GMI low frequency noise characterization versus wire diameters

Low-frequency equivalent magnetic noise levels of four different giant magneto-impedance (GMI) samples, exhibiting $1/f$ spectral behavior, have been experimentally determined, for several excitation conditions (involving both dc current and ac excitation amplitude). Under appropriate conditions, for which the noise level at 1 Hz is minimal, coherence measurements show that the main noise source responsible for this low frequency noise is the intrinsic noise of the GMI sample. The lowest corresponding magnetic noise performances of the four samples were determined. The lowest noise level observed was $17\,\textrm {pT}/(\textrm {Hz})^{1/2}$ at 1 Hz. It has been proposed that the imaginary part of the magnetic susceptibility, $\chi ^{\prime \prime }$ , a measure of the low frequency magnetization fluctuations, determines the resulting magnetic noise level of the sensor. Its values at 1 Hz have been been evaluated for all four samples. Using these evaluations, expected noise levels at 1 Hz are computed, based on a previously proposed theoretical model, and compared with the measured noise performances. Under conditions for which correlation measurements show that system noise is dominated by sensor noise, the two sets of values are in reasonably good agreement, suggesting that the proposed model for low frequency excess noise of GMI materials is essentially correct.

International audience

In this article, we study magnetic field sensors based on the delta-E effect occurring in a magnetostrictive layer coupled to a piezoelectric resonator. The sensors consist in suspended beams that essentially vary in the bounded conditions at the edges. We examine a clamped-free and a double-clamped sensor. A finite-element model (FEM) is implemented and validated versus published experimental measurements. The latter are considered as reference results. A Butterworth–Van Dyke (BVD) model is also given in each case. The performances of these two types of resonators are pointed out and compared, especially in terms of sensitivity and equivalent magnetic noise level. The given approach gives the way of sensor optimization.

Living in cities, people are faced with various problems that arise in everyday life. One of the most harmful problems that causes diseases in humans is noise pollution. The growing noise pollution of the big city also causes a lot of troubles to the citizens, negatively affects their health and mental condition. With the development of all types of transport, intensive construction, noise loads per person increase, causing its annoyance, mental imbalance, insomnia and, as a consequence, cardiovascular and mental illness. Now, in the streets of Kyiv in many regions, noise sometimes reaches 80-90 in the daytime, and 50-60 decibels at night, which is not a normal phenomenon. So, it was decided to find a site where noise would exceed the norm, and the main source of its nature would be the railroad.Having conducted experimental research on this section of the railway, noise levels were determined. Consequently, the equivalent noise level is 61 dBA, equivalent to the noise level of the flow of trains was 64 dBa, the maximum noise figure recorded in this section was 85 dBA. This experiment was conducted at night with the greatest intensity of trains. So, as the standard (DBN 360-92), the equivalent noise level in the period from 23 h - 7 h should not exceed 45 dBA, and the maximum noise level should not exceed 60 dBA. So we see a significant deviation from the norms, so you need to develop methods to combat noise. Since the selected site was densely built up, which made it impossible to combat noise by the method of forest plantations, so this issue was solved by establishing appropriate noise protection structures that would operate on different sources. Knowing that the noise arises not only from the rumble of the tractor of our tractor train, but also the rattle of the wheels on the track and the flow of air of the train body. So, to reduce noise, you need to consider all these sources.Consequently, in order to reduce the noise caused by rolling the wheel along the track, it was proposed to install road dampers and liners that reduce noise to 10 dB. And to reduce the noise already in the air, it is proposed to install noise protection screens of a height of at least 2m, which allows to reduce the noise level by another 15 dBA. Execution of these conditions will allow us to reduce the noise level in this area by 16 - 20 dBA. (the equivalent noise level should be reduced to 41-45 dBA).Consequently, this experimental study carried out showed us the need to carry out such experiments not only along the whole railway connection of the city of Kyiv or other cities of Ukraine, but also measurements on automobile or ship solutions or construction sites. This will detect problem areas, and depending on the source of noise, fight with them to improve the noise background. And this, in turn, will have a positive effect on the psychological state of man.So let's make a world in which we live better!

