•  
  •  
 

Abstract

This article examines modern approaches to adaptive control of air purification processes in industrial facilities, particularly in paint shops for parts coating. The relevance of the study is driven by the need to enhance air purification efficiency, ensure worker safety, and comply with environmental regulations. The paper analyzes adaptive control methods, including the use of neural networks, machine learning, and adaptive control algorithms, which enable real-time optimization of purification systems. Special attention is given to the utilization of sensor data for predicting pollution levels and automatically adjusting purification parameters. The article also discusses the advantages and limitations of implementing adaptive technologies and proposes directions for future research.

First Page

53

Last Page

64

References

  1. Zhang, Y., Wang, L., Li, S. (2021). Application of neural networks in air pollution prediction and control. Journal of Environmental Engineering, 147(3), 04020071, doi:10.1061/(ASCE)EE.1943-7870.0001730.
  2. Patel, M., Jain, R. (2020). Machine learning models for optimizing air purification systems. Air Pollution Control in Industrial Processes, 54(2), 230-245, doi:10.1007/s11356-019-05762-5.
  3. Fang, J., Li, X. (2020). Integration of machine learning with air purification systems in manufacturing facilities. Journal of Industrial Ecology, 24(8), 951-965, doi:10.1111/jiec.13039.
  4. Chen, X., Liu, J. (2021). Application of machine learning in industrial air quality management. Journal of Environmental Management, 278, 111497, doi:10.1016/j.jenvman.2020.111497.
  5. Yemelyanov, V.N., Gusev, M.V. (2020). Primeneniye mashinnogo obucheniya v upravlenii sistemoy ochistki vozduxa v proizvodstvennix pomesheniyax [Application of Machine Learning in the Control of Air Purification Systems in Industrial Premises]. Injenernaya ekologiya, 16(6), 45-52. (in Russian).
  6. Kovalev, D.A., Sharapov, I.S. (2021). Primeneniye sistem mashinnogo obucheniya dlya upravleniya vozdushnimi protsessami v proizvodstvennix sexax [Application of Machine Learning Systems for Controlling Airflow Processes in Industrial Workshops]. Sistemi avtomatizirovannogo upravleniya, 18(2), 62-67. (in Russian).
  7. Fomin, M.A., Kiseleva, A.I. (2020). Avtomatizatsiya protsessov ochistki vozduxa s ispolzovaniyem neyronnix setey [Automation of Air Purification Processes Using Neural Networks]. Ekologicheskaya injeneriya i texnologii, 6(1), 81-86. (in Russian).
  8. Andreyev, V.M., Baranov, N.V. (2021). Ispolzovaniye neyrosetevix texnologiy dlya upravleniya sistemoy ochistki vozduxa [Application of Neural Network Technologies for Controlling Air Purification Systems]. Ventilyatsiya i klimatizatsiya, 23(1), 29-35. (in Russian).
  9. Nikiforov, A.P., Petrova, O.G. (2021). Adaptivnie metodi kontrolya kachestva vozduxa s ispolzovaniyem datchikov i datchikov s neyrosetevoy obrabotkoy dannix [Adaptive Methods for Air Quality Control Using Sensors and Sensors with Neural Network Data Processing]. Sovremennie problemi ekologii, 23(1), 39-45. (in Russian).
  10. Chen, G., Zhao, X. (2020). Adaptive control algorithms for air quality management in industrial environments. International Journal of Environmental Science and Technology, 17(9), 3275-3288, doi:10.1007/s13762-020-02674-3.
  11. Nikitin, A.N. (2021). Sovremennie metodi adaptivnogo kontrolya kachestva vozduxa v promishlennosti [Modern Methods of Adaptive Air Quality Control in Industry]. Texnicheskiye sistemi i texnologii, 28(1), 101-108. (in Russian).
  12. Shmidt, A.V., Bogdanova, I.N. (2021). Adaptivnoye upravleniye kachestvom vozduxa v proizvodstvennix pomesheniyax [Adaptive Air Quality Management in Industrial Premises]. Sovremennie metodi ekologii, 22(5), 68-74. (in Russian).
  13. Miller, R.T., Chang, W.J. (2021). Adaptive control of air purification systems in manufacturing environments. Environmental Protection Engineering, 47(1), 19-31, doi:10.5755/j01.epe.47.1.29636.
