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Analysis of noise pollution emitted by stationary MF285 tractor using different mixtures of biodiesel, bioethanol, and diesel through artificial intelligence

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Abstract

In the present study, the noise pollution from different compositions of biodiesel, bioethanol, and diesel fuels in a four-cylinder and four-stroke engine of MF285 tractor was studied. Further, the noise pollution was measured from two positions, the driver and bystander, at 1000, 1600, and 2000 revolutions, and ten different fuel levels resulting from different compositions of biodiesel, bioethanol, and diesel fuels. For data analysis, adaptive network-based fuzzy inference system (ANFIS), artificial neural network (ANN), and response surface methodology (RSM) were applied. Comparing the means of noise pollution at different levels demonstrated that the B25E6D69 fuel, made up of 25% biodiesel and 6% bioethanol, had the lowest noise pollution. The lowest noise pollution was at 1000 rpm, and with the increase of engine speed, the noise pollution intensified. The models laid by the RSM were better than other.

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References

  • Andrew LG, Dianne CH, Brian JS (2007) The effect of piston friction on the torsional natural frequency of a reciprocating engine. Mech Syst Signal Process 21:2833–2837

    Article  Google Scholar 

  • Arkhipov M, Krueger E, Kurtener D (2008) Evaluation of ecological conditions using bioindicators: application of fuzzy modeling. International conference on computational science and its applications, pp 491–500

    Google Scholar 

  • Aybek A, Kamer HA, Arslan S (2010) Personal noise exposures of operators of agricultural tractors. Appl Ergon 41:274–281

    Article  Google Scholar 

  • Azadeh A, Ghaderi SF, Sohrabkhani S (2006) Forecasting electrical consumption by integration of neural network, time series and ANOVA. Appl Math Comput 186:1753–1761

    Google Scholar 

  • Balan B, Mohaghegh S, Ameri S (1995) State- of- art- in permeability determination from well log data: part 1- a comparative study, model development. Society of Petroleum Engineers, United States of America

    Google Scholar 

  • Brown RH (1988) Handbook of engineering in agriculture, vol 2. Prentice & Hall pub. Inc, U.K

    Google Scholar 

  • Buragohain M, Mahanta C (2008) A novel approach for ANFIS modelling based on full factorial design. Appl Soft Comput 8:609–625

    Article  Google Scholar 

  • Celen IH, Arin S (2003) Noise level of agricultural tractor. Pak J Biol Sci 6(19):1706–1711

    Article  Google Scholar 

  • Cheng CB, Cheng CJ, Lee ES (2002) Neuro-fuzzy and genetic algorithm in multiple response optimization. Comput Math Appl 44:1503–1514

    Article  Google Scholar 

  • Cormick A, Willims J, Brimhall I, Hoyes RR (2006) Effects of biodiesel blends on vehicle emissions, Fiscal year 2006 annual operating plan milestone 10.4. National Renewable Energy Laboratory

  • Craverner TL, Roush WB (1999) Improving neural network prediction of amino acid levels in feed ingredients. J Appl Poult Res 78:983–991

    Google Scholar 

  • Crocker MJ (1998) Handbook of acoustics, vol 1. John Wiley & Sons, New York

    Google Scholar 

  • Dayhoff J (1990) Neural network principles. Prentice-Hall International, U.S.A

    Google Scholar 

  • Dewangan KN, Kumar GP, Tewari VK (2005) Noise characteristics of tractors and health effect on farmers. Appl Acoust 66:1049–1062

    Article  Google Scholar 

  • Durbin J, Watson GS (1971) Testing for serial correlation in least squares regression. Biometrika 58:1–19

    Google Scholar 

  • Emam MA (2012) Prediction of agricultural tractor noise levels using artificial neural networks. Int J Curr Res 4:170–176

    Google Scholar 

  • Farkas I, Remenyi P, Biro B (2000) A neural network topology for modeling grain drying. Comput Electron Agric 26:147–158

    Article  Google Scholar 

  • Ferella F, Mazziotti Di Celso G, De Michelis I, Stanisci V, Veglio F (2010) Optimization of the trasesterification reaction in biodiesel production. Fule 89:36–42

    Article  CAS  Google Scholar 

  • Hassan-Beygi SR, Ghobadian B, Kianmehr MH, Chayjan RA (2007) Prediction of a power tiller sound pressure levels in octave frequency bands using artificial neural networks. Int J Agric Biol 3:494–496

    Google Scholar 

  • Haykin S (1994) Neural networks: a comprehensive foundation. McMillan College Publishing Company, New York

    Google Scholar 

  • JunHong Z, Bing H (2005) Analysis of engine front noise using sound intensity techniques. Mechanical systems and signal processing 19, pp 213–221

    Google Scholar 

  • Keskin A (2010) The in flounce of ethanol-gasoline blends on spark ignition engine vibration characteristics and noise emissions. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 32:1851–1860

  • Kumar A, Ganjyal GM, Jones DD, Hanna MA (2006) Digital image processing for measurement of residence time distribution in a laboratory extruder. J Food Eng 75:237–244

    Article  Google Scholar 

  • Li W, Ren Y, Wang XB, Miao H, Huang ZH (2007) Combustion characteristics of a compression ignition engine fuelled with diesel-ethanol blends. Automob Eng 222:265–274

