupational diseases (96.8%) resulted from exposure to industrial noise (noise effects of the inner ear), mainly in civil aviation pilots. In the CHAO, occupational diseases mainly developed in miners of mining enterprises (80.6%), among which the most common were noise effects of the inner ear (32.5%), chronic bronchitis (24.1%), mono- and polyneuropathies (12.7%). In contrast to the NAO, in 2008-2019, the level of occupational morbidity in the PRAO exceeded all-Russian indicators and tended to increase. The risk of diseases in 2017-2019 was higher than in 2008-2010: RR=2.51; CI 1.62-3.89, p&lt;0.001. In 2008-2019 the probability of the formation of occupational pathology among employees of enterprises in the CHAO was higher than in the NAO: RR=3.84; CI 2.92-5.06, p&lt;0.001. Conclusion. To reduce the occupational morbidity of miners of the CHAO, it is necessary to improve personal protective equipment and technological equipment to reduce noise levels, vibration, the concentration of aerosols of predominantly fibrogenic action, and the severity of the labor process. The use of aviation headsets with an increased level of noise reduction will help reduce the exposure of workers to noise. For solving this problem, it is necessary to update the flight fleet of civil aviation in NAO.

Efficacy of high flow nasal cannula as an alternative to continuous positive airway pressure therapy in surgical patients with suspected moderate to severe obstructive sleep apnea

PurposeTo compare the efficacy of High flow nasal cannula (HFNC) as an alternative to Continuous Positive Airway Pressure (CPAP) therapy on the first postoperative night in patients with suspected moderate to severe obstructive sleep apnea (OSA). MethodsThis is randomised controlled trial conducted in a tertiary hospital which included elective surgical patients with STOP-BANG score of 5 and above. Forty patients were randomised into one of the four postoperative treatment groups: CPAP, or HFNC at three different flow rates (20 L/min, 30 L/min and 40 L/min). The primary outcome measured was the number of recorded drops in baseline SpO2 of >4%. Secondary outcomes measured included the need for supplemental oxygen or other interventions and the total number of hours of usage of the device. Patient satisfaction, preference for device and reasons for their preference were also collected. ResultsCPAP was used for a significantly fewer number of hours compared to HFNC (at all flow rates) during the first postoperative night. There was no significant difference in the primary outcome or in the requirement for other interventions between the four treatment groups. 73.3% of patients in the HFNC group preferred the use of HFNC to the use of CPAP. Reasons for user preference for HFNC include device comfort, ease of use, reduced noise levels and perception of efficacy. ConclusionsHFNC could be an useful alternative to CPAP as it is not inferior to CPAP in the perioperative management of OSA and is better tolerated.

Building performance evaluation of public housing in Harare, Zimbabwe

This study sought to evaluate the performance of residential building spaces in public housing in Harare, Zimbabwe. It specifically measured building performance indicators determined by the building’s characteristics and the physical, locational and service attributes of buildings. A quantitative research design was adopted, in which questionnaires and observations were used in data collection. A two-stage sampling technique was used, because the population could be subdivided into clusters. From residents in three clusters, which include Highfield-Venice Flats, Avenues Flats and Mbare Flats, 263 respondents were conveniently chosen. Results from the independent t-test that was conducted showed that, at 95% confidence level, there exist significant differences in residential satisfaction among residents of Highfield-Venice Flats and those of Avenues Flats (t = 2.159, p-value= 0.035&gt;0.05). Overall, residents are dissatisfied with the attributes of the buildings in which they live and the general residential situation. There is a general dissatisfaction with the buildings, suggesting that the building performance is not meeting their needs and expectations. Housing attribute preferences, privacy, dwelling proximity, and neighbourhood attachment showed a significant and positive impact on general residential satisfaction. Hence, there is a need to improve housing attribute preferences such as improving the quality of air and lighting as well as noise levels, since respondents expressed dissatisfaction with these attributes. Housing ceilings can be installed to reduce noise levels. More so, the quality of air and lighting can be improved by inserting more air ventilations and wider windowpanes. Privacy should be improved by ensuring that the residential structures have boundary walls that may be needed by the residents. More so, dwelling proximity ought to be improved. The Ministry of National Housing and Social Amenities and other public housing institutions can consider developing structures such as shopping centres, public schools as well as roads and social amenities such as parks, pools and workout facilities before they build residential houses.

Optimized nonlocal active sound control in frequency domain

In the active sound control problem considered in the paper, a quite arbitrary closed region is acoustically shielded from ambient noise generated outside via implementation of secondary sound sources which are situated at the perimeter of the domain to be protected. It is presumed that the information available for the operation of control is only limited by the acoustic field that can be measured on a closed surface around the shielded region. The problem becomes much more complicated if there are desired sound sources situated inside the shielded region. In this case the input field is determined by contributions from noise, desired sound and controls. It is supposed that only the total acoustic field is available that makes the statement of the problem quite general and realistic. As the output, it is required to attenuate noise while preserving the desired field unaffected. To tackle the problem, a recently developed algorithm based on the nonlocal control is applied. From the point of view of a practical realization, the number of microphones and loudspeakers should be minimized. We propose for the first time some ways to essentially optimize distribution patterns of controls and sensors for the nonlocal control with preservation of desired sound. Numerical experiments are carried out for noise attenuation in a cube to study the trade-off between the level of noise reduction and number of sensors and controls. It is demonstrated that the nonlocal control can be efficiently realized with a reasonable number of sensors and controls. As shown, with only two controls per wavelength the achieved level of noise attenuation exceeds 10 dB. This result matches the optimal local control when any desired sound is absent.