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Year 2020, Volume: 16 Issue: 4, 429 - 436, 30.12.2020

Abstract

References

  • [1] Utley, W. A. (1980), “Noise from opencast coal mining sites,” Applied Acoustics, vol. 13, no. 2, pp. 85–102.
  • [2] Ghose, M.K. “Noise pollution evaluation and its abatement measures in coal mining area,” Minetech, vol. 11, no. 3, pp. 55–57, 1990.
  • [3] Vardhan, H., Rao, Y. and Karmakar, N. “Noise analysis of heavy earth moving machinery deployed in opencast mines and development of suitable maintenance guidelines for its attenuation - part 1,” Noise and Vibration Worldwide, vol. 35, no. 8, pp. 11–24, 2004.
  • [4] Sharma, O., Mohanan , V. and Singh, M. “Noise emission levels in coal industry,” Applied Acoustics, Elsevier, vol. 54, no. 1, pp. 1–7, 1998.
  • [5] Barrientos, M.C., Lendrum, D.C. and Steenland, K., (2004). Occupational Noise; Assessing the Burden of Disease from Work-Related Hearing Impairment at National and Local Levels. World Health Organization Protection of the Human Environment. Environmental Burden of Disease Series, No. 9. Geneva.
  • [6] Donoghue AM. (2004) Occupational health hazards in mining: an overview. Occupational Medicine; 54: 283 - 289.
  • [7] Ramlu, M.A. “Occupational noise exposure and hearing damage,” Mining Engineer’s Journal, vol. 6, no. 7, pp. 9–20, 2005.
  • [8] Daniel, E., (2007). Noise and hearing loss: A review, Journal of School Health, 77, 5, 225-231.
  • [9] Joy, G. J., Middendorf, P. J., “Noise exposure and hearing conservation in us. coal mines-a surveillance report,” Journal of Occupational and Environmental Hygiene, vol. 4, no. 1, pp. 26–35, Jan 2007, http://www.cdc.gov/niosh/mining/pubs/pubreference/outputid2304.htm.
  • [10] Dekker JJ, Edwards AL, Franz RM, et al. (2011) Meeting the milestones: are South African small- to medium-scale mines up to the task. The Journal of The Southern African Institute of Mining and Metallurgy; 111: 309-313.
  • [11] Edwards, A.L., Dekker, J.J., Franz, R.M., Dyk, T. V. and Banyini, A. “ Profiles of noise exposure levels in South African Mining,” The Journal of The Southern African Institute of Mining and Metallurgy, vol. 111, pp. 315–322, 2011.
  • [12] Çınar, İ., Şensöğüt, C. (2013). Evaluation of noise measurements performed in mining sites for environmental aspects. International Journal of Environmental Research, 7(2), 383-386.
  • [13] Álvarez-Vigil, A.E., Gonzalez-Nicieza, C., Gayarre, F.L., Álvarez-Fernández, M.I. Predicting blasting propagation velocity and vibration frequency using artificial neural networks, International Journal of Rock Mechanics and Mining Sciences, 55 (2012) 108-116.
  • [14] Görgülü, K., Arpaz, E. Demirci, A., Koçaslan, A., Dilmaç, M.K., Yüksek, A.G. Investigation of blast-induced ground vibrations in the Tülü boron open pit mine, Bulletin of Engineering Geology and the Environment, 72 (2013) 555-564.
  • [15] Simangunsong, G.M., Wahyudi, S. Effect of bedding plane on prediction blast-induced ground vibration in open pit coal mines, International Journal of Rock Mechanics and Mining Sciences, 79 (2015) 1-8.
  • [16] Nanda SK, Tripathy DP Application of functional link artificial neural network for prediction of machinery noise in opencast mines, Advances in Fuzzy Systems, 4 (2011) 1-11.
  • [17] Huang X. Study on ANN noise adaptability in application of industry process characteristics mining. Advanced Materials Research, 2012;462:635-640.
  • [18] Karacan, C.Ö. Modeling and prediction of ventilation methane emissions of US longwall mines using supervised artificial neural networks, International Journal of Coal Geology, 73 (2008) 371-387.
  • [19] Zhao, K., Chen, S. Study on artificial neural network method for ground subsidence prediction of metal mine, Procedia Earth and Planetary Science, 2 (2011) 177-182.
  • [20] Naghadehi, M.Z., Jimenez, R., KhaloKakaie, R., Jalali, S.M.E. A new open-pit mine slope instability index defined using the improved rock engineering systems approach, International Journal of Rock Mechanics and Mining Sciences, 61 (2013) 1-14.
  • [21] Siami-Irdemoosa, E., Dindarloo, S.R. Prediction of fuel consumption of mining dump trucks: A neural networks approach, Applied Energy, 151 (2015) 77-84.
  • [22] Rahimdel MJ., Mirzaei M., Sattarvand J., Ghodrati B., Mirzaei Nasirabad H. Artificial neural network to predict the health risk caused by whole body vibration of mining trucks Journal of Theor Appl Vibr Acous. 3(1) (2017) 1–14.

Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks

Year 2020, Volume: 16 Issue: 4, 429 - 436, 30.12.2020

Abstract

Ever inreasing demand to raw mineral production stimulates intense use of mining machinery and subsequently exposes mining machinery operators to high levels of continuous noise. Long-term exposure to high levels of continuous noise can cause Occupational Hearing Loss (OHL) on operators. In order to certify a good working environment, it is important to estimate real noise levels of opencast mining machines.
The aim of this study was to assess exposure levels to continuous noise using the test records of continouos noise emitted from mining machinery and recommend some actions to reduce it. Artificial neural networks (ANN) tool developed by MATLAB software has been used for these estimates.
During the study, consistent personal noise exposure levels emitting from 60 different opencast mining machinery was recorded. The lowest, highest, average and equivalent noise levels of the machines were recorded and possible exposure noise-levels (LEX,8H) on operators were calculated.
Later, data obtained from tests were used to train the ANN multilayered model by forward-feed-fault-back circulation algorithm. During modeling of ANN; vehicle types, recording times, ambient temperature and pressure and relative humudity were determined as input parameters. By the help of the model, equivalent and momentary noise levels prior to maximum level were estimated. Following training and testing of the model, the obtained noise levels were examined by statistical analysis commonly used in ANN models. It was noticed that the designed model provided very close results to the actual test results and can be applied successfully.

