The article is devoted to the development of a control system for the respiratory circuit of an artificial lung ventilation (ALV) device to support the alveolar mobilization maneuver of premature newborns. Since in modern ALVs their adjustment for the maneuver of recruitment of lungs of premature newborns is carried out manually by adjusting the mechanical valve, the creation of a respiratory circuit control system will significantly reduce the time of adjustment and reduce the number of errors that occur during its implementation. The paper proposes the architecture of the respiratory circuit control system of the ALV, which consists of two control loops: one for regulating the pressure of the respiratory mixture, the second for regulating the oxygen concentration in the respiratory mixture. A simplified model of the breathing circuit control system, developed in the MATLAB Simulink dynamic simulation environment, makes it possible to evaluate the performance of this architecture. CHR method and manual tuning method based on knowledge of the system operation are used to search for the coefficients of the controllers of the control system. The Nyquist criterion is used to assess the stability of the system model. The application of the Nyquist criterion makes it possible to conclude that the breathing circuit control system is stable. A testing device of the control circuit has been developed and tested to assess the performance of the respiratory circuit control system. The conclusion has been made about the adequacy of the developed model and the operability of the proposed technical solution on the basis of testing.
Translated title of the contributionAUTOMATION OF NON-INVASIVE ARTIFICIAL VENTILATION FOR NEWBORNS BASED ON THE PROCESSING OF PRESSURE SIGNALS AND OXYGEN CONCENTRATION IN THE GAS-AIR MIXTURE
Original languageRussian
Pages (from-to)414-427
Number of pages14
JournalUral Radio Engineering Journal
Volume6
Issue number4
DOIs
Publication statusPublished - 2022

    Level of Research Output

  • VAK List

    GRNTI

  • 50.43.00

ID: 34761309