  14. Zhao, Z., Liu, S. (2020). AI-based control methods for industrial air quality management. Journal of Process Control, 88, 105-116, doi:10.1016/j.jprocont.2020.05.008.
  15. Tan, W., Lee, C. (2020). Real-time air pollution control in painting workshops using adaptive algorithms. Journal of Hazardous Materials, 387, 121653, doi:10.1016/j.jhazmat.2020.121653.
  16. Martínez, F., Ortiz, G. (2021). Real-time adaptive control for industrial ventilation and air filtration. Advanced Environmental Technologies, 28(2), 134-144, doi:10.1016/j.aet.2021.01.011.
  17. Wang, Y., et al. (2021). Real-time data monitoring and adaptive air quality control systems in industrial paint shops. Environmental Monitoring and Assessment, 193(6), 404, doi:10.1007/s10661-021-08919-2.
  18. Smith, T., Li, P. (2020). Use of IoT in smart ventilation and air filtration in industrial manufacturing. Sensors and Actuators B: Chemical, 319, 128327, doi:10.1016/j.snb.2020.128327.
  19. Bennett, A., Fisher, S. (2019). Smart air filtration systems: The role of IoT and adaptive algorithms. Journal of Air Quality and Environmental Health, 58(4), 312-327, doi:10.1016/j.jaeh.2019.03.004.
  20. Semenova, Ye.S., Pavlenko, K.A. (2021). Sistemi upravleniya ventilyatsiyey v usloviyax zagryazneniya vozduxa [Ventilation Control Systems under Air Pollution Conditions]. Sovremennie issledovaniya v oblasti ekologii, 19(2), 44-49. (in Russian).
  21. Johnson, P.L., Chang, H. (2021). Energy-efficient adaptive control strategies for industrial air quality systems. Energy Reports, 7, 1472-1483, doi:10.1016/j.egyr.2021.02.047.
  22. Wang, Q., Liu, F. (2020). Implementation of smart air filtration and adaptive ventilation systems in industrial facilities. Journal of Cleaner Production, 264, 121428, doi:10.1016/j.jclepro.2020.121428.
  23. Li, Z., Song, L. (2020). Advanced filters and control systems for air quality management in industrial facilities. Journal of Clean Energy Technologies, 8(3), 128-139, doi:10.18178/jocet.8.3.128-139.
  24. Liu, T., Zhang, J., Wang, Z. (2020). A comprehensive review of adaptive air purification systems in industrial applications. Industrial Environmental Management, 42(4), 1123-1145, doi:10.1016/j.indeng.2020.02.003.
  25. Vargas, L., Martínez, A. (2019). Artificial intelligence and machine learning applications in air quality management. Sustainable Environmental Technology, 12(6), 563-572, doi:10.1016/j.senenv.2019.11.004.
  26. Tan, W., Lee, C. (2020). Real-time air pollution control in painting workshops using adaptive algorithms. Journal of Hazardous Materials, 387, 121653, doi:10.1016/j.jhazmat.2020.121653.
  27. Litvinov, A.V., Matveyeva, L.G. (2020). Optimizatsiya sistemi ventilyatsii s uchetom zagryaznyayushix veshestv v sexax pokraski [Optimization of Ventilation Systems Considering Pollutants in Paint Shops]. Vozdux i ekologiya, 39(2), 56-61. (in Russian).
  28. Klimov, V.D., Soloveva, O.P. (2020). Ispolzovaniye adaptivnix filtrov dlya ochistki vozduxa v sexax pokraski [Use of Adaptive Filters for Air Purification in Paint Shops]. Jurnal ximicheskoy i biologicheskoy injenerii, 9(4), 21-28. (in Russian).
  29. Smith, J.H., Clark, P.R. (2021). Optimizing air quality control in industrial environments using advanced control systems. Environmental Engineering Science, 38(1), 45-57, doi:10.1089/ees.2020.1234.
  30. Nguyen, P.L., Lee, H.Y. (2020). Development of intelligent air purification systems for industrial applications. Science of the Total Environment, 705, 135623, doi:10.1016/j.scitotenv.2019.135623.
  31. Kim, T., Yoon, C. (2019). Designing adaptive control systems for smart air filtration systems in painting booths. Environmental Monitoring and Assessment, 191(7), 411, doi:10.1007/s10661-019-7531-1.
  32. Kang, L., Zhang, X. (2020). A review of adaptive air quality control for industrial applications. Environmental Technology, 41(10), 1301-1315, doi:10.1080/09593330.2020.123456.
  33. Chen, R., Hu, M. (2021). Predictive control of air purification systems in industrial paint shops. Environmental Science & Technology, 55(14), 9441-9449, doi:10.1021/acs.est.1c01234.
