Intensity Of Measurement Noise Research Articles

The effect of noise reduction on work-related stress: a quasi-experimental study on weaving workers exposed to high levels of noise

Introduction: The textile industry is one industry in the world with a high risk in its production process. The operation of weaving machines generates high levels of noise, which can cause various adverse effects on workers' health, especially work-related stress. IT Co. Ltd., one of the largest textile companies in Solo, Central Java, since 1975, has not been able to overcome the problem of the high noise intensity, especially in the weaving production room. Methods: This study aims to determine the effect of reducing noise exposure on work-related stress by installing sound-absorbing materials from coconut fiber waste. The study was carried out in 2 phases. The first phase measured noise intensity and work stress before the intervention. The second phase was carried out for 12 measurements daily after installing sound-absorbing material from coconut fiber waste. Results: Installing sound-absorbing material from the coconut fiber waste on the second to the thirteenth day positively reduced the average noise intensity and work-related stress score compared to the first day before the intervention. Conclusion: The study showed a significant difference in the average noise intensity and work-related stress before and after installing the sound-absorbing materials on 13 days of measurement.

Analysis of noise reduction measures in a noise workshop handover control room

Objective: To explore the sound insulation, sound absorption and other noise reduction transformation methods in a noise workshop handover control room. Methods: In December 2021, through the occupational health investigation and on-site testing of the handover control room of a noise workshop, the causes of excessive noise were analyzed, and the transformation design scheme to reduce noise was proposed and the effect was analyzed. Results: Before the transformation, the peak frequency band noise intensity of the noise workshop handover control room was 112.8 dB (A), and the peak frequency was 1000 Hz. After noise reduction, the theoretical calculated control value was 61.0 dB (A), and the measured noise intensity was 59.8 dB (A) . Conclusion: The noise intensity of the handover control room is reduced after noise reduction, which is in line with the contact limit requirements of the control room in GBZ 1-2010 "Hygienic Standards for the Design of Industrial Enterprises", and has reference significance for noise control engineering.

Optimization of the Course Movement of an Unmanned Vehicle in the Presence of Obstacles and Disturbances

The article discusses the optimization of the control process of an unmanned vehicle. Currently, there is an active development and use of unmanned vehicles. There is a practice of using unmanned shuttles in closed areas (conferences, forums, etc.). The use of cars with automated control in urban conditions and on rough terrain is being tested. In this regard, it is important to develop control algorithms that allow solving problems of car control in real time under the influence of disturbances and the presence of obstacles. With the development of technology and an increase in computing power, it becomes possible to use optimal control algorithms that allow you to achieve better results when the terminal conditions are met, minimizing energy costs. This paper shows the solution of the problem of optimal control of an unmanned vehicle in the presence of a penalty function, measurement noise and disturbances from incomplete data using the separation principle. The problem of optimal control in a deterministic and stochastic setting is solved using an algorithm with a predictive model with a generalized work functional. The effectiveness of applying the Kalman filter is shown depending on the different intensity of measurement noise and different vehicle speeds. The results of numerical modeling are presented, showing the possibility of using the proposed algorithm to control an unmanned vehicle under various initial and final conditions. The developed algorithm has been successfully applied to bypass a moving object.

A Time-Delay Approach to Extremum Seeking with Measurement Noise*

In this paper, we present a time-delay approach to extremum seeking (ES) corrupted by white noise for uncertain static quadratic maps. We first apply a time-delay approach to the ES system and arrive at a neutral type time-delay system with stochastic perturbations. Then we further present the latter system as a retarded one and employ the variation of constants formula for the mean-square exponential ultimate boundedness analysis. Under the assumption that the upper bound of the 6th moment of the estimation error is a known arbitrarily large constant L, explicit conditions in terms of simple scalar inequalities depending on the bound L, tuning parameters and the intensity of measurement noise are established to guarantee the mean-square exponential ultimate boundedness of the ES control systems. Comparatively to the existing results for ES with measurement noise via the qualitative analysis, our approach can provide a quantitative analysis and simplify the stability analysis process as well. A numerical simulation is given to illustrate the efficiency of the proposed method.