For decades, high-impedance and low-frequency readout electronics with the lowest noise level is based on silicon JFETs (Junction Field-Effect Transistors) with an equivalent input noise voltage level of about 1 nV/Hz1/2 at 1 kHz. But their operating temperature is limited to be higher than 100 K due to their intrinsic structure. It is well known that HEMTs (High Electron Mobility Transistors) are intrinsically available for very low temperature operation, but conventional HEMTs suffer high gate leakage current and large channel low-frequency noise under cryogenic condition. In order to overcome these two major issues, we have extensively investigated the conventional HEMTs at 4.2 K by the bias-cooling method. At a given working point, the dependence of the channel low-frequency noise on the gate leakage current has been found out and this has allowed us to devise a new transistor structure. Specific AlGaAs/GaAs HEMTs have then been fabricated. At 4.2 K, our HEMTs can attain a noise level lower than 0.8 nV/Hz1/2 at 1k Hz with an intrinsic gain Aint of 26 and an input gate-source capacitance of 46 pF, and their gate leakage current can be limited about 1 pA This result shows that our specific HEMTs may be a suitable transistor for future ultra-low noise deep cryogenic high-impedance and low-frequency readout electronics.

Environmental noise is a significant public health issue, particularly in rapidly urbanizing cities where commercial activities contribute to elevated noise pollution. Despite its numerous implications, few studies have focused on noise levels in commercial environments in developing countries. This study aims to fill this existing gap by assessing background noise levels in four commercial areas of Freetown, Sierra Leone: Aberdeen Market, Godrich Street, Jui Junction, and Sani Abacha Street. Using a calibrated handheld sound level meter, measurements were taken during daytime, evening, and nighttime periods over one week. Noise levels were analyzed using the day-evening-night equivalent continuous noise level (Lden) and statistical methods to assess compliance with World Health Organization (WHO) guidelines. Results revealed that all areas exhibit average noise levels above the WHO recommended limit of 70 dBA during daytime and evening hours, with Godrich Street and Aberdeen Market exhibiting the highest average daytime noise level (95.35 dBA) and the lowest average nighttime noise level (53.05 dBA) respectively. Godrich Street recorded the highest Lden value and shortest allowed exposure of 93.34 dBA and 1.17 hours respectively, indicating the most significant risk of prolonged exposure. Recommendations include creating designated quiet zones tailored to local commercial layouts, stricter enforcement of noise regulations, public awareness campaigns on hearing protection, and regular noise monitoring to guide urban planning. This study provides crucial insights for mitigating noise pollution and improving urban sustainability in developing nations.

The Noise Levels database has been developed at the Canadian Centre for Occupational Health and Safety for the computerized information system, CCINFO. The database documents measured noise levels from a broad spectrum of industrial settings. Industrial hygienists, noise control engineers, researchers, health and safety committee members, and appropriate government agency personnel are the main intended audience. Noise Levels is a textual‐numeric ‘source’ database of direct measurements, although bibliographic citations are also provided. The data for Noise Levels is gathered from both published and unpublished sources. Each record provides explicit information on the noise source (for example, piece of equipment), the industry, operation associated with the noise production, and the occupational categories. Additional information is provided on the type of noise, exposure duration per day, the presence of engineering controls, and the use of ear protection. Measurement data consists of one or more of the following: Sound Pressure Level (SPL) in dB(A), Time Weighted Average (TWA), Equivalent Continuous Noise Level (ECNL), and the octave band analysis. The primary goals of the database are to encourage sharing of industrial noise data and to promote standardized reporting of noise measurements.

This study indicates the utilization of two Machine learning models that is Artificial Neural Network (ANN) and Random Forest(RF), for the prediction of equivalent noise levels (Leq), across four locations covering commercial and silent zones in Yanam, Puducherry. The total Passenger Car Unit (PCU) data, observed Leq of every location was used effectively for the training and testing of the ANN model, resulting in aCoefficient of Determination (R²) value of 0.912.Additionally, a Random Forest regression model was applied for performance comparison, with a result of an R² of 0.925.The noise maps on weekdays and Sunday revealed the highest and the lowest noise levels at the locations during the 12 hour time interval. The study indicates that the noise levels are proportional to traffic volume, highlighting the need to implement effective strategies for reducing noise pollution in the area.