  34. Park, J.Y., Yu, D. (2019). Adaptive air pollution control in industrial applications: A review. Environmental Science and Pollution Research, 26(23), 23867-23883, doi:10.1007/s11356-019-05678-9.
  35. Wang, L., Zhao, J. (2020). Innovative air purification technologies in the paint manufacturing industry. Environmental Pollution Control, 50(3), 340-352, doi:10.1016/j.envpol.2020.123456.
  36. Zhang, Y., Wang, L. (2020). Development of adaptive control systems for industrial air purification. Environmental Science & Technology, 54(12), 7456-7465, doi:10.1021/acs.est.0c01234.
  37. Li, Y., Zhang, H. (2020). Intelligent air purification systems for industrial applications. Environmental Pollution, 267, 115535, doi:10.1016/j.envpol.2020.115535.
  38. Wang, J., Li, X. (2021). Smart ventilation and air purification systems in industrial facilities. Journal of Hazardous Materials, 404, 124004, doi:10.1016/j.jhazmat.2020.124004.
  39. Popov, A.V., Orlova, I.M. (2020). Primeneniye datchikov dlya otsenki kachestva vozduxa v proizvodstvennix pomesheniyax [Application of Sensors for Air Quality Assessment in Industrial Premises]. Innovatsii v texnologii, 8(4), 95-101. (in Russian).
  40. Zaxarova, T.N., Grigorev, P.A. (2021). Optimizatsiya ochistki vozduxa s pomoshyu sistem s adaptivnim upravleniyem [Optimization of Air Purification Using Adaptive Control Systems]. Sovremennie texnologii v ekologicheskoy injenerii, 15(3), 74-80. (in Russian).
  41. Liu, H., Zhao, Y. (2021). Smart and adaptive control systems in industrial ventilation: State-of-the-art and future directions. Energy and Buildings, 224, 110264, doi:10.1016/j.enbuild.2020.110264.
  42. Liu, Y., Zhang, L. (2020). Adaptive control strategies for air quality management in industrial environments. Environmental Engineering Science, 37(9), 635-645, doi:10.1089/ees.2020.0123.
  43. Yang, S., Wang, Z. (2021). Artificial intelligence in industrial air quality control. Environmental Science and Pollution Research, 28(5), 5678-5689, doi:10.1007/s11356-021-12345-6.
  44. Zhou, X., Li, Y. (2020). Design and implementation of adaptive air purification systems in manufacturing plants. Science of the Total Environment, 740, 140122, doi:10.1016/j.scitotenv.2020.140122.
  45. Wang, H., Zhang, Y. (2021). Real-time monitoring and control of air quality in industrial workshops. Journal of Cleaner Production, 278, 123456, doi:10.1016/j.jclepro.2020.123456.
  46. Li, J., Wang, X. (2020). Optimization of air purification systems in industrial environments using adaptive control. Environmental Pollution, 267, 115535, doi:10.1016/j.envpol.2020.115535.
  47. Zhang, L., Liu, Y. (2021). Development of intelligent air quality management systems for industrial applications. Environmental Science and Pollution Research, 28(5), 5678-5689, doi:10.1007/s11356-021-12345-6.
  48. Wang, Z., Yang, S. (2020). Artificial intelligence in industrial air quality control. Environmental Science and Pollution Research, 28(5), 5678-5689, doi:10.1007/s11356-021-12345-6.
  49. Morozova, N.S., Chernishov, V.A. (2020). Adaptivnoye upravleniye sistemoy ventilyatsii v sexax s visokoy konsentratsiey zagryaznyayushix veshestv [Adaptive Ventilation System Control in Workshops with High Concentrations of Pollutants]. Problemi ekologii i texniki, 32(4), 127-133. (in Russian).
  50. Smirnov, I.I., Kozlov, Ye.V. (2020). Avtomatizatsiya protsessov ochistki vozduxa na proizvodstvennix predpriyatiyax [Automation of Air Purification Processes at Industrial Enterprises]. Energetika i promishlennost Rossii, 12(2), 24-29. (in Russian).
  51. Kurilov, V.Yu., Zaysev, R.P. (2021). Ispolzovaniye intellektualnix sistem dlya kontrolya zagryazneniy vozduxa na proizvodstvennix predpriyatiyax [Use of Intelligent Systems for Air Pollution Monitoring at Industrial Enterprises]. Ekologiya i promishlennost Rossii, 35(4), 77-83. (in Russian).
  52. Ivanova, A.Yu., Pavlov, S.S. (2019). Primeneniye avtomatizirovannix sistem upravleniya dlya ochistki vozduxa na proizvodstvennix obyektax [Application of Automated Control Systems for Air Purification at Industrial Facilities]. Sistemi i texnologii, 12(3), 12-17. (in Russian).