Bayesian Nonparametric Learning and Knowledge Transfer for Object Tracking Under Unknown Time-Varying Conditions

We consider the problem of a primary source tracking a moving object under time-varying and unknown noise conditions. We propose two methods that integrate sequential Bayesian filtering with transfer learning to improve tracking performance. Within the transfer learning framework, multiple sources are assumed to perform the same tracking task as the primary source but under different noise conditions. The first method uses Gaussian mixtures to model the measurement distribution, assuming that the measurement noise intensity at the learning sources is fixed and known a priori and the learning and primary sources are simultaneously tracking the same source. The second tracking method uses Dirichlet process mixtures to model noise parameters, assuming that the learning source measurement noise intensity is unknown. As we demonstrate, the use of Bayesian nonparametric learning does not require all sources to track the same object. The learned information can be stored and transferred to the primary source when needed. Using simulations for both high- and low-signal-to-noise ratio conditions, we demonstrate the improved primary tracking performance as the number of learning sources increases.

Modelling of Facial Images for Analysis of Recognition System

Face recognition is categorized as a biometric technology that employs the use of computer ability in image processing to detect and recognize human faces. Face recognition system has numerous applications for many purposes such as for access control, law enforcement and surveillance thus this system is dominant in present technology. Generally, face recognition system become more advance in term of the accuracy and implementation. However, there are a few parameters that effects the accuracy of recognition system for examples, the pose invariant, illumination effect, size of image and noise tolerance. Even though there are a number of systems were already available in the literature, the complete understanding of their performances are relatively limited. This is due to many systems focused on a narrow application band – therefore, a comprehensive analysis are needed in order to understand their performances leading to establishing the conditions for successful face recognition system. In this paper we developed a synthetic model to represent facial images to be used as a platform for performance analysis of facial recognition systems. The model includes 5 face types with the ability to vary all parameters that are affecting recognition performance – measurement noise, face size and face-background intensity differences. The model is important as it provide an avenue for performance analysis of facial recognition systems.

Cubature Ensemble Kalman Filter for Highly Dimensional Strongly Nonlinear Systems

The Ensemble Kalman filter (EnKF) was introduced for highly dimensional systems, but it has poor performance in the presence of strong nonlinearities. The Cubature Kalman filter (CKF) has outstanding performance in strongly nonlinear systems, however, it is limited by high dimensionality. In this work, we provide a comparison between the EnKF and the CKF to elaborate the problems of each scheme in highly dimensional strongly nonlinear systems. To address these problems, we introduce a Cubature Ensemble Kalman filter (CEnKF) that is a combination between both types of filters making it more suitable for highly dimensional strongly nonlinear systems. These algorithms are tested by extensive computer simulations on several models for chaotic dynamical systems. In addition, the computational complexity of the CKF/EnKF/CEnKF is analyzed. Simulation results show that the CEnKF, given a large enough ensemble size, can perform better than the EnKF and CKF for highly dimensional strongly nonlinear systems with high measurement noise intensity. The CEnKF also has better stability than the EnKF, and it performs as good as the CKF with a large enough ensemble size.

Noise exposure of cyclists in Ho Chi Minh City: A spatio-temporal analysis using non-linear models

The auditory and non-auditory effects of noise on health are today well known. A number of studies have recently shown that cyclists represent a population that is especially strongly exposed to noise in urban environments, particularly because of their proximity to road traffic. These studies have however very rarely examined the case of the cities of the South, despite the fact that these cities are known to have higher levels of exposure to noise. The objective of this article is therefore to analyze variations in cyclists’ levels of noise exposure in Ho Chi Minh City (Vietnam) by integrating three dimensions: that is, the characteristics of the trip, neighbourhood effects, and the temporal dimension. Three participants cycled more than 1000 km in the city, equipped with noise dosimeters and GPS watches, for a total of 3300 one-minute segments, each of which measured noise intensity (LAeq dB(A)). It is not surprising that the levels of exposure registered were particularly high (average 78.8 dB(A)), notably compared with earlier studies conducted in Europe and North America. The use of generalized additive models in particular made it possible to highlight the effect of the complex interaction between the slope and the cyclists’ speed on the levels of noise exposure, the effect and duration of the morning and afternoon rush hour periods, and the spatial distribution of residual environmental noise. One of the main findings was that in sectors with the highest levels of exposure to noise (central neighbourhoods or areas near the airport), these levels are up to four times higher than in more peripheral or rural areas.

Effect of Chronic Noise Exposure on Aggressive Behavior of Automotive Industry Workers.

Background: Noise pollution is one of the important harmful physical factors in work environment in developed and developing countries. It not only causes a variety of physiological effects, but also accounts for psychological disorders. Objective: To investigate the effects of chronic exposure to noise on aggression in automotive industry workers. Methods: In a cross-sectional study conducted in an Iranian automotive industry, a group of workers were randomly selected from different parts of the paint shop. The workers' aggression level was measured using the Buss and Perry's questionnaire. The noise level was also measured at the workplace. Using linear regression analysis, the relationship between the level of aggression and noise level was evaluated. Results: 250 workers with a mean age of 36.1 (SD 3.7) years were studied. There was a significant (p<0.05) correlation between the measured noise intensity and the aggression level of the studied workers. Conclusion: Exposure to noise in work environment increases the incidence of tension and inappropriate behavior associated with aggression. Controlling noise through use of protective equipment might reduce the deleterious effects of noise on workers.

Identification of Nonlinear State-Space Systems From Heterogeneous Datasets

This paper proposes a new method to identify nonlinear state-space systems from heterogeneous datasets. The method is described in the context of identifying biochemical/gene networks (i.e., identifying both reaction dynamics and kinetic parameters) from experimental data. Simultaneous integration of various datasets has the potential to yield better performance for system identification. Data collected experimentally typically vary depending on the specific experimental setup and conditions. Typically, heterogeneous data are obtained experimentally through 1) replicate measurements from the same biological system or 2) application of different experimental conditions such as changes/perturbations in biological inductions, temperature, gene knock-out, gene over-expression, etc. We formulate here the identification problem using a Bayesian learning framework that makes use of “sparse group” priors to allow inference of the sparsest model that can explain the whole set of observed heterogeneous data. To enable scale up to large number of features, the resulting nonconvex optimization problem is relaxed to a reweighted Group Lasso problem using a convex–concave procedure. As an illustrative example of the effectiveness of our method, we use it to identify a genetic oscillator (generalized eight species repressilator). Through this example we show that our algorithm outperforms Group Lasso when the number of experiments is increased, even when each single time-series dataset is short. We additionally assess the robustness of our algorithm against noise by varying the intensity of process noise and measurement noise.

Vibration and Noise in Magnetic Resonance Imaging of the Vocal Tract: Differences between Whole-Body and Open-Air Devices.

This article compares open-air and whole-body magnetic resonance imaging (MRI) equipment working with a weak magnetic field as regards the methods of its generation, spectral properties of mechanical vibration and acoustic noise produced by gradient coils during the scanning process, and the measured noise intensity. These devices are used for non-invasive MRI reconstruction of the human vocal tract during phonation with simultaneous speech recording. In this case, the vibration and noise have negative influence on quality of speech signal. Two basic measurement experiments were performed within the paper: mapping sound pressure levels in the MRI device vicinity and picking up vibration and noise signals in the MRI scanning area. Spectral characteristics of these signals are then analyzed statistically and compared visually and numerically.

Comfort and noise level in infants with helmet interface

Abstract Objectives To evaluate comfort and noise intensity using the COMFORT scale in infants who receive respiratory support with a helmet interface. Patients and methods An observational descriptive study was conducted on all infants (1–12 months of age) admitted to a PICU from November 1st 2013 to March 31th 2014 and who received non-invasive ventilation with a helmet interface. Tolerance to the interface was assessed by use of the COMFORT scale. The intensity of the noise to which the infants were exposed was measured with a TES1350A HIBOK 412 sound-level metre. Three measurements were made every day. Results Twenty-seven patients with bronchiolitis (median age: 54 days; range: 10–256) were included. Median COMFORT score in the first day was 21 points (14–28). An increase in patient comfort was found with a gradual decrease in the scores, with a maximum reduction of 22% from the first hours (score of 22) to the fifth day (score of 18). The minimum sound intensity registered was 42 dB, and the maximum was 78 dB. Background noise intensity was associated with noise intensity in the helmet. No differences were observed in COMFORT score and noise intensity between ventilator devices. Conclusions Helmet interface was well tolerated by infants. COMFORT score results are an indicator that infants were comfortable or very comfortable. The measured noise intensity was in the safe range permitted by World Health Organization.

Preliminary Study on Underwater Ambient Noise Generated by Typhoons**Supported by the National Natural Science Foundation of China under Grant No 11125420.

We present a typhoon-generated noise model with which the noise intensity during typhoons can be estimated accurately. The model is verified through experimental study, and the simulation results agree reasonably with the experimental data. The measured noise intensity is approximately proportional to the cube of the local wind speed.

Confort y nivel de ruido en ventilación no invasiva con interfase helmet en lactantes

ObjectivesTo evaluate comfort and noise intensity using the COMFORT scale in infants who receive respiratory support with a helmet interface. Patients and methodsAn observational descriptive study was conducted on all infants (1 to 12 months of age) admitted to a PICU from November 1st 2013 to March 31th 2014 and who received non-invasive ventilation with a helmet interface. Tolerance to the interface was assessed by use of the COMFORT scale. The intensity of the noise to which the infants were exposed was measured with a TES1350A HIBOK 412 sound-level meter. Three measurements were made every day. ResultsTwenty seven patients with bronchiolitis (median age: 54 days; range: 10 to 256) were included. Median COMFORT score in the first day was 21 points (14 - 28). An increase in patient comfort was found with a gradual decrease in the scores, with a maximum reduction of 22% from the first hours (score of 22) to the fifth day (score of 18). The minimum sound intensity registered was 42dB, and the maximum was 78dB. Background noise intensity was associated with noise intensity in the helmet. No differences were observed in COMFORT score and noise intensity between ventilator devices. ConclusionsHelmet interface was well tolerated by infants. COMFORT score results are an indicator that infants were comfortable or very comfortable. The measured noise intensity was in the safe range permitted by World Health Organization.

Detection on Structural Sudden Damage Using Continuous Wavelet Transform and Lipschitz Exponent

The degradation of civil engineering structures may lead to a sudden stiffness reduction in a structure and such a sudden damage will cause a discontinuity in the dynamic responses. The detection on structural sudden damage has been actively carried out in this study. The signal singularity of the acceleration responses with sudden stiffness reduction is characterized by the coefficients of continuous wavelet transform with fine scales. A detection approach based on the CWT is proposed in terms of the decomposed detail coefficients of continuous wavelet transform to detect the damage time instant and location. The Lipschitz exponent is mathematically used to estimate the local properties of certain function and is applied to reflect the damage severity. Numerical simulation using a five-story shear building under different types of excitation is carried out to assess the validity of the proposed detection approach for the building at different damage levels. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also investigated. The effects of both measurement noise intensity and frequency range on the damage detection are numerically investigated.

Damage Detection on Sudden Stiffness Reduction Based on Discrete Wavelet Transform

The sudden stiffness reduction in a structure may cause the signal discontinuity in the acceleration responses close to the damage location at the damage time instant. To this end, the damage detection on sudden stiffness reduction of building structures has been actively investigated in this study. The signal discontinuity of the structural acceleration responses of an example building is extracted based on the discrete wavelet transform. It is proved that the variation of the first level detail coefficients of the wavelet transform at damage instant is linearly proportional to the magnitude of the stiffness reduction. A new damage index is proposed and implemented to detect the damage time instant, location, and severity of a structure due to a sudden change of structural stiffness. Numerical simulation using a five-story shear building under different types of excitation is carried out to assess the effectiveness and reliability of the proposed damage index for the building at different damage levels. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also investigated. The made observations demonstrate that the proposed damage index can accurately identify the sudden damage events if the noise intensity is limited.

Estimation of Receiver Aircraft States and Wind Vectors in Aerial Refueling

A square root unscented Kalman filter is used to estimate the states of a receiver aircraft and the components of the wind the aircraft is exposed to as it flies behind the tanker aircraft. The wind is the superposition of time-varying prevailing wind, turbulence, and the tanker’s wake-induced wind. The system update of the estimator uses the nonlinear aircraft model, augmented by a nonlinear wind model, obtained from the translational dynamics of the aircraft. The aircraft state estimates are successfully used in controlling the position of the receiver aircraft relative to the tanker flying straight level and making turns. Although the performance of the estimation and control is very dependent on the covariance and correlation time constants of the sensor measurement errors, the estimated state feedback performs better than measured state feedback with higher levels of measurement noise and turbulence intensity.

Estimating interdependences in networks of weakly coupled deterministic systems

The extraction of information from measured data about the interactions taking place in a network of systems is a key topic in modern applied sciences. This topic has been traditionally addressed by considering bivariate time series, providing methods which are sometimes difficult to extend to multivariate data, the limiting factor being the computational complexity. Here, we present a computationally viable method based on black-box modeling which, while theoretically applicable only when a deterministic hypothesis about the processes behind the recordings is plausible, proves to work also when this assumption is severely affected. Conceptually, the method is very simple and is composed of three independent steps: in the first step a state-space reconstruction is performed separately on each measured signal; in the second step, a local model, i.e., a nonlinear dynamical system, is fitted separately on each (reconstructed) measured signal; afterward, a linear model of the dynamical interactions is obtained by cross-relating the (reconstructed) measured variables to the dynamics unexplained by the local models. The method is successfully validated on numerically generated data. An assessment of its sensitivity to data length and modeling and measurement noise intensity, and of its applicability to large-scale systems, is also provided.

Exposure to noise during continuous positive airway pressure: influence of interfaces and delivery systems

We measured noise intensity and perceived noisiness during continuous positive airway pressure (CPAP) performed with two interfaces (face-mask, helmet) and four delivery systems. Eight healthy volunteers received CPAP in random order with: two systems provided with a flow generator using the Venturi effect and a mechanical expiratory valve (A: Venturi, Starmed; B: Whisperflow-2, Caradyne Ltd); one 'free-flow' system provided with high flow O(2) and air flowmeters, an inspiratory gas reservoir, and a water valve (C: CF800, Drägerwerk, AG); and a standard mechanical ventilator (Servoventilator 300, Siemens-Elema). Systems A, B, and C were tested with a face-mask and a helmet at a CPAP value of 10 cm H(2)O; the mechanical ventilator was only tested with the face mask. Noise intensity was measured with a sound-level meter. After each test, participants scored noisiness on a visual analog scale (VAS). The noise levels measured ranged from 57+/-11 dBA (mechanical ventilator plus mask) to 93+/-1 and 94+/-2 dBA (systems A and B plus helmet) and were significantly affected by CPAP systems (A and B noisier than C and D) and interfaces (helmet CPAP noisier than mask CPAP). Subjective evaluation showed that systems A and B plus helmet were perceived as noisier than system C plus mask or helmet. Maximum noise levels observed in this study may potentially cause patient discomfort. Less noisy CPAP systems (not using Venturi effect) and interfaces (facial mask better than helmet) should be preferred, particularly for long or nocturnal treatments.

A new damage index for detecting sudden change of structural stiffness

A sudden change of stiffness in a structure, associated with the events such as weld fracture and brace breakage, will cause a discontinuity in acceleration response time histories recorded in the vicinity of damage location at damage time instant. A new damage index is proposed and implemented in this paper to detect the damage time instant, location, and severity of a structure due to a sudden change of structural stiffness. The proposed damage index is suitable for online structural health monitoring applications. It can also be used in conjunction with the empirical mode decomposition (EMD) for damage detection without using the intermittency check. Numerical simulation using a five-story shear building under different types of excitation is executed to assess the effectiveness and reliability of the proposed damage index and damage detection approach for the building at different damage levels. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also examined. The results from this study demonstrate that the damage index and damage detection approach proposed can accurately identify the damage time instant and location in the building due to a sudden loss of stiffness if measurement noise is below a certain level. The relation between the damage severity and the proposed damage index is linear. The wavelet-transform (WT) and the EMD with intermittency check are also applied to the same building for the comparison of detection efficiency between the proposed approach, the WT and the EMD.