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Enregistrement W2002142209 · doi:10.4103/1463-1741.40824

Occupational noise in rice mills

2008· article· en· W2002142209 sur OpenAlex
Prasanna Kumar, K.N. Dewangan, Amaresh Sarkar, Amrita Kumari, Banani Kar

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Notice bibliographique

RevueNoise and Health · 2008
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiquePlant and Biological Electrophysiology Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMillNoise (video)Environmental sciencePulp and paper industryEngineeringComputer science

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: A major occupational hazard for the workers in rice mills is the noise during the operation of various machines. A noise survey was conducted in the workrooms of eight renowned rice mills of the north-eastern region of India established during the period between 1980 and 1985. The rice mills were selected on the basis of the outcome of a walk-through noise survey involving several rice mills of the region. A noise survey map of each rice mill was drawn to identify the predominant noise sources and the causes of high noise in the workrooms of the rice mill. The sound-pressure level (SPL) in the workrooms of the rice mill varied from 78 to 92 dBA. The paddy cleaner, rubber roll sheller, compartment separator, rice cleaner, auxiliary sieve shaker and an electric motor without enclosure were found to be the predominant noise sources in the workrooms of the mill. The causes of high noise in the rice mills may be attributed to the use of a long flat belt drive, crank-and-pitman mechanism, absence of an electric motor enclosure, poor machine maintenance and inadequate acoustic design of the workroom of the rice mill. About 26% of the total labourers were found to be exposed to higher levels of noise than 85 dBA. Subjective response indicated that about 26% of the total labourers felt noise interferes in their work and about 49% labourers were of opinion that noise interferes with their conversation. CONTEXT: Noise from machines in the rice mills was found to be the major occupational hazard for the rice mill workers. The predominant noise sources need to be identified and the causes of high noise need to be studied to undertake the appropriate measures to reduce the noise level. AIMS: To identify the predominant noise sources and their distributions in rice mills, to study the causes of high levels of noise in rice mills and to examine the response of the workers towards noise. SETTINGS AND DESIGN: A noise survey was conducted in eight renowned rice mills of the north-eastern region of India. The mills were selected based on a walk-through survey conducted for the identification of rice mills with high noise. A noise survey map of each rice mill was collected by following the guidelines of Canadian Centre for Occupational Health and Safety (CCOHS). The distribution of high noise in rice mills was studied and the causes of high noise were identified. The subjective response to noise in rice mills was assessed by conducting personal interview with all the workers of the rice mills using a structured form. METHODS AND MATERIAL: The guidelines of CCOHS were followed during the noise survey. A sound level meter (SLM; Model-824) was used to record the noise level at each grid point marked at 1 m x 1 m. SPL in weighting scale "A" and the noise spectrum were recorded at each grid point for 30 s and data were stored in SLM. A noise survey map of equivalent SPL was drawn for each rice mill by drawing contour lines on the sketch of the rice mill between the points of equal SPL. The floor area in the rice mill where SPL exceeded 85 dBA was identified from the noise survey map of each rice mill to determine the causes of high levels of noise. In order to study the variation in SPL in the workroom of the rice mill throughout the shift, equivalent SPL was measured at six locations in each rice mill. The subjective response to noise in rice mills was assessed by conducting personal interview with all the workers of the rice mills using a structured form. Demographic information, nature of work, working hours, rest period, experience of working in mill, degree of noise annoyance, activity interference, and psychological and physiological effects of machine noise on the worker were asked during the interview. STATISTICAL ANALYSIS USED: Nil. RESULTS: The noise survey in eight select rice mills of the major paddy-growing regions of India revealed that the workrooms of five rice mills had SPL more than 85 dBA in the locations where workers were engaged for most of the time. The predominant noise sources in the rice mills were paddy cleaner, rubber roll sheller, compartment separator, rice cleaner, sieve shaker and an electric motor without enclosure. The causes of high noise in the rice mills may be due to the use of a long flat belt drive, crank-and-pitman mechanism, absence of an electric motor enclosure, poor machine maintenance and inadequate acoustic design of the workroom in the rice mill. In general, a well-maintained rice mill with each machine being run individually using an electric motor produced less noise than that being run using a single electric motor along with flat belt drives. The normal working period in the rice mill was 48 h/week and it was 56 h/week during the peak season of rice milling. About 26% of the total workers were exposed to noise of more than 85 dBA. Subjective response indicated that about 26% of the total workers felt noise interferes in their work and about 49% workers were of opinion that noise interferes with their conversation. CONCLUSIONS: The workers in the rice mills are exposed to high noise, which will have detrimental effect on their health. Apart from undertaking appropriate noise control measures, preventive maintenance of machines needs to be given due importance in all the rice mills.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,195
Score d'incertitude au seuil0,188

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,067
Tête enseignante GPT0,280
Écart entre enseignants0,214 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle