Sound Level Meter Research Articles

Acoustic noise in a small-format 3.0-T neonatal MRI system.

Today, magnetic resonance imaging (MRI) is rarely used in managing the care of premature neonates. This is in large part due to the medical and logistical challenges associated with moving neonates from the neonatal intensive care unit (NICU) to the radiology department. Furthermore, acoustic noise associated with MR scanning poses safety concerns for both practitioners and neonatal patients. A small-format 3.0-T neonatal scanner was recently developed and placed within the NICU to address these logistical and acoustic challenges. To compare acoustic noise measurements of a small-format 3.0-T neonatal MRI scanner with conventional adult-sized 1.5-T and 3.0-T MRI scanners using identical neonatal head imaging protocols. Sound pressure level (SPL) measurements of a standard imaging protocol were made in a small-format neonatal 3.0-T MRI scanner as well as in adult-sized 1.5-T and 3.0-T scanners. SPL measurements were made with a Brüel & Kjær sound level meter model 2250. The statistical significance of the differences in SPL between scanners was determined using one-way ANOVA. Average sound pressure level values were measured in unweighted decibels (dB) and A-weighted decibels (dBA) for all imaging sequences in the protocol. The average A-weighted SPLs for the NICU from 1.5-T and 3.0-T MRI scanners were 81.02 ± 0.28 dBA, 87.00 ± 0.85 dBA, and 94.91 ± 0.65 dBA, respectively. SPLs at the isocenter of the NICU MRI scanner were 5.98 dBA quieter than in the 1.5-T scanner (P=0.007), and 13.89 dBA quieter than in the 3.0-T scanner (P<0.001). For staff standing next to the scanner, the NICU scanner was 20.24 dBA quieter than the 1.5-T scanner (P<0.001) and 19.28 dBA quieter than the 3.0-T scanner (P<0.001). The NICU 3.0-T MRI system is significantly quieter than conventional adult-sized MRI systems, improving safety for neonatal patients. Significant reductions in SPL were also noted inside the screen room where clinicians may be present during scanning.

Monitoring and measuring noise pollution in urban environments (Case study: Khorramabad city)

Introduction: Environmental noise, caused by traffic, leads to increased risk of health problems. Nowadays, noise pollution is one of the most important problems in the communities which adversely affects the health. The aim of this study was to assess the noise pollution in Khorramabad city. Materials and methods: To measure the noise level in the city, 39 stations near to sensitive places such as hospitals, educational centers, and so on were selected. Measurements were performed, for 30 min, in the mornings (7-10 AM) and evenings (5-8 PM) using a standard sound level meter. The measurements were made on working days during the week and assuming the traffic load was the same. Results: The sound level in all 39 considered stations was higher than the standard of residential-commercial in more than 90% of the stations compared to the environmental standard. The mean of sound measured in the monitored stations was equal to 68.28±2.6 dB. The maximum measured sound level belonged to station S2. In station S2, the maximum measured sound was reported as 81.72±11.3 dB. The findings showed that sound level in the evenings were slightly higher than the mornings. Also, in the evening, the highest and lowest measured sound values belonged to stations S1 and S20. The amount of measured sound level at stations S1 and S20 was equal to 80.9 and 39.7 dB, respectively. Based on findings, the highest and lowest sound recorded belonged to stations S39 and S20 which area type of stations S20 and S39 was commercial and residential, respectively. Conclusion: This study showed that the average level of sound pressure was higher than the permissible limit, so the necessity of planning is suggested to reduce the level of noise pollution and consequently reduce the anxiety level of citizens and increase health.

Analysis of the Gaussian assumption of single sound source measured and processed through sound level meter

Machine learning (ML) techniques are constantly growing in acoustics. Such methods exploit large databases to train algorithms and earn complex feature correlations. The primary goal is to obtain inferences and predictions. Thus, ML often exploits statistics, and understanding the data distribution becomes fundamental when analyzing the available data. However, it is well-known that only some common methods can be used with large databases, e.g., normality tests are discouraged. The present work aims to explore the Gaussian assumption underlying a validated clustering technique used in long-term monitoring of sound level meters. The Gaussianity of single sound sources is analyzed through normal tests, normal probability plots, cumulative distribution functions, and high-order moments. The analysis involves a real-world measurement carried out through a sound level meter and speech recordings obtained from a common database used in machine learning. Results show that a single sound source can be deemed Gaussian in sound level meter long-term measurements, leading to important insights concerning the choice of algorithms.

