Industrial Noise Sources Research Articles

Health impact of environmental and industrial noise - a narrative review.

Industrial noise sources are among the environmental noise sources that are ranked second among the causes of ill health in Europe by the World Health Organization. The aim of this paper is to summarize and review of published information focusing on noise annoyance from industrial activities and mining. A search for articles was performed using the bibliographic databases platforms. The epidemiological evidence shows that environmental noise may be associated with cardiovascular and metabolic diseases, impaired cognitive development in children, mental health, post-irritability, and sleep disturbances. As a result of efforts to minimize the effects of industrial noise on human health, the New South Wales Environment Protection Authority published A Guide to the Noise Policy for Industry in 2017, which sets out recommended noise levels, methods, and procedures for noise management based on the latest scientific evidence. Social networks can be used to assess the population's noise annoyance and to verify the effectiveness of the measures. The industrial noise sources are typically defined by low-frequency noise. Low-frequency noise has very low attenuation and is only slightly affected by obstacles, therefore it can be a major cause of night noise annoyance. An association was confirmed between exposure to low-frequency noise and sleep disturbance, psychological problems, cognitive impairment, increased social conflicts, anxiety, emotional instability, nervousness, and reduced mental performance - concentration, and visual perception. In view of the long tradition of mining and industry, the assessment of noise from these activities from the perspective of its impacts on human health is an inherent part of legislative processes. Med Pr Work Health Saf. 2024;75(5).

Prediction and evaluation of the low-frequency noise impact from industrial noise sources

German legislation requires an assessment of low-frequency noise in addition to the regular noise assessment for industrial plants. The detailed prediction and assessment of low-frequency noise immissions is carried out according to the administrative regulation for noise TA Lärm and the German standard DIN 45680. However, a standardised procedure for predictions of low-frequency noise does not exist. For this reason, different approaches for the prediction of low-frequency noise immissions have been developed over the last two decades. Typically, the method according to DIN ISO 9613-2 for sound propagation outside is extended heuristically to the lower frequency range. The predicted low-frequency noise level outside the room is taken as a basis for determining the noise immission level inside the room. The level of knowledge about the quality of sound propagation modeling of low-frequency noise is still debatable. A forecast method of low-frequency noise components should be on the "safe side" in terms of noise control; however, the scope of the required measures to meet the noise requirements must be comprehensible and proportionate. We present an overview of the building blocks of a forecasting process and the challenges that arise. The topic is illustrated by a practical example.

Applications of ventilation-enabling sound insulation devices based on mock-up test findings

Road traffic, railway and industrial noise sources are main challenges in maintaining satisfying acoustical environment for living habitat in Hong Kong. Ventilation-enabling sound insulation devices has been introduced to Hong Kong residential development in the aim of striking a good balance between indoor ventilation and sound insulation. In the form of windows and balconies, the sound insulation devices were applied to mitigate the potential road traffic, railway, and fixed noise impacts. The sound insulation performances of the devices were verified in a 1:1 mock-up test and indicated by in-out difference, which contributed from the outdoor and indoor noise levels. The in-out difference of the sound insulation devices varies with the adopted spectrum, depending on flat layout configurations. The enhancing performance of applied acoustic material to the sound insulation devices, and that of applied acoustic fin adjacent to the devices are also studied.

Unmanned Aircraft/Aerial System (UAS) Noise Compilation

Unmanned aircraft/aerial systems (UASs) can be used for many purposes, for example, in servicing delivery, recreational activities, utility inspection, and film industries. Use of UAS vehicles is limited, with more widespread use pending approval. For some applications, use of UAS vehicles can expose communities to a type of noise not currently experienced, with current noise sources typically related to transportation systems (e.g., aircraft, rail, and road or highway noise sources), home activities (e.g., air conditioning units and lawn car), and industrial noise sources. It is important to understand the type of noise communities will experience with UAS operations.

Long-term environmental noise measurement methods for industrial noise sources

Industrial noise sources can impact nearby residential communities, especially in rural areas. In order to assess the situation after commissioning, plant noise must be reliably differentiated from prevailing ambient, transient environmental noises, and weather-related events. Continuously attending such measurements is generally impractical. On the other hand, classifying events by eyeballing a stream of Leq values after the fact isn't sufficiently reliable in most cases either. An effective approach is presented that involves measurement and statistical, observational, and analytical methods to perform much of the work in an automated fashion. Methods include statistically excluding transients from the Leq, filtering to eliminate birds and bugs, spectral characteristics of wind events, and potential spectral identifiers indicative of operation. Classifications are confirmed by listening to periodic and/or event-driven audio segments. This approach works best when both the plant noise and prevailing ambient are quasi-steady; plant-generated transients and weather events may require manual reclassification. Examples from long-term environmental noise studies are provided. The methods are neither dramatic nor novel but their effectiveness in combination may be useful, especially for those new to this type of work.

Loudspeaker modeling using CadnaA in an urban environment

CadnaA is traditionally used to model environmental noise sources, such as traffic, trains, and industrial noise sources. In this presentation, we will talk about past experiences using CadnaA to model outdoor noise levels from loudspeakers at music venues in an urban environment. This noise modeling was validated by comparing to “real world” measured data.

Order domain beamforming for the acoustic localization of rotating machinery under variable speed working conditions

Rotating machinery is widely used in the modern industry, which undergoes huge amounts of variable speed working conditions. Localizing the sound sources of the rotating machinery on a specific order is significant to noise source identification and fault diagnosis. The order domain beamforming method (ODBF) is proposed in this paper to localize the source in the rotating machinery at a specific order. Firstly, the measured acoustic array signals are resampled into the angle domain via the key phase signal. Then, the fast Fourier transform is operated to obtain the acoustic pressure on a specific order. Finally, with the derivated steering vector in the order domain, the proposed order domain beamforming method can obtain the acoustic map on the scanning plane to localize the primary acoustic sources of the rotating machinery. The numerical simulation investigates the performance of the proposed ODBF under different cases. The industrial motor noise source identification experiment further verifies the effectiveness of the proposed ODBF.

Tools for evaluation and prediction of industrial noise sources. Application to a wastewater treatment plant.

In recent years, acoustic pollution caused by noise has considerably increased in many countries. Particularly in Spain, the noisiest country in Europe. It is sometimes difficult to predict the noise levels that a new installation or an expansion of industrial equipment will cause in the surroundings. This work introduces a new methodology for the prediction, evaluation, and analysis of industrial noise sources, as well as a novel tool for predicting and categorizing outdoor noise from its measurement at their sources. A Wastewater Treatment Plant (WWTP) has been used to demonstrate the applicability and validity of this methodology. The continuous level of acoustic pressure equivalent has been measured in different points of the plant using an integrating sound level meter. From these values, noise maps have been built to obtain detailed information of the industrial noise generated in the installation. Also, the typical frequency patterns of each type of source have been used for the calculation of source noise apportionments. To achieve this objective, several noise sources have been selected to provide information about their contribution to the industrial noise in the WWTP surrounding area. Finally, predictions have been validated using actual measurements. This methodology is a useful tool to predict personal exposure to noise and the impact on the environment. This information can be used, in particular, to propose mitigation actions.

Exposure to industrial noise: impacts on cognitive performance

Research on the relation between exposure to noise and cognitive performance inside industrial environments is not as broad as on office environments. For a better understanding of the specific industrial noise problems, participants performed arithmetic tests inside a hemi anechoic room while they were exposed to sounds of five typical industrial noise sources. The subjects also classified how annoying they perceived the noise signals. The effect of noise on the arithmetic test's performance was larger on accuracy than on velocity, which was verified using a Student t-test. Spectral-temporal characteristics - especially high frequency content and strong low frequency modulation - appear to relate better with lower performance on the test than high sound levels. Subjects that evaluated noise as more annoying performed worse in a final arithmetic test (under silence) after being exposed to the noises, indicating a possible cumulative effect of noise on performance. The findings provide a better insight in the cognitive behavior of people who are exposed to industrial noise. Hence, the study will proceed with the specific noise analysis of single industrial workplaces.

Mathematical models for the improvement of detection techniques of industrial noise sources from acoustic images

In this paper, a procedure for the detection of the sources of industrial noise and the evaluation of their distances is introduced. The above method is based on the analysis of acoustic and optical data recorded by an acoustic camera. In order to improve the resolution of the data, interpolation and quasi interpolation algorithms for digital data processing have been used, such as the bilinear, bicubic, and sampling Kantorovich (SK). The experimental tests show that the SK algorithm allows to perform the above task more accurately than the other considered methods.

Innovative techniques for the improvement of industrial noise sources identification by beamforming

Abstract An innovative technique based on beamforming is implemented, at the aim of detecting the distances from the observer and the relative positions among the noise sources themselves in multisource noise scenarios. By means of preliminary activities to assess the optical camera focal length and stereoscopic measurements followed by image processing, the geometric information in the source-microphone direction is retrieved, a parameter generally missed in classic beamforming applications. A corollary of the method consists of the possibility of obtaining also the distance among different noise sources which could be present in a multisource environment. A loss of precision is found when the effect of the high acoustic reflectivity ground interferes with the noise source.