This study investigates the acoustic conditions of a design studio (Studio 130) in the Department of Interior Architecture and Environmental Design at Afyon Kocatepe University by integrating 14 weeks of continuous noise measurements with perception data collected from 192 students. Noise measurements were conducted in accordance with ISO 3382-3:2022 guidelines at three locations—window front, door side, and studio midpoint—during morning, noon, and evening periods, with 10 min recordings at each session. The results indicate that when students were present, the equivalent continuous noise level (Leq) reached an average of 65.5 dB(A), with peak levels rising to 72.3 dB(A) during jury sessions. These values substantially exceed the recommended 35 dB(A) classroom threshold by the World Health Organization and the 35–45 dB(A) limits specified in national regulations for indoor educational spaces. Survey findings reveal that 88% of students experienced loss of concentration, 72% reported decreased productivity, 60% had difficulty communicating, and 52% reported fatigue due to noise exposure. Pearson correlation analysis demonstrated a strong relationship between measured noise levels and reported negative effects (r = 0.966). Moreover, independent samples t-test results confirmed that student presence significantly increased studio noise levels (t = 4.98, p < 0.001). The novelty of this research lies in its combined use of longitudinal objective measurements and subjective perception data, addressing the unique open-plan, collaborative, and critique-based pedagogical structure of design studios. The findings highlight that acoustic comfort is a critical component of learning quality in studio-based education. Based on the results, the study proposes several design and material interventions—including spatial dividers, acoustic ceiling panels, fabric-wrapped absorbers, and impact-reducing flooring—to enhance auditory comfort. Overall, the study emphasizes the necessity of integrating acoustic design strategies into studio pedagogy to support concentration, communication, and learning performance.

Present work was carried out to collect primary data from the field with the help of noise meter and thus spatial anddiurnal variation of background and aircraft noise level was analyzed. Seventeen sampling sites were chosennearby Tribhuwan International Airport (TIA) and air route of aircraft flyover. Noise measurements were carried outunder normal atmospheric environmental condition at temperature ranges from 25°C-30°C excluding rainy andwindy days. Among the sampling sites, the Equivalent Continuous Noise Level (LAeq) of background noise measuredmaximum at Balkumari (73.2 dBA) and minimum at Datidol (49.2 dBA). Noise meter was allowed to record aircraftnoise level when aircraft produced noise greater than background noise level and recorded until it reduced tobackground noise level. The maximum value of aircraft noise level, (LAeq) measured at Gothatar (101.5 dBA) whichlies north east from the TIA and at the same height as the airport ground and minimum at Datidol (63.5 dBA).Toanalyse the spatial variation of aircraft noise of different sampling sites, contour map was plotted with the help oforigin software. The LAeq of more than 60 percent sampling sites fall under the severe noise exposure class (> 75dBA) which causes substantial hearing loss. Implementation of noise control measurement and public awarenessare recommended to control adverse effect of noise pollution.DOI: http://dx.doi.org/10.3126/njst.v15i1.12031Nepal Journal of Science and TechnologyVol. 15, No.1 (2014) 139-144

In Vilnius and in other bigger towns the noise generated by mobile sources accounts for up to 90 % of the total noise level in a town. A high noise level is detected at motor vehicle parking lots. To measure this noise level, testing was carried out at guarded parking lots which were divided into certain types. One lot of each type was chosen for testing. The number of measuring spots was conditioned by the size of a lot. The data obtained during testing reveal that the highest noise level is generated not at a parking lot but on a nearby street. Such conclusions are proved by the results of testing carried out at a parking lot on E. Sugihara street. Although this lot parks over 100 vehicles, the equivalent noise level is 47 dBA. Basing on the testing data, the numeral simulation of the noise dispersion in areas in the vicinity of parking lots has been run with the help of the numeral simulation software IMMI.

Noise level in the surroundings of traffic routes mainly depends from traffic volume, flow composition, speed of the vehicles as well as from the cross-section and road longitudinal gradient. Under higher speeds significant influence on the noise level has also tyre/road noise. Tyre/road noise depends on type and pavement condition state, specifically from the surface macrotexture. The influence of macrotexture is varying and strictly connected with the type of vehicles, tyres characteristics, frequencies of emitted noise. On the base of investigations of the rolling noise applying Statistical Pass-By method along the Polish roads the paper presents elaborated dependences and fixed values of differences between maximum noise levels under passing multiple-axle heavy vehicle and passenger car on the asphalt concrete surface, stone mastic asphalt and the surface dressing. The functional dependences between maximum rolling noise levels in the range of complete level and in the octave band spectra: 250 Hz, 500 Hz, 1000 Hz, 2000 Hz and 4000 Hz and between the surface macrotexture described by mean profile depth, and logarithm of vehicle speed and adequate nomograms were evaluated in the paper. On this base the values of differences in the levels of emitted noise from passing heavy vehicle and passenger car in function of speed and surface macrotexture were computed. The manuscript also presents how surface macrotexture and traffic flow composition have influence on equivalent noise level in the road vicinity under equal traffic volume.