References

  • [1] Utley, W. A. (1980), “Noise from opencast coal mining sites,” Applied Acoustics, vol. 13, no. 2, pp. 85–102.
  • [2] Ghose, M.K. “Noise pollution evaluation and its abatement measures in coal mining area,” Minetech, vol. 11, no. 3, pp. 55–57, 1990.
  • [3] Vardhan, H., Rao, Y. and Karmakar, N. “Noise analysis of heavy earth moving machinery deployed in opencast mines and development of suitable maintenance guidelines for its attenuation - part 1,” Noise and Vibration Worldwide, vol. 35, no. 8, pp. 11–24, 2004.
  • [4] Sharma, O., Mohanan , V. and Singh, M. “Noise emission levels in coal industry,” Applied Acoustics, Elsevier, vol. 54, no. 1, pp. 1–7, 1998.
  • [5] Barrientos, M.C., Lendrum, D.C. and Steenland, K., (2004). Occupational Noise; Assessing the Burden of Disease from Work-Related Hearing Impairment at National and Local Levels. World Health Organization Protection of the Human Environment. Environmental Burden of Disease Series, No. 9. Geneva.
  • [6] Donoghue AM. (2004) Occupational health hazards in mining: an overview. Occupational Medicine; 54: 283 - 289.
  • [7] Ramlu, M.A. “Occupational noise exposure and hearing damage,” Mining Engineer’s Journal, vol. 6, no. 7, pp. 9–20, 2005.
  • [8] Daniel, E., (2007). Noise and hearing loss: A review, Journal of School Health, 77, 5, 225-231.
  • [9] Joy, G. J., Middendorf, P. J., “Noise exposure and hearing conservation in us. coal mines-a surveillance report,” Journal of Occupational and Environmental Hygiene, vol. 4, no. 1, pp. 26–35, Jan 2007, http://www.cdc.gov/niosh/mining/pubs/pubreference/outputid2304.htm.
  • [10] Dekker JJ, Edwards AL, Franz RM, et al. (2011) Meeting the milestones: are South African small- to medium-scale mines up to the task. The Journal of The Southern African Institute of Mining and Metallurgy; 111: 309-313.
  • [11] Edwards, A.L., Dekker, J.J., Franz, R.M., Dyk, T. V. and Banyini, A. “ Profiles of noise exposure levels in South African Mining,” The Journal of The Southern African Institute of Mining and Metallurgy, vol. 111, pp. 315–322, 2011.
  • [12] Çınar, İ., Şensöğüt, C. (2013). Evaluation of noise measurements performed in mining sites for environmental aspects. International Journal of Environmental Research, 7(2), 383-386.
  • [13] Álvarez-Vigil, A.E., Gonzalez-Nicieza, C., Gayarre, F.L., Álvarez-Fernández, M.I. Predicting blasting propagation velocity and vibration frequency using artificial neural networks, International Journal of Rock Mechanics and Mining Sciences, 55 (2012) 108-116.
  • [14] Görgülü, K., Arpaz, E. Demirci, A., Koçaslan, A., Dilmaç, M.K., Yüksek, A.G. Investigation of blast-induced ground vibrations in the Tülü boron open pit mine, Bulletin of Engineering Geology and the Environment, 72 (2013) 555-564.
  • [15] Simangunsong, G.M., Wahyudi, S. Effect of bedding plane on prediction blast-induced ground vibration in open pit coal mines, International Journal of Rock Mechanics and Mining Sciences, 79 (2015) 1-8.
  • [16] Nanda SK, Tripathy DP Application of functional link artificial neural network for prediction of machinery noise in opencast mines, Advances in Fuzzy Systems, 4 (2011) 1-11.
  • [17] Huang X. Study on ANN noise adaptability in application of industry process characteristics mining. Advanced Materials Research, 2012;462:635-640.
  • [18] Karacan, C.Ö. Modeling and prediction of ventilation methane emissions of US longwall mines using supervised artificial neural networks, International Journal of Coal Geology, 73 (2008) 371-387.
  • [19] Zhao, K., Chen, S. Study on artificial neural network method for ground subsidence prediction of metal mine, Procedia Earth and Planetary Science, 2 (2011) 177-182.
  • [20] Naghadehi, M.Z., Jimenez, R., KhaloKakaie, R., Jalali, S.M.E. A new open-pit mine slope instability index defined using the improved rock engineering systems approach, International Journal of Rock Mechanics and Mining Sciences, 61 (2013) 1-14.
  • [21] Siami-Irdemoosa, E., Dindarloo, S.R. Prediction of fuel consumption of mining dump trucks: A neural networks approach, Applied Energy, 151 (2015) 77-84.
  • [22] Rahimdel MJ., Mirzaei M., Sattarvand J., Ghodrati B., Mirzaei Nasirabad H. Artificial neural network to predict the health risk caused by whole body vibration of mining trucks Journal of Theor Appl Vibr Acous. 3(1) (2017) 1–14.
There are 22 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Ayla Tekin 0000-0002-2547-0872

Publication Date December 30, 2020
Published in Issue Year 2020 Volume: 16 Issue: 4

Cite

APA Tekin, A. (2020). Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks. Celal Bayar Üniversitesi Fen Bilimleri Dergisi, 16(4), 429-436.
AMA Tekin A. Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks. CBUJOS. December 2020;16(4):429-436.
Chicago Tekin, Ayla. “Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 16, no. 4 (December 2020): 429-36.
EndNote Tekin A (December 1, 2020) Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 16 4 429–436.
IEEE A. Tekin, “Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks”, CBUJOS, vol. 16, no. 4, pp. 429–436, 2020.
ISNAD Tekin, Ayla. “Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 16/4 (December 2020), 429-436.
JAMA Tekin A. Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks. CBUJOS. 2020;16:429–436.
MLA Tekin, Ayla. “Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks”. Celal Bayar Üniversitesi Fen Bilimleri Dergisi, vol. 16, no. 4, 2020, pp. 429-36.
Vancouver Tekin A. Noise Exposure Estimation of Surface-Mine- Heavy Equipment Operators Using Artificial Neural Networks. CBUJOS. 2020;16(4):429-36.