Identification and analysis of noise sources in the Noor-Abad gas compressor station, Iran

The objective of this study is to identify the sources of acoustic noise (noise pollution) in the Noor-Abad gas compressor station and then to prioritize the station equipment based on noise pollution. First, the key locations inside the station as well as in the surrounding residential area, aka the study area, are determined for the measurement of sound pressure level. Then, the sound pressure level is measured at those points, and the related noise map is produced. Based on the noise map, the noise condition in the study area is evaluated by comparing the measured acoustic parameters with allowable standard values. Dangerous regions and critical points are thus identified. The major noise sources consist of main blowdown, units’ blowdowns, scrubbers, and turbo-compressors. The sound pressure level of main blowdown is measured at two intervals from its position: 80 m inside the station and 600 m outside the station (at the edge of the surrounding residential area). Also, the sound pressure level for a unit blowdown and a scrubber is measured at respectively 25 m and 40 m from their positions. Finally, the station equipment is prioritized based on noise pollution. The analysis of measurement results showed that the main noise sources are, respectively, the station main blowdown, units’ scrubbers, units’ blowdowns, turbo-compressors, and gas pipelines.

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Status of noise pollution in urban area of Dharan Sub- Metropolitan City and Inaruwa Municipality of Sunsari District, Nepal

Nepalese Journal of Biosciences ◽

10.3126/njbs.v7i1.41760 ◽

2017 ◽

Vol 7 (1) ◽

pp. 35-40

Author(s):

Ranij Shrestha ◽

Alankar Kafle ◽

Kul Prasad Limbu

Keyword(s):

Sound Pressure Level ◽

Sound Pressure ◽

Pollution Assessment ◽

Noise Pollution ◽

Pressure Level ◽

Noise Levels ◽

Night Time ◽

Level Measurement ◽

Standard Value ◽

Autumn And Winter

The environmental noise level measurement in Dharan and Inaruwa cities of eastern Nepal were conducted and compared with the ambient noise standards provided by Government of Nepal. The noise pollution assessment was performed in autumn and winter seasons by the indicator average day time sound pressure level (Ld, during 7.00 to 22.00 hrs) and average night time sound pressure level (Ln, during 22.00 to 7.00 hrs). The Ld and Ln values at the commercial, silence and residential zones of Dharan were 78 to 82 and 72 to 73, 65 to 73 and 60 to 70, 65 to 76 and 62 to 64 dB(A) in autumn and 78 to 79 and 72 to 76, 64 to 71 and 58 to 68, 63 to 74 and 60 to 62 dB(A) in winter, respectively whereas for Inaruwa, measurement were 75 to 77 and 73 to 75, 59 and 57, 67 and 60 dB(A) in autumn and 66 to 70 and 63 to 68, 55 and 53, 65 and 58 dB(A) in winter, respectively. The results showed that noise levels exceeded the standard value at most of the sites.

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Investigation of Noise Pollution Distribution in Different Parts of Yazd Textile Factories

Archives of Occupational Health ◽

10.18502/aoh.v5i2.6195 ◽

2021 ◽

Author(s):

Mohammad Javad Zare Sakhvidi ◽

Hamideh Bidel ◽

Ahmad Ali Kheirandish

Keyword(s):

