Uma Metodologia para a Avaliação Virtual da Dose de Exposição ao Ruído no Ambiente de Trabalho

Abstract

The permanence of people in environments with high noise levels can cause various organic commitments, such as hypertension, stress, increased muscle tension, impaired concentration, and temporary or permanent hearing disorders. The occupational noise induced hearing loss (ONIHL) is the only disease caused by noise recognized by Brazilian law. To evaluate the noise unsoundness in the workplace, the Labor Laws Consolidation in Brazil, in Ordinance 3214, NR- 15, establishes the limits of noise exposure for workers in Brazil, aiming to protect them from hearing damage. This Ordinance by NR-7, establishes the obligation of entrance, periodic and resignation audiometric exams and to establish exposure limits and differentiate impulsive and continuous noise. The Standard Occupational Hygiene NHO 01, 2001 from FUNDACENTRO establishes criteria and procedures for the evaluation of occupational noise exposure, which involves potential risk of occupational deafness. Also introduces the concept of exposure level as a criterion to quantification and characterization of occupational exposure to continuous or intermittent noise, and consider the use of integrators and instantaneous readings. Although it provides a secure evaluation and improve on the working condition of employees, it is evident that the exposure is required to be performed the procedure. Seeking to avoid such exposure, it has been hypothesized to create a system to predict the dose of exposure even before the task execution. It was thus proposed in this work to develop a methodology that utilizes a prior mapping and identification of sources of noise in the workplace beyond the routine work of the employee, to predict the dose of exposure to occupational noise of a given homogeneous group. They were used two algorithms to predict the likelihood that the employee be anywhere in the plant, the first taking into consideration the distance of the official point evaluated and the second by a probabilistic neural network. It was possible using the methodologies created to provide a full assessment, using the mean and the variance resulting from the repeatability of simulations to predict the dose of exposure to occupational noise.