Case study of simplified reverberation time measurement under multiple conditions using a sound level meter

Recent advancements in the computational capacity of sound level meters have facilitated the simultaneous recording of diverse calculation results and waveform recording data. Traditionally, reverberation time determination entailed manually adjusting a linear regression line to the reverberation decay curve derived from recorded sound levels, followed by reverberation time computation based on the gradient of said line. However, automated techniques have made reverberation time calculation via a sound level meter feasible. This paper discusses a case study evaluating the efficacy and considerations of simplified reverberation time measurements conducted across various conditions, encompassing scenarios with multiple sound sources and diverse indoor environments. The study leveraged recorded data from a sound level meter and employed automated methods simulated on a personal computer.

Large aperture microphone array measurement at operating airport for sound source model creation of J-FRAIN

In 2022, authors conducted microphone array measurements at an operating airport to create sound source models for commercial aircraft based on the noise prediction framework J-FRAIN. A similar measurement was also performed by our colleagues in 2019, but it was a trial to establish the concept of the framework and was done using a microphone array in which the number of microphones was reduced to about half. In order to improve the accuracy of the sound source models, the microphone array with a 30-meter diameter consisting of 195 microphones mounted on the ground was used in 2022. Recording-based simultaneous noise measurement using sound level meters was also performed around the airport to validate prediction results in terms of time histories of 1/3 octave band sound pressure levels. This paper describes an overview of the microphone array measurements conducted in 2022 and a case study of noise prediction around the airport using sound source models created from the data of microphone array measurements conducted in 2022. Predicted results are compared with 1/3 octave band data measured using sound level meters mounted at a height of 4 m above the ground at sites of noise monitoring stations around the airport.

On the acceptance limits for short-term level fluctuation of sound calibrators

To ensure noise measurement accuracy, sound calibrators are used to check the sound level meter accuracy before and after any such measurements, as required by most noise regulations. The sound calibrator itself needs to be calibrated routinely and traceable to national standards. The International Standard IEC 60942, Electroacoustics - Sound calibrators, specifies performance requirements for the sound pressure level, short-term level fluctuation, frequency, and distortion and associated test methods. However, the acceptance limits for short-term level fluctuation specified in IEC 60942 is problematic. The short-term level fluctuation acceptance limits specified in Table 2 of IEC 60942 for the level variations inherited by a stable sinusoid at low frequencies are either underestimated or overestimated. In this paper, a detailed theoretical analysis is presented addressing this particular issue. Closed-form solutions are obtained for typical sinusoidal sound signals. Two experimental setups and measurement results for the validation of the theoretical analysis are also presented. One uses a commercial sound level meter and the other uses a precision sound pressure measurement system developed recently at the National Research Council Canada. A revised table for the acceptance limits is then proposed for the future revision of Table 2 of IEC 60942.

Reliable metrology for infrasound sensors

The reliable assessment of infrasound has become increasingly important in the last years. Reliable measurements require calibration of the employed sensors with traceability to the SI. While there is measurement equipment capable of measuring infrasound available, there is no sufficient calibration below 10 Hz. Traceability for airborne sound is currently realized by primary calibration methods which are applicable down to 2 Hz, with limitations below 10 Hz. Against that background, a primary and a secondary calibration setup have been developed at PTB. Together they enable the traceable calibration of a variety of infrasound sensors such as microphones, sound level meters or microbarometers. Moreover in practice, procedures are necessary which ensure reliable results in a field environment even with external disturbances. A field study was conducted comparing the performance of measurement microphones and microbarometers at a wind park. Emphasis was placed on different means of protection against wind induced noise. Additionally, a laboratory study investigated the influence of small damages to a microphone diaphragm on the reliability of the microphone. In this contribution, the newly developed calibration setups for infrasound sensors and the insights from the field and laboratory studies are presented.

Generating a virtual acoustic environment to approximate the soundscape of a historical cathedral

This paper focuses on the generation of a virtual acoustic environment of a historical cathedral basilica located in St. Augustine, Florida, USA. The virtual acoustic environment is an effective means to study a cultural heritage's soundscape that restricts visitors from accessing and being quiet. The author used a laser scanner to capture the reality of the cathedral's interior, in order to maximize the visual perception of the worship space, and created a 3D digital textured mesh model using the points cloud generated from laser scanning. The spatial experience recorded by a 360 camera with an ambisonic microphone provided the virtual soundwalk at multiple locations. The background and foreground sound were synthesized in Unity using the same music recordings that the church used during the day. The sound pressure levels were closely matched with the ones measured by a sound level meter. The virtual acoustic environment was simulated by using spatial applications in Unity and optimized through the comparison of the room acoustical measurements performed based on ISO 3382.

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.

Exploring the frequency response of mobile phones applications for sound monitoring in urban green spaces

Citizen science engages non-professional scientists globally in scientific endeavors, fostering commitment to environmental conservation initiatives. This research explores the frequency response of mobile phones for sound monitoring, particularly in the context of urban green spaces. The method involves Laboratory tests at the Brazilian National Metrology Institute, Standardization, and Industrial Quality (Inmetro), evaluating two Android and one iOS devices using the NoiseCapture and Openoise apps. Laboratory tests conform to the frequency response standards outlined in IEC 61672-1, covering the 63Hz to 16kHz range. Following this, the devices captured audio scenes encompassing human, natural, and machine sounds at the University of São Paulo campus. Findings revealed that the frequency response of iPhones functioned as Class 2 sound level meters except for low-frequency bands. Android consistently performed similarly across both applications tested and exhibited acceptable performance in mid-range frequencies. Therefore, when considering citizen science projects, emphasis should be placed on app selection, prioritizing additional features like sound mapping. Field results showed minimal errors from human and transportation sounds but challenges with high-frequency components from birds, insects, and machines. The study concludes the necessity for alternative measurement systems identifying animal sound sources, along with involving non-professional scientists in scientific research.

Beyond loudness: development of a holistic solar-powered urban soundscape sensor

Low-cost sensor networks have increasingly been used to monitor noise pollution as an alternative to certified sound level meters. Existing sensor networks monitor loudness and, in some cases, classify sound sources. Most sensors do not capture metrics that are more representative of the human perception of sound, require a permanent power supply, or are relatively expensive. We develop an energy-efficient soundscape sensor with the goal of recording metrics complementary to loudness. We have implemented metrics from psychoacoustics and metrics inspired by biodiversity research, such as sharpness, intermittency, and acoustic entropy. Furthermore, the sensor predicts the source of sound events. For privacy-preservation, all audio is processed directly on the sensor. The sensor is based on a low-power microcontroller (ESP32-S3), available for a fraction of the cost of a Raspberry Pi, which is often used for sound source prediction. Finally, the sensor is solar-powered and therefore easy to install for research purposes at places without direct access to the power grid. A temporary deployment of several sensors in Amsterdam, the Netherlands, is planned

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.

Development and distribution of an in situ experimental wind turbine noise database

The PIBE project is the first French collaborative research project on wind turbine noise. One of its objectives is to quantify the experimental dispersion observed in situ on acoustic quantities/metrics and influencing parameters, and to compare it with the numerical dispersion estimated using acoustic propagation models. A long-term experimental campaign was carried out over consecutive 410 days around a wind farm comprising eight 80-metre-high and 90-metre diameter turbines. Acoustic sensors (five Class I sound level meters) were deployed on site, recording third-octave spectra and overall A- and Z-weighted values of the Leq indicator and fractile indices (L10, L50 and L90), at distances from 325 m to 1400 m from the wind turbines row. In addition, three 3D ultrasonic anemometers and a Lidar system were used to measure meteorological variables influencing long-range sound propagation (e.g. wind and temperature verical profiles). Besides, train and aircraft passing close to the site were inventoried to identify periods of high background noise. All experimental data have been processed into an ElasticSearch database. An interactive web application has been developed in R Shiny to facilitate processing, visualization and analysis of the experimental database.

Noise within hospital wards: a survey method

Noise pollution is one of the most disturbing environmental factors. It directly affects people's lives, especially vulnerable people such as children, old-age, and hospital patients. Hospitals are complex buildings with manifold spaces and facilities where different users live with different sensitivity to noise. Several studies highlight the discomfort that patients, staff, and visitors experience in hospitals due to inadequate noise levels. All this leads to stress, sleep disorders, interference in communication, aggression, and annoyance. Noise exposure in hospitals is due to several sound sources. Each varies throughout the day, and their detection could be challenging. The present study proposes a clustering technique to analyze long-term sound level meter monitoring in an Italian hospital (Pisa, Tuscany). Equivalent short-term levels obtained with an interval time of 0.1 s are used as the database to exploit the occurrences curves of different chunks of the monitoring. Then, through a validated method, the spectra of different kinds of sound sources are reconstructed via the Gaussian Mixture Model. Results are compared with near-field measurements of single sources.

The innovated national noise monitoring network in The Netherlands

Over ten years ago, the National Institute for Public Health and the Environment started monitoring noise emissions from major roads and railways in The Netherlands. Today, this monitoring program is still going strong. The measured data is used to validate the yearly reported noise production levels calculated by the Dutch road and railway authorities, to monitor trends in noise production, and to check the validity of the Dutch noise calculation method. Measurements in the entire network are performed at an altitude of four meters close to fifty meters from the major road or railway in free field as these are the requirements for the reported calculated levels. The network therefore, has to operate stand-alone, resulting in challenges in terms of power supply, datastorage and communication. Ten years ago, we started with a battery-powered network of simple and cost-effective dataloggers. Recently, we made innovations by transitioning to a solar-powered network of modern sound level meters with remote data communication. In this presentation I will give a brief history of this monitoring network, how it developed, and show you the possibilities of the present-day innovated network.

Setting up light and noise maps to define the contours of a reserve of darkness and silence in Sherbrooke, Québec, Canada

Urban sprawl brings cities closer to natural areas, making them cohabit is a significant environmental challenge. Densification can also increase light and noise pollution, negatively affecting human and biodiversity well-being. Grounded on a collaboration between a college and a university, this work combines brightness and noise maps to establish the contours of a reserve of darkness and silence in Sherbrooke's Mont-Bellevue Park (Québec, Canada). The light and sound environments of the city are mapped by the research team using two devices mounted on vehicles or bicycles: a multispectral and multidirectional brightness sensor and a sound level meter. Long-term and fixed-point light and noise measurements were also conducted to develop the mobile measurement protocol. Wind tunnel measurements in an anechoic chamber were finally used to determine the effect of travel speed on measured noise levels, showing that speeds of less than 15 km/h ensure unbiased acoustic measurements using a windscreen. Perspectives include using the Noise Capture application to provide crowdsourced and additional noise levels at fixed measurement points. The open-source Noise Modelling tool will provide us with calculated environmental noise maps to be compared with measured data.

Improving knowledge of the acoustic factors involved in railway noise annoyance: first results of a pilot field survey of sixty-two local residents

Railway transportation contributes to the objectives of decarbonization but also generates negative externalities, including noise. Energy noise indicators used to characterize population exposure do not adequately reflect the repetitive nature of railway noise peaks. The GENIFER pilot study aims to test a protocol designed to characterize railway noise events according to the instantaneous perceived annoyance when the train is passing, in order to improve understanding of the influence of acoustic factors on annoyance. The first phase of the survey was carried out in 2023 among 62 residents of a pilot site. An electronic device was used to collect around 5,000 ratings, ranging from 1 to 10, assessing the instantaneous annoyance induced by train noise at passing trains. The site instrumentation included sixteen sound level meters and two video recording systems, enabling annoyance ratings to be associated with the acoustic characteristics of railway noise events. A questionnaire aimed at identifying co-determinants of long-term annoyance was also administered to participants. Feedback on the field implementation of this survey and initial results concerning acoustic measurements, instantaneous annoyance ratings and questionnaire responses will be presented.

Systematic review of environmental noise in neonatal intensive care units.

