Determining and separating the main frequency of steam exhaust noise from other noise sources in an oil refinery of Iran

Noise exposure is one of the main problems in petroleum industry. Petroleum industry is a strategic industry in Iran with large number of workers whom are exposed to different noise sources. Identification and evaluation of this noise sources and reducing excessive noises are big issues in petroleum industry from point of occupational health. This descriptive-analytic study was performed in the unit control one oil refinery of Iran. The general objectives of this study were to determine the noise pollution، frequency analyzing and to determine the main frequency of steam exhaust in the refinery. Basically، some main information including: draws، noise sources and technical information were gathered in this study. Then the measurement of environmental noise، using meshing method in spread fields of noise sources، was performed. Finally، noise frequency analysis was accomplished to determine the main frequency of desired sound sources and a creative method with four step frequency analyzing was used to investigate and determine the main frequency of main jets. In addition، the main frequency of steam jet was determined and separated based on comparison between the field and mathematical data، using technical emitted noise and steam exhaust characters. The results of environmental survey showed that sound pressure levels were greater than 85 dB (A) as national standard level. Analysis results showed that 4000 Hz is the main frequencies of steam jet. The results of main frequency survey of steam jet regarding technical properties and using calculating method verified the field measurement results. In this study، with use of creative method with four steps noise frequency analysis of steam jet and then was compared results of frequency survey regarding technical properties and using calculating method was characterized that with this method noise properties of jet from other sources separated. Results of this study could be applied to identify and separate noises with different frequencies and sources while are emitting from a same place at same time.