Variability due to short-distance favorable sound propagation and its consequences for immission assessment.

The specific noise immission from an (industrial) noise source is commonly assessed by short-term measurements. Good practice prescribes measuring under downwind conditions at modest wind speeds. Nevertheless, this still leads to large variation, even at short distances and needs quantification. More specifically, the variation in sound propagation due to the changing refractive state of the atmosphere and the relatively large variation in soil impedance one can find for (visually determined) "grassland" is studied. Highly detailed meteorological tower data were combined with measured grassland impedances. These data are fed to the full-wave one-directional Green's function parabolic equation sound propagation model. The variation, even under these good-practice measurement conditions, is found to be large, and strongly dependent on sound frequency, source height, receiver height, and propagation distance. When assessing the specific sound pressure level from a multitude of sources, this variation strongly decreases compared to a low-height single source. Besides absolute variations, fluctuations in the transmission loss between a close point and a more distant one are discussed in this paper. The variation ranges give an idea on this systematic uncertainty when performing short-term measurements, and their impact on convergence to yearly averaged equivalent sound pressure levels.

Cumulative Industrial Noise Impact on the Environment

Abstract The paper presents basic legal conditions, applicable to the calculation of cumulative noise levels in the environment with indication mainly on lack of detailed regulations both in formal and methodological approach for evaluating those levels. The paper is focused on methodological approach with the emphasison analysis of existing case studies in the industry. The main subject of the analysis is the cumulation of industrial noise sources: newly designed and existing ones, together with a proposal of accumulate other types of the noise. Evaluation of cumulative noise levels for new (designed) objects is realised by computational methods, and for existing objects, by measurements or by combination of measurement and computational methods. It is assumed that the cumulative level is an energetic sum of the rating levels for all installations and it will not exceed the limit value in a given place. For the cumulation of different noise sources, the weighting for criterion values of these sources will be applied in aggregation.

The field study and numerical simulation of industrial noise mapping

The acoustic environment is known to have a physiological as well as psychological impact on human health and also have a great importance in the establishment of comfort conditions. Accordingly, a healthy environment and better quality of life depend on environmental noise control. There are numerous research about traffic, airport and railway noise mapping studies with related to the subject in the literature. However, there are some other factors affect the outcomes of the noise mapping studies such as how the industrial buildings is used. Although this factor effects significantly the industrial noise mapping studies, there is no sufficient number of research studies refers this topic. In fact, the research studies about the noise level of industrial units and their interaction between its surrounding areas play a key role on the industrial noise mapping. It is a well-known fact that there are too many parameters effect the noise mapping results in the real world applications. On the contrary, in the local areas such as an industrial estate, some parameters can be more effective on the noise level and may need a special attention in order to obtain noise mapping results accurately. This study deals with the issue of industrial noise mapping process as part of ensuring environmental noise control and demonstrates that there is a strong relation between the noise level of an industrial estate and the usage of the industrial buildings. In order to achieve this purpose, numerical analysis and some field researches were carried out in the study. In this scope, the sound levels of industrial noise sources were determined and – on the basis of the prevailing sound propagation conditions – a noise map was established for the region. For the industrial noise map, the limit values published in the Turkish Environmental Noise Regulation were used, and the number of people affected by excessive noise levels determined. Noise barriers were designed and their impact on reducing excessive noise in populated areas to acceptable limit values were evaluated. It is concluded that the industrial noise mapping research systematically carried out in order to show the role of the sensitivity analysis related to the different opening of the doors of the industrial buildings.

DETERMINATION OF SOUND ABSORPTION COEFFICIENT FOR PLATES AND LAYERED COMPOSITE MATERIAL MADE FROM TEXTILE WASTE AND CORK

<p>For sustainable development of the textile industry must find solutions to reduce waste and decrease noise at work. Of textile waste are obtained boards of different thicknesses, which aim to be wide field of use. For it is to achieve some experimental results about the soundproofing of plate types: is studying recoverable boards made of short textile fiber and cork boards. Textiles have a thickness of 3 mm and 10 mm and cork boards with a thickness of 3 mm and 10 mm. For determining is used the impedance tube reading Brüel&Kjaer, type 4206. By analyzing the absorption coefficient results that materials have absorbing characteristics that increase with material thickness. From these boards aims to obtain laminated composite materials used to encapsulate industrial noise sources.</p>