Occupational Exposure ◽

Sound Pressure Level ◽

Textile Industry ◽

Sound Pressure ◽

Noise Pollution ◽

Sound Level ◽

Pressure Level ◽

Cross Sectional ◽

Sound Pressure Levels ◽

Different Parts

Background: Chronic occupational exposure to noise is an unavoidable reality in the country's textile industry and even other countries. The aim of this study was to compare the sound pressure level in different parts of the textile industry in Yazd and in different parts of the textile industry. Methods: This cross-sectional study was performed on 930 textile workers in Yazd. A questionnaire was used to obtain demographic information and how to use protective equipment. Then, to obtain the sound pressure level of each unit and device and to use the measurement principles, a calibrated sound level meter was used. Then the results were analyzed using SPSS Ver.29 software. Results: The participants in this study were 714 males and 216 females with a mean age of 35.27 and 33.63 years, respectively. Seven hundred fifty-six participants (81.29%) were exposed to sound pressure levels higher than 85 dB. Among the participants, only 18.39% of the people used a protective phone permanently. Except for factory E, with an average sound pressure level of 77.78 dB, the rest of the factories had an average sound pressure level higher than the occupational exposure limit. The sound measurement results of different devices show that the sound pressure levels above 90 dB are related to the parts of Dolatab, Ring, Kinetting (knitting), Chanel, Autoconer, Dolakni, Open End, MultiLakni, Tabandegi, Texture, and Poy. Conclusion: Based on the results of the present study, noise above 90 dB is considered as one of the main risk factors in most parts of the textile industry (spinning and weaving), which in the absence of engineering, managerial or individual controls on it causes hearing loss in becoming employees of this industry

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Variation in vibro-acoustic noise due to the defects in an automotive drum brake

INTER-NOISE and NOISE-CON Congress and Conference Proceedings ◽

10.3397/in-2021-2192 ◽

2021 ◽

Vol 263 (4) ◽

pp. 2646-2653

Author(s):

Ananthapadmanabhan Ramesh ◽

Sundar Sriram

Keyword(s):

Analytical Model ◽

Sound Pressure Level ◽

Sound Pressure ◽

Transfer Functions ◽

Acoustic Noise ◽

Pressure Level ◽

Acoustic Model ◽

Drum Brake ◽

Non Linear ◽

Sound Pressure Levels

Drum brakes are significant contributors to noise and vibration in automobiles causing discomfort to the passengers. The vibration and hence the resulting noise increase due to various inherent defects in the drum brake, such as asymmetry. This work aims to quantify the variation in the vibro-acoustic noise due to several common defects in the drum brake using an integrated non-linear vibration analytical model and a numerical acoustic model. The sources of vibro-acoustic noise sources such as contact and reaction forces are predicted using a four-degree-of-freedom non-linear contact mechanics based analytical model. A finite element based acoustic model of the drum brake is utilized to predict the force to the sound pressure transfer function in the drum brake. Product of the transfer functions and the forces gives the corresponding sound pressure level from which the overall sound pressure levels are estimated. The variation in the overall sound pressure levels due to different drum brake defects is evaluated by introducing defects to the analytical model. The results show that the overall sound pressure level is a strong function of the defects. It is envisioned that the current work will help in the development of effective health monitoring systems.

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Reducing the harmful effects of noise on the human environment. Sound insulation of industrial skeleton enclosures in the 10–40 kHz frequency range

Journal of Environmental Health Science and Engineering ◽

10.1007/s40201-020-00560-2 ◽

2020 ◽

Vol 18 (2) ◽

pp. 1451-1463

Author(s):

Witold Mikulski

Keyword(s):

Sound Pressure Level ◽

Sound Pressure ◽

Sheet Steel ◽

Pressure Level ◽

Sound Insulation ◽

Frequency Range ◽

Noise Sources ◽

Human Environment ◽

Absorbing Material ◽

Acoustic Enclosures

Abstract Purpose The purpose of the research is to work out a method for determining the sound insulation of acoustic enclosures for industrial sources emitting noise in the frequency range of 10–40 kHz and apply the method to measure the sound insulation of acoustic enclosures build of different materials. Methods The method is developed by appropriate adaptation of techniques applicable currently for sound frequencies of up to 10 kHz. The sound insulation of example enclosures is determined with the use of this newly developed method. Results The research results indicate that enclosures (made of polycarbonate, plexiglass, sheet aluminium, sheet steel, plywood, and composite materials) enable reducing the sound pressure level in the environment for the frequency of 10 kHz by 19–25 dB with the reduction increasing to 40–48 dB for the frequency of 40 Hz. The sound insulation of acoustic enclosures with a sound-absorbing material inside reaches about 38 dB for the frequency of 10 kHz and about 63 dB for the frequency of 40 kHz. Conclusion Some pieces of equipment installed in the work environment are sources of noise emitted in the 10–40 kHz frequency range with the intensity which can be high enough to be harmful to humans. The most effective technical reduction of the associated risks are acoustic enclosures for such noise sources. The sound pressure level reduction obtained after provision of an enclosure depends on its design (shape, size, material, and thickness of walls) and the noise source frequency spectrum. Realistically available noise reduction values may exceed 60 dB.