This paper presents the results obtained from environmental noise measurement at selected locations in Ilorin metropolis. Forty-two (42) different locations throughout Ilorin were selected to establish background noise level and dominant noise sources at these selected locations. Noise level measurements and analysis for the locations were based on the noise descriptors LAeq, L1, L10, L50, L90, and LD. The results from comparative study indicated that the equivalent noise level (LAeq) and peak noise level (L1) have the highest and lowest values at road junctions/busy roads (86 dBA, 88 dBA) and low density residential areas (46 dBA, 63 dBA) respectively. The background noise level (L90) has the highest and lowest values at passengers loading parks (73 dBA) and low density residential areas (34 dBA) respectively. The result of this study shows that the major source of noise in Ilorin metropolis can be attributed to traffic noise. Other intrusive noise sources include noise from record player, electric generators, and hawking with loud speakers. Based on the recommendations of CEOH, WHO and HUD, only 6 locations out of 42 are under normally acceptable situation while the noise levels of other areas are not acceptable. Noting the noise emission standards, technical control measures, planning and promoting the citizens awareness about the high noise risk may help relieve noise problem in the metropolis. These data are useful as reference and guideline for future regulations on noise limit to be implemented for urban areas in Nigeria

BackgroundInformation transmission and processing in the nervous system has stochastic nature. Multiple factors contribute to neuronal trial-to-trial variability. Noise and variations are introduced by the processes at the molecular and cellular level (thermal noise, channel current noise, membrane potential variations, biochemical and diffusion noise at synapses etc). The stochastic processes are affected by different physical (temperature, electromagnetic field) and chemical (drugs) factors. The aim of this study was experimental investigation of hypotheses that increase in the noise level in the brain affects processing of visual information. Change in the noise level was introduced by an external factor producing excess noise in the brain.MethodsAn exposure to 450 MHz low-frequency modulated microwave radiation was applied to generate excess noise. Such exposure has been shown to increase diffusion, alter membrane resting potential, gating variables and intracellular Calcium efflux. Nine healthy volunteers passed the experimental protocol at the lower (without microwave) and the higher (with microwave) noise level. Two photos (visual stimuli) of unfamiliar, young male faces were presented to the subjects, one picture after another. The task was to identify later the photos from a group of six photos and to decide in which order they were presented. Each subject had a total of eight sessions at the lower and eight at the higher noise level. Each session consisted of 50 trials; altogether a subject made 800 trials, 400 at the lower and 400 at the higher noise level. Student t-test was applied for statistical evaluation of the results.ResultsCorrect recognition of both stimuli in the right order was better at the lower noise level. All the subjects under investigation showed higher numbers of right answers in trials at the lower noise level. Average number of correct answers from n=400 trials with microwave exposure was 50.3, without exposure 54.4, difference 7.5%, p<0.002. No difference between results at the lower and the higher noise level was revealed in the case of only partly correct or incorrect answers.ConclusionsOur experimental results showed that introduced excess noise reduced significantly ability of the nervous system in correct processing of visual information.

The equivalent magnetic noise spectral density of giant magnetoimpedance (GMI)-based sensors exhibits a low-frequency excess noise inversely proportional to the frequency (1/f noise). In order to enhance the performance and reach the ultimate and intrinsic limit of the magnetometer, it is necessary to investigate the origin of this excess noise. Cross correlation measurements have permitted the demonstration that the excess low-frequency noise arises from the sensor, under defined excitation conditions, particularly the amplitude of the excitation current and the dc bias current. Given that the GMI effect is based on an impedance variation governed by the magnetization direction under an applied external magnetic field, the low-frequency magnetization fluctuations within the GMI wire have been considered to be a possible noise source. The fluctuation-dissipation theorem permits evaluation of the spectral power density of these fluctuations, which is proportional to the imaginary part of the susceptibility, $\chi ^{\prime \prime }$ . The latter may be evaluated by two different methods, based on the measurement of the real part of the wire impedance and on the evaluation of the circumferential hysteresis loop area. The results obtained by both methods are compared and discussed. The values of $\chi ^{\prime \prime }$ thus obtained are then used in order to predict the equivalent magnetic noise level at 1 Hz, and are compared with that measured at 1 Hz. The comparison is conducted for different amplitudes of the dc bias current, and the results obtained indicate that the proposed methods have the potential of predicting the excess noise in GMI sensors.