Noise Pollution in Irbid City — Jordan

Noise defined as any sound that annoys or disturbs humans or that causes or tends to cause an adverse psychological and physiological effect on humans. Irbid is one of the most populated cities in Jordan. It is environmentally noise polluted due to the rapid and widespread introduction of mechanical methods for production and for their transportation. L10, L50, L90 and LAeq noise levels were measured during the day time and night time to assess and evaluate the noise levels from mosques, schools, celebration halls, streets, building works, industrial areas and commercial areas. The results of the investigation showed that the measured noise levels from all the selected sources were high during the day time and the noise problem is not only limited to day time, but continues in night time in this city. These noise levels were higher than those set by Jordanian limits during day time and night time. A significant correlation between the measured statistical noise levels L10, L50 and L90 and equivalent continuous noise level LAeq were also detected. The mean value of industrial noise source was motors of large vehicles and engines. Whereas the presence of slow moving vehicles, low speed and honking of horns during traffic ingestion periods lead to an increase in noise levels in commercial areas. The noise from building machines and equipment (dredges, concrete mixers, concrete pumps and jackhammers) is quite different from that of traditional equipment. The construction machines have engines that produce a loud, fluctuating noise with varying frequencies that can propagate the sound for a long distance. The noise produced by these engines is particularly disturbing due to the wide variations in frequency and volume.

Method to improve warning sound detection for hearing protectors

Hearing protection devices (HPDs) provide both desirable attenuation of environmental noise and undesirable attenuation of auditory warning alarms, such as vehicle backup alarms. Both warning alarm detection and localization performance are affected. A digital cross-correlation based method is described to identify a pre-selected warning alarm to bypass the attenuation of the HPD while maintaining attenuation of environmental noise outside the bandwidth of the alarm. This method can be integrated into existing digital HPD designs. Computer simulation of the algorithm demonstrates that an alarm signal can be detected at signal-to-environmental noise ratios as low as 30 dB for the military and industrial noise sources investigated. Implementation of the method using a modified commercial HPD demonstrates a 7 dB improvement in warning alarm detection threshold compared with an unmodified HPD. Alternative methods for presenting the alarm signal to the user will be discussed as well as modifications to expand the method to accommodate multiple alarm signals.

Reducing of the Sound Pressure Level in Industrial Areas by Screening Noise Sources

This paper presents several ways in which the propagation of acoustic waves produced by an industrial noise source can be attenuated by identifying the optimal location of an acoustic screen near the noise source. Six types of acoustic screens were used, made of six types of materials (of the category used in the field of construction), with or without sound absorbing qualities. The noise source was placed in four different positions in front of the acoustic screen. The microphone was placed in 16 recording positions, at four distances and four heights. The experimentally obtained values indicate that the efficiency of the acoustic screen is optimal when the screen is placed at a reduced distance from the noise source, in a centered position. To obtain a high degree of sound pressure level attenuation, one can choose among variants with at least two screening walls positioned in a “V” form.

Total annoyance from an industrial noise source with a main spectral component combined with a background noise

When living close to an industrial plant, people are exposed to a combination of industrial noise sources and a background noise composed of all the other noise sources in the environment. As a first step, noise annoyance indicators in laboratory conditions are proposed for a single exposure to an industrial noise source. The second step detailed in this paper involves determining total annoyance indicators in laboratory conditions for ambient noises composed of an industrial noise source and a background noise. Two types of steady and permanent industrial noise sources are studied: low frequency noises with a main spectral component at 100 Hz, and noises with a main spectral component in middle frequencies. Five background noises are assessed so as to take into account different sound environments which can usually be heard by people living around an industrial plant. One main conclusion of this study is that two different analyses are necessary to determine total annoyance indicators for this type of ambient noise, depending on the industrial noise source composing it. Therefore, two total annoyance indicators adapted to the ambient noises studied are proposed.

Annoyance from industrial noise: Indicators for a wide variety of industrial sources

In the study of noises generated by industrial sources, one issue is the variety of industrial noise sources and consequently the complexity of noises generated. Therefore, characterizing the environmental impact of an industrial plant requires better understanding of the noise annoyance caused by industrial noise sources. To deal with the variety of industrial sources, the proposed approach is set up by type of spectral features and based on a perceptive typology of steady and permanent industrial noises comprising six categories. For each perceptive category, listening tests based on acoustical factors are performed on noise annoyance. Various indicators are necessary to predict noise annoyance due to various industrial noise sources. Depending on the spectral features of the industrial noise sources, noise annoyance indicators are thus assessed. In case of industrial noise sources without main spectral features such as broadband noise, noise annoyance is predicted by the A-weighted sound pressure level L(Aeq) or the loudness level L(N). For industrial noises with spectral components such as low-frequency noises with a main component at 100 Hz or noises with spectral components in middle frequencies, indicators are proposed here that allow good prediction of noise annoyance by taking into account spectral features.