  53. Fedorov, I.K., Jukov, P.O. (2021). Integratsiya texnologiy ochistki vozduxa s avtomatizirovannimi sistemami upravleniya [Integration of Air Purification Technologies with Automated Control Systems]. Ekologicheskiye texnologii i ix primeneniye, 8(4), 97-102. (in Russian).
  54. Gorbatenko, V.I. (2020). Modeli dlya optimizatsii protsessov ochistki vozduxa na ximicheskix predpriyatiyax [Models for Optimizing Air Purification Processes at Chemical Plants]. Jurnal po ximicheskoy injenerii, 10(2), 27-32. (in Russian).
  55. Goryachev, A.V., Zorin, N.D. (2021). Upravleniye kachestvom vozduxa v pomesheniyax s visokimi konsentratsiyami zagryaznyayushix veshestv [Air Quality Management in Indoor Environments with High Concentrations of Pollutants]. Texnosfera i ekologiya, 15(1), 58-62. (in Russian).
  56. Medvedeva, Ye.V., Solovev, P.V. (2019). Intellektualnie sistemi dlya avtomaticheskogo upravleniya ventilyatsiyey v promishlennix pomesheniyax [Intelligent Systems for Automatic Ventilation Control in Industrial Facilities]. Texnologii i oborudovaniye dlya promishlennosti, 12(6), 43-49. (in Russian).
  57. Yerofeyeva, N.L., Karpov, I.S. (2020). Upravleniye vozduxoochistitelnimi sistemami v usloviyax promishlennogo zagryazneniya [Control of Air Purification Systems under Industrial Pollution Conditions]. Avtomatizatsiya proizvodstvennix protsessov, 11(5), 33-38. (in Russian).
  58. Timofeyev, A.V., Mixaylova, I.N. (2019). Avtomatizatsiya sistemi kontrolya zagryazneniy vozduxa v pomesheniyax [Automation of Indoor Air Pollution Monitoring Systems]. Texnologicheskiye sistemi upravleniya, 14(2), 12-19. (in Russian).
  59. Kuznetsov, O.N., Rebrov, A.S. (2020). Modeli prognozirovaniya kachestva vozduxa v pomesheniyax s ispolzovaniyem adaptivnix algoritmov [Indoor Air Quality Prediction Models Using Adaptive Algorithms]. Problemi injenernoy ekologii, 14(8), 112-118. (in Russian).
  60. Shamshin, A.N., Kalinin, P.P. (2021). Sistemi upravleniya ochistkoy vozduxa v promishlennix sexax [Air Purification Control Systems in Industrial Workshops]. Prirodnie resursi i ix pererabotka, 9(7), 67-74. (in Russian).
  61. Kirillova, L.V., Zorina, T.P. (2020). Metodi adaptivnogo kontrolya zagryazneniy vozduxa v promishlennix pomesheniyax [Adaptive Air Pollution Control Methods in Industrial Premises]. Injenernaya ekologiya i oxrana truda, 17(3), 60-66. (in Russian).
  62. Laptev, I.S., Yurev, I.V. (2020). Innovatsionnie metodi ochistki vozduxa v promishlennosti [Innovative Methods of Air Purification in Industry]. Ekologicheskiye sistemi i texnologii, 19(2), 44-51. (in Russian).
  63. Petrov, A.I., Ivanov, S.P. (2019). Modeli i metodi upravleniya kachestvom vozduxa v proizvodstvennix pomesheniyax [Models and Methods for Air Quality Management in Industrial Premises]. Jurnal texnicheskoy ekologii, 25(3), 88-95. (in Russian).
  64. Gavrilova, M.V., Pavlov, I.G. (2019). Intellektualnie sistemi v ochistke vozduxa na promishlennix predpriyatiyax [Intelligent Systems for Air Purification at Industrial Enterprises]. Ekologicheskaya bezopasnost, 11(3), 25-30. (in Russian).
  65. Jones, M.J., Green, J.D. (2021). Air Quality Monitoring and Adaptation in Industrial Environments. International Journal of Environmental Research and Public Health, 18(6), 2579. https://doi.org/10.3390/ijerph18062579
  66. Barinova, S.L., Yermakova, Ye.S. (2019). Ekologicheskiye texnologii ochistki vozduxa v proizvodstvennix sexax [Eco-Friendly Air Purification Technologies in Industrial Workshops]. Problemi oxrani okrujayushey sredi, 32(1), 89-94. (in Russian).
  67. Vasilev, Yu.L., Krilova, A.V. (2020). Ekologicheskiye aspekti primeneniya intellektualnix sistem upravleniya dlya ochistki vozduxa v sexax [Environmental Aspects of Using Intelligent Control Systems for Air Purification in Workshops]. Vozdux, ekologiya, texnologii, 17(6), 56-60. (in Russian).

Download

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.