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Sound Levels Forecasting in an Acoustic Sensor Network Using a Deep Neural Network

Sensors ◽

10.3390/s20030903 ◽

2020 ◽

Vol 20 (3) ◽

pp. 903 ◽

Cited By ~ 3

Author(s):

Juan M. Navarro ◽

Raquel Martínez-España ◽

Andrés Bueno-Crespo ◽

Ramón Martínez ◽

José M. Cecilia

Keyword(s):

Neural Network ◽

Sensor Network ◽

Sound Pressure Level ◽

Deep Neural Network ◽

Sound Pressure ◽

Noise Pollution ◽

Pressure Level ◽

Acoustic Sensor ◽

Short Term ◽

Sound Levels

Wireless acoustic sensor networks are nowadays an essential tool for noise pollution monitoring and managing in cities. The increased computing capacity of the nodes that create the network is allowing the addition of processing algorithms and artificial intelligence that provide more information about the sound sources and environment, e.g., detect sound events or calculate loudness. Several models to predict sound pressure levels in cities are available, mainly road, railway and aerial traffic noise. However, these models are mostly based in auxiliary data, e.g., vehicles flow or street geometry, and predict equivalent levels for a temporal long-term. Therefore, forecasting of temporal short-term sound levels could be a helpful tool for urban planners and managers. In this work, a Long Short-Term Memory (LSTM) deep neural network technique is proposed to model temporal behavior of sound levels at a certain location, both sound pressure level and loudness level, in order to predict near-time future values. The proposed technique can be trained for and integrated in every node of a sensor network to provide novel functionalities, e.g., a method of early warning against noise pollution and of backup in case of node or network malfunction. To validate this approach, one-minute period equivalent sound levels, captured in a two-month measurement campaign by a node of a deployed network of acoustic sensors, have been used to train it and to obtain different forecasting models. Assessments of the developed LSTM models and Auto regressive integrated moving average models were performed to predict sound levels for several time periods, from 1 to 60 min. Comparison of the results show that the LSTM models outperform the statistics-based models. In general, the LSTM models achieve a prediction of values with a mean square error less than 4.3 dB for sound pressure level and less than 2 phons for loudness. Moreover, the goodness of fit of the LSTM models and the behavior pattern of the data in terms of prediction of sound levels are satisfactory.

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Reducing of the Sound Pressure Level in Industrial Areas by Screening Noise Sources

Noise & Vibration Worldwide ◽

10.1260/0957-4565.43.10.28 ◽

2012 ◽

Vol 43 (10) ◽

pp. 28-36

Author(s):

Tomozei Claudia ◽

Nedeff Valentin ◽

Lazar Gabriel ◽

Ciobanu Elena

Keyword(s):

Sound Pressure Level ◽

Sound Pressure ◽

Pressure Level ◽

Noise Sources ◽

Industrial Areas

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The relationship of Depression Anxiety and Stress Scale and Harmon Jones with Noise in Isfahan Steel Industry Workers

Occupational Hygiene and Health Promotion ◽

10.18502/ohhp.v4i4.5448 ◽

2021 ◽

Author(s):

Hadi ALIMORADI ◽

Ruhollah FALLAH MADAVARI ◽

Mahsa NAZARI ◽

Reza JAFARI NODOSHAN ◽

Mohammad Javad ZARE SAKHVIDI ◽

...

Keyword(s):

Cognitive Dissonance ◽

Sound Pressure Level ◽

Steel Industry ◽

Sound Pressure ◽

Noise Pollution ◽

Pressure Level ◽

Control Group ◽

Case Group ◽

Wide Range ◽

Relationship Of

Introduction: Loud noise is one of the harmful factors that affects industry workers seriously. In the steel industry, a wide range of equipment and machinery are used in the production processes, which are considered as the sources of annoying noise. Sound has immediate and delayed harmful effects on the process of concentration and increases blood pressure. The aim of this study was to investigate the effect of noise in two different ranges in the control and case groups within the authorized (between 60 to 85 dB) and unauthorized (above 85 dB) categories in the steel industry. Methods: This cross-sectional study was conducted among 300 workers in Isfahan Steel Industries. Environmental sound assessment was performed to determine the distribution of sound pressure level according to the ISO 9612 standard in the company's production units. In this method, the number of exposed people, the exposure time, and the weight factor corresponding to the sound pressure level were calculated in 30 minutes. The DASS-42 and Harmon Jones (DARQ) questionnaires were used to predict the mental state of the participants and to measure the severity of mood swings and arousal. The collected data were analyzed using SPSS statistical software (ver22). Results: Based on the findings, age had a significant effect on depression, marital status had a significant effect on anxiety, and work shift had a significant effect on the level of stress and cognitive dissonance of employees. The stress mean was significantly higher in the case group (14.40 ± 1.66) than the control group (p <0.001). This indicates the effect of sound intensity level on the increase of stress and cognitive dissonance of workers in a noisy environment. With increasing exposure to sound, the participants’ stress decreased (p <0.05). Conclusion: Considering the positive and significant relationship of noise level with stress and cognitive inconsistency of workers in the case group, it is necessary to take effective preventive measures to prevent psychological harm and maintain the workers' health in this industry. In order to reduce noise, a number of applicable solutions have been proposed including spatial planning, selection of suitable materials, control of noise pollution related to outdoor construction, control of noise pollution related to indoor construction, and training.

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Pengujian Alat Pemanen Energi Akustik Berbasis Loudspeaker Dengan Sumber Kebisingan Acak Dari Mesin Kendaraan Bermotor

Prosiding SNFA (Seminar Nasional Fisika dan Aplikasinya) ◽

10.20961/prosidingsnfa.v4i0.35921 ◽

2019 ◽

Vol 4 ◽

pp. 152

Author(s):

Untung Adi Santosa ◽

Ikhsan Setiawan ◽

B.S. Utomo

Keyword(s):

Sound Pressure Level ◽

Sound Pressure ◽

Random Noise ◽

Electrical Power ◽

Dominant Frequency ◽

Pressure Level ◽

Acoustic Energy ◽

Noise Sources ◽

Quarter Wavelength ◽

The Impact

Abstract: This paper reports the test results of a loudspeaker-based acoustic energy harvester with acoustic random noise sources from a motorcycle. The harvester consists of a quarter wavelength resonator and a subwoofer type loudspeaker with a nominal diameter of 6 inches. The motorcycle used in this experiment is 135 cc Bajaj Pulsar motorsport with modified exhaust from the GBS-Motosport Jakarta. The motor engine is operated at 3000 rpm, resulting in noise with a fluctuating Sound Pressure Level (SPL) in the range of (90-93) dB. Six variations of resonator lengths are used, those are 21 cm, 31 cm, 58 cm, 85 cm, 112 cm, and 139 cm. In this test, data of dominant frequency, SPL, and output rms voltage were taken for 15 minutes. The rms voltage is measured at 100 Ω load resistor. The results show that the 112 cm resonator produces the highest average rms electrical power, that is (0.21 ± 0.01) mW, which is obtained at frequency that fluctuates within (95-120) Hz. In addition, with random sound sources, SPL and its dominant frequency fluctuate greatly, so it will greatly affect the generated electric power. Further research is needed to enhance the output electrical power and anticipate the impact of frequency fluctuation which exists in random noise sources.Abstrak: Paper ini memaparkan hasil pengujian alat pemanen energi akustik berbasis loudspeaker dengan sumber kebisingan acak dari mesin kendaraan bermotor. Alat pemanen energi akustik ini terdiri dari resonator seperempat panjang gelombang dan loudspeaker jenis subwoofer dengan diameter nominal 6 inci. Sumber kebisingan yang digunakan adalah motor Bajaj Pulsar 135 cc dengan knalpot modifikasi dari GBS-Motosport Jakarta. Mesin motor dioperasikan pada laju putaran tetap 3000 rpm, sehingga menghasilkan kebisingan dengan SPL (sound pressure level) yang berfluktuasi dalam interval (90-93) dB. Digunakan enam variasi panjang resonator, yaitu 21 cm, 31 cm, 58 cm, 85 cm, 112 cm, dan 139 cm. Dalam pengujian ini, data frekuensi dominan kebisingan, SPL kebisingan, dan tegangan keluaran alat pemanen energi akustik diambil selama 15 menit. Tegangan rms keluaran diukur pada resistor beban 100 Ω. Hasil eksperimen menunjukkan bahwa resonator dengan panjang 112 cm menghasilkan daya listrik rms rata-rata tertinggi yaitu sebesar (0,21 ± 0,01) mW, diperoleh pada frekuensi yang berfluktuasi antara 95 Hz sampai 120 Hz. Selain itu, hasil eksperimen ini menunjukkan bahwa dengan sumber bunyi acak, SPL kebisingan dan frekuensi dominannya sangat berfluktuasi, sehingga akan sangat berpengaruh terhadap daya listrik yang dihasilkan. Penelitian lebih lanjut diperlukan untuk meningkatkan daya listrik keluaran dan mengantisipasi dampak fluktuasi frekuensi sumber kebisingan acak.

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Study on acoustic environment of canteens in South China University of Technology

INTER-NOISE and NOISE-CON Congress and Conference Proceedings ◽

10.3397/in-2021-1902 ◽

2021 ◽

Vol 263 (5) ◽

pp. 1695-1702

Author(s):

Ziyu Zhou ◽

Hongwei Wang

Keyword(s):

South China ◽

Sound Pressure Level ◽

Sound Pressure ◽

Pressure Level ◽

Noise Sources ◽

Acoustic Environment ◽

University Of Technology ◽

Different Types ◽

Satisfaction Evaluation ◽

The Voice

In order to understand the characteristics of the acoustic environment of University canteens, the canteens of South China University of Technology were selected as the research objects, and the acoustic parameters were measured on the spot and the questionnaire survey was conducted. The results show that the average sound pressure level of restaurants with smaller area is lower than that of restaurants with larger area, and the sound pressure level of dining space first increases rapidly, then increases slowly, and finally remains unchanged with the increase of the number of diners. In the aspect of restaurant acoustic environment satisfaction evaluation, the space with the smallest dining area has the highest acoustic environment satisfaction evaluation level, and the collision sound of tableware collection and table and chair moving has the highest correlation with the acoustic environment satisfaction evaluation. In terms of different types of noise sources, diners think that the most disturbing noise for conversation is the voice of the surrounding people, followed by the collision of tables and chairs and the collection of tableware, and the least disturbing noise is the noise of air conditioning and kitchen equipment.

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Innovation in Noise Mapping in Natural Gas Compressor Stations

2010 8th International Pipeline Conference, Volume 3 ◽

10.1115/ipc2010-31048 ◽

2010 ◽

Author(s):

K. K. Botros ◽

A. Hawryluk ◽

J. Geerligs ◽

B. Huynh ◽

R. Phernambucq

Keyword(s):

Sound Pressure Level ◽

Gas Turbines ◽

Sound Pressure ◽

Dominant Frequency ◽

Pressure Level ◽

Multiple Point ◽

Noise Sources ◽

Noise Mapping ◽

Noise Measurements ◽

Future Work

Noise is generated at gas turbine-based compressor stations from a number of sources, including turbomachinery (gas turbines and compressors), airflow through inlet ducts and scrubbers, exhaust stacks, aerial coolers, and auxiliary systems. Understanding these noise sources is necessary to ensure that the working conditions on site are safe and that the audible noise at neighbouring properties is acceptable. Each noise source has different frequency content, and the overall sound pressure level (OSPL) at any location in the station yard or inside the compressor building is the result of a superposition of these noise sources. This paper presents results of multiple-point spectral noise measurements at three of TransCanada’s compressor stations on the Alberta System. A method is described to determine the overall noise map of the station yard using Delaunay Triangulation and Natural-Neighbour Interpolation techniques. The results are presented in OSPL maps, as well as animated pictures of the sound pressure level (SPL) in frequency domain which will be shown on a video at the conference. The latter will be useful in future work to determine the culprit sources and the respective dominant frequency range that contributes the most to the OSPL.

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