Exposure to industrial noise: impacts on cognitive performance

2021 ◽  
Vol 263 (4) ◽  
pp. 2590-2600
Author(s):  
Luiz Henrique Mesa Casa Pereira ◽  
Björn Knöfel ◽  
Jan Troge ◽  
Welf-Guntram Drossel ◽  
Marcel Klein ◽  
...  
Keyword(s):  
Cognitive Performance ◽  
Noise Analysis ◽  
Low Frequency ◽  
Cumulative Effect ◽  
Noise Sources ◽  
Industrial Noise ◽  
Sound Levels ◽  
Office Environments ◽  
High Sound ◽  
High Frequency Content

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.

scholarly journals INFRASOUND AND LOW FREQUENCY NOISE IMMISION FROM PIPELINES. iMPROVING THE ISO 1996-2:2017 PROPOSED METHODS. CASES STUDIES CONDUCTED AT LOS ANDES AND PERUVIAN RAINFOREST

Akustika ◽  
2019 ◽  
Vol 32 ◽  
pp. 335-345
Author(s):  
Walter Montano
Keyword(s):  
Low Frequency ◽  
Sound Level ◽  
Frequency Noise ◽  
Gas Extraction ◽  
Howler Monkeys ◽  
Noise Sources ◽  
Industrial Facilities ◽  
Sound Levels ◽  
Continuous Noise ◽  
Amazonian Rainforest

The gas extraction wells are in Amazonian rainforest and by them there are their industrial facilities. The pipeline has about 800 km with four pumps stations and two compressor stations. The challenge of conducting sound measurements was important-there is no specialized literature-and other noise "sources" are howler monkeys, cicadidae chirping, woodpeckers, trees´foliage, etc. However the problem is simply because those fixed industrial facilities are the only ones. People live in isolated hamlet on the side of dirt roads, so they are exposed 24/7 to the continuous noise; at homes 4 km away from the plants the sound level is 60 dBC, but in the spectrum of ILFN tones could not be identified. This Paper presents the procedures that were developed to identify the ILFN tones, improving the methods proposed in ISO 1996-2, writing a software that "automatically eliminates" the sound levels that don´t belong to the industry,

Low Frequency Noise Analysis in Advanced CMOS Devices

2011 ◽  
Vol 324 ◽  
pp. 441-444 ◽  
Author(s):  
Jalal Jomaah ◽  
Majida Fadlallah ◽  
Gerard Ghibaudo
Keyword(s):  
Experimental Data ◽  
Noise Analysis ◽  
Low Frequency ◽  
Deep Submicron ◽  
Electrical Noise ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Noise Sources ◽  
The Impact ◽  
Mobility Fluctuations

A review of recent results concerning the low frequency noise in modern CMOS devices is given. The approaches such as the carrier number and the Hooge mobility fluctuations used for the analysis of the noise sources are illustrated through experimental data obtained on advanced CMOS generations. Furthermore, the impact on the electrical noise of the shrinking of CMOS devices in the deep submicron range is also shown.

scholarly journals Noise conversion of Schottky diodes in mm-wave detectors under different nonlinear regimes: modeling and simulation versus measurement

2015 ◽  
Vol 8 (3) ◽  
pp. 479-493 ◽  
Author(s):  
Jéssica Gutiérrez ◽  
Kaoutar Zeljami ◽  
Enrique Villa ◽  
Beatriz Aja ◽  
Maria Luisa de la Fuente ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Noise Analysis ◽  
Schottky Diodes ◽  
Source Parameters ◽  
Low Frequency ◽  
Operating Conditions ◽  
Noise Sources ◽  
Wave Detector ◽  
Detector Output ◽  
Conversion Matrix

This paper presents and discusses several methods for predicting the low-frequency (LF) noise at the output of a mm-wave detector. These methods are based on the extraction of LF noise source parameters from the single diode under a specific set of bias conditions and the transfer or conversion of these noise sources, under different operating conditions including cyclostationary regime, to the quasi-dc output of a mm-wave detector constructed with the same model of diode. The noise analysis is based on a conversion-matrix type formulation, which relates the carrier noisy sidebands of the input signal with the detector output spectrum through a pair of transfer functions obtained in commercial software. Measurements of detectors in individual and differential setups will be presented and compared with predictions.

scholarly journals Data-Driven Modeling of Low Frequency Noise Using Capture-Emission Energy Maps

2020 ◽  
Vol 11 (1) ◽  
pp. 356
Author(s):  
Jonghwan Lee
Keyword(s):  
Noise Analysis ◽  
Low Frequency ◽  
Gaussian Mixture ◽  
Noise Model ◽  
Accurate Estimation ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Noise Sources ◽  
Emission Energy ◽  
Bias Temperature Instability

A new approach for modeling low frequency noise is presented to enable the predictions of noise behavior from negative bias temperature instability (NBTI). The noise model is based on a capture-emission energy (CEE) map describing the probability density function of widely distributed defect capture-emission activation energies. To enlarge the capture-emission energy window and to perform the accurate estimation of the recoverable component of CEE, the Gaussian mixture model (GMM) is applied to the CEE map. This approach provides an efficient identification of noise sources and an in-depth noise analysis under both stationary and cyclo-stationary conditions.

Noise source location and scaling of subsonic upper-surface blowing

2020 ◽  
Vol 19 (3-5) ◽  
pp. 191-206
Author(s):  
Trae L Jennette ◽  
Krish K Ahuja
Keyword(s):  
Strouhal Number ◽  
Noise Source ◽  
Low Frequency ◽  
Directivity Pattern ◽  
Source Location ◽  
Dipole Source ◽  
Frequency Noise ◽  
Noise Sources ◽  
Trailing Edge ◽  
Trailing Edge Noise

This paper deals with the topic of upper surface blowing noise. Using a model-scale rectangular nozzle of an aspect ratio of 10 and a sharp trailing edge, detailed noise contours were acquired with and without a subsonic jet blowing over a flat surface to determine the noise source location as a function of frequency. Additionally, velocity scaling of the upper surface blowing noise was carried out. It was found that the upper surface blowing increases the noise significantly. This is a result of both the trailing edge noise and turbulence downstream of the trailing edge, referred to as wake noise in the paper. It was found that low-frequency noise with a peak Strouhal number of 0.02 originates from the trailing edge whereas the high-frequency noise with the peak in the vicinity of Strouhal number of 0.2 originates near the nozzle exit. Low frequency (low Strouhal number) follows a velocity scaling corresponding to a dipole source where as the high Strouhal numbers as quadrupole sources. The culmination of these two effects is a cardioid-shaped directivity pattern. On the shielded side, the most dominant noise sources were at the trailing edge and in the near wake. The trailing edge mounting geometry also created anomalous acoustic diffraction indicating that not only is the geometry of the edge itself important, but also all geometry near the trailing edge.

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

Noise Mapping ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 129-137
Author(s):  
Giorgio Baldinelli ◽  
Francesco Bianchi ◽  
Danilo Costarelli ◽  
Francesco D’Alessandro ◽  
Flavio Scrucca ◽  
...  
Keyword(s):  
Image Processing ◽  
Noise Source ◽  
Focal Length ◽  
Noise Sources ◽  
Geometric Information ◽  
Industrial Noise ◽  
Sources Identification ◽  
Innovative Technique ◽  
Innovative Techniques

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.

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