    Article  Google Scholar 

  • Metin EH, Murat H (2008) Comparative analysis of an evaporative condenser using artificial neural network and adaptive neuro-fuzzy inference system. Int J Refrig 31:1426–1436

    Article  CAS  Google Scholar 

  • Mion RL, Viliotti CA, Dantas MJF, Nascimento EMS (2009) Evaluation of noise levels of mechanized tractor seeders pneumatic. Engenharia na Agricultura 17:87–92

    Article  Google Scholar 

  • Mittal GS, Zhang J (2000) Prediction of temperature and moisture content of frankfurters during thermal processing using neural network. J Appl Poult Res 78:13–24

    Google Scholar 

  • Naderloo L, Alimardani R, Omid M, Sarmadian F, Javadikia P, Torabi MY, Alimardani F (2012) Application of ANFIS to predict crop yield based on different energy inputs. Measurement 45:1406–1413

    Article  Google Scholar 

  • Paulraj MP, Yaacob S, Andrew AM (2010) Vehicle noise comfort level indication using artificial neural network. In: 3rd Regional Conference on Noise VaCN (Hrsg.), Putrajaya, Malaysia

    Google Scholar 

  • Pruvost L, Leclère Q, Parizet E (2009) Diesel engine combustion and mechanical noise separation using an improved spectrofilter, vol 23, pp 2072–2087

    Google Scholar 

  • Rakopoulos DC, Rakopoulos CD, Kakaras EC, Giakoumis EG (2008) Effects of ethanol–diesel fuel blends on the performance and exhaust emissions of heavy duty DI diesel engine. Energy Convers Manag 49:3155–3162

    Article  CAS  Google Scholar 

  • Salles E, Zambotti A, Gouvea A et al (2008) An experimental study of diesel-ethanol combustion controlled electronically. Robert Bosch Ltda, Colombia

    Google Scholar 

  • Salokhe VM, Majumder B, Islam MS (1995) Vibration characteristics of power tiller. J Terrramech 32:181–196

    Article  Google Scholar 

  • Sehsah EE, Abass Helmy M, Sorour HM (2010) Noise test of two manufactured power tillers during transport on different local road conditions. Int J Agric Biol Eng 3:19–27

    Google Scholar 

  • Selim MYE (2001) Pressure-time characteristics in diesel engine fueled with natural gas. Renew Energy 22:473–489

    Article  CAS  Google Scholar 

  • Serge G (2001) Designing fuzzy inference systems from data: interpretability oriented review. IEEE Trans Fuzzy Syst 9:426–442

    Article  Google Scholar 

  • Solecki L (1998) Occupational hearing loss among selected farm tractor operators employed on large multiproduction farm in Poland. Int J Occup Med Environ Health 11:69–80

    CAS  Google Scholar 

  • Stayner RM (1988) Maximum permissible noise levels emitted by wheeled agricultural and forestry tractors in the member states of the European Community. Appl Acoust 23:191–197

    Article  Google Scholar 

  • Taghi zadeh-ali saraei A, Ghobadian B, Tavakoli–hashjin T, Mohtasebie SS (2012) Vibration analysis of a diesel engine using biodiesel and pet diesel fuel blends. Fuel 102:414–422

    Article  CAS  Google Scholar 

  • Taghizadeh-Alisaraei A, Ghobadian B, Tavakoli-Hashjin T, Mohtasebi SS (2012) Vibration analysis of a diesel engine using biodiesel and petrodiesel fuel blends. Fuel 102:414–422

    Article  CAS  Google Scholar 

  • Talamo JDC (1985) Active control of low frequency noise in tractor cabs, noise and vibration in agriculture and forestry, Proceedings of the Eight Foint Ergonomics Symposium, Silsoe, England, pp 46–52

    Google Scholar 

  • Yıldırım S, Eski I (2008) Sound quality analysis of cars using hybrid neural networks. Simul Model Pract Theory 16:410–418

    Article  Google Scholar 

  • Zoldy M (2011) Ethanol-biodiesel-diesel blends as a diesel extender option on compression ignition engines. Transp J 26:303–309

    Article  Google Scholar 

Download references

Funding

The authors would like to acknowledge the financial support from the Ministry of Science, Research and Technology, Tehran, Iran, and the Vice Chancellor for Research and Technology of Razi University of Kermanshah.

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Authors and Affiliations

  1. Department of Mechanical Biosystems Engineering, Faculty of Agriculture, College of Agriculture and Natural Science, Razi University, Kermanshah, 67571, Iran

    Mohammad Ghaderi, Hossein Javadikia, Leila Naderloo, Mostafa Mostafaei & Hekmat Rabbani

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  1. Mohammad Ghaderi
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  2. Hossein Javadikia
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  3. Leila Naderloo
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  4. Mostafa Mostafaei
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  5. Hekmat Rabbani
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Correspondence to Hossein Javadikia.

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Ghaderi, M., Javadikia, H., Naderloo, L. et al. Analysis of noise pollution emitted by stationary MF285 tractor using different mixtures of biodiesel, bioethanol, and diesel through artificial intelligence. Environ Sci Pollut Res 26, 21682–21692 (2019). https://doi.org/10.1007/s11356-019-05523-1

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  • DOI: https://doi.org/10.1007/s11356-019-05523-1

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