To systematically review the literature on noise exposure within the neonatal intensive care unit/special care nursery settings, specifically to describe: noise characteristics, sources of noise and ways of measuring noise. Systematic searches were conducted through databases Medline, Embase and PubMed. Studies were included if they met the inclusion criteria (1) reported noise characteristics; (2) reported noise exposure measurements; (3) in the neonatal intensive care unit/ special care nursery settings. Methods and key findings were extracted from included studies. Quality analysis was done using a modified version of the Newcastle-Ottawa Scale. We identified 1651 studies, screened 871, reviewed 112 and included 47. All reported NICU average equivalent sound levels were consistently louder than recommended guidelines (45 dB). The most consistent association with higher sound pressure levels were noise sources grouped under people congregation. Half of the studies did not use measuring devices adhering to international sound level meter (SLM) standards. All NICUs exceeded recommended accumulative sound levels. People were the most consistent source of noise. Sound pressure levels need to be consistently measured with devices adhering to international SLM standards in future studies.

Mapping critical soil moisture thresholds of water stress for global grasslands

The critical soil moisture threshold (SMth) of plant water stress distinguishes whether vegetation is in an energy-limited or water-limited regime. Accurate quantification of SMth for grasslands holds significant implications for drought monitoring and efficient grassland management. However, our understanding of SMth within global grasslands remains limited. In this study, we investigated the relationship between SMth and environmental factors and mapped the global SMth for grasslands based on the estimated SMth across FLUXNET sites. Firstly, SMth was identified and estimated for 18 distinct grassland sites. Then, the factors significantly affecting SMth were investigated and the global SMth for grasslands was predicted using an empirical linear model. Our results showed that SMth was significantly positively correlated with mean annual soil moisture (SM), mean annual precipitation (PRE), and maximum annual LAI (LAImax), while negatively correlated with vapor pressure deficit (VPD) and shortwave radiation (RAD). These factors collectively constrain SMth well, with the coefficient of determination of 0.79. The estimated mean SMth for global grasslands from 2000 to 2021 is 27.8%, with a range from 1.3% to 55.2%. The SMth values are lower in the northern hemisphere than that in the southern hemisphere. The highest values of SMth, exceeding 40.0%, are mainly distributed in Brazil, Peru, Southern Europe, New Zealand and the Tibetan Plateau. In contrast, the lowest values, failing below 20.0%, are mainly distributed in Northern Canada, Greenland, Central African Savannah and Kazakhstan. The SMth is markedly lower in the arid region than that in the tropical and temperate regions. The quantified SMth in this study could provide a direct way to determine whether and to what extent grasslands are subjected to water stress, which would greatly facilitate the study of drought or water stress effects on vegetation growth for grassland ecosystems.

Work and Environment Related Characteristics Associated with Voice Disorders among Primary School Teachers

The objective of this study is to assess work and environment related factors associated with voice disorders among primary school teachers in the Colombo district in Sri Lanka. Methods: An institution based cross sectional study was conducted among 790 primary school teachers, in the Colombo District in Sri Lanka. They were selected by a stratified random sampling method. The validated Voice Handicap Index (VHI-30) questionnaire and a self-administered questionnaire were used for data collection. Sound levels within 10 selected classrooms were measured objectively using CR:303 sound level meter (Cirrus). Data analysis was by bivariate method with chi squared and logistic regression. Results: Among the work related characteristics assessed teaching 5 or more subjects (OR=1.40, CI = 1.039, 2.90), staying after school hours (OR=1.69, CI = 1.19, 2.38) were significantly associated with voice disorders. Among the factors associated with work environment, teachers having a speech pattern in yelling and shouting category (OR=2.25, CI=1.68, 2.99), speaking in noisy environments (OR=1.09, CI= 1.15, 3.15), being exposed to smoky dusty environments (OR = 1.61, CI= 1.19, 2.16), having average or high dust levels in classrooms (OR=2.03, OR=1.50, 2.76), having a moderate to high noise level in classrooms (OR= 1.93, CI=1.45, 2.58) and having ‘just adequate, inadequate and average’ space in a classroom (OR=1.74, CI=1.29, 2.34) were significantly associated with voice disorders. The sound levels objectively measured in classrooms revealed that all classrooms had higher than acceptable noise levels during a teaching session. Conclusions and recommendations: The association of voice disorders with work related characteristics were similar to the findings in other studies. However, the high noise levels detected in the classrooms on objective measurement were high. It is recommended that these findings be addressed through a multidisciplinary approach and National standards for acceptable noise levels within classrooms be established.