Carbon dioxide breathing machine

Abstract

The invention provides a carbon dioxide breathing machine, which belongs to the technical field of breathing machines and comprises a CO2 gas path, a normal air path, a mixed air path, an O2 gas path, a humidifying and heating device, a tail end monitoring system and an environment monitoring system, a first fan, a CO2 concentration sensor, a flow sensor and a CO2 gas path switch are arranged in the CO2 gas path; an air filtering air inlet silencer, a second fan and a differential pressure sensor are arranged in the normal air path; an O2 concentration sensor, a CO2 concentration sensor and a flow sensor are arranged in the mixed air path; an O2 gas source oxygen generator, a third fan, an O2 concentration sensor, a flow sensor and an O2 gas path switch are arranged in the O2 gas path; the tail end monitoring system comprises a breathing mask, a blood oxygen concentration tester and a PETCO2 sensor; the environment monitoring system comprises a CO2 concentration sensor, an O2 concentration sensor, a barometer and a temperature and humidity sensor.

Description

Technical Field

[0001] The invention belongs to the technical field of ventilators, and in particular relates to a carbon dioxide ventilator. Background Art

[0002] In the field of respiratory therapy and assisted sleep, ventilation therapy is currently generally performed by using compressed air from a fan. With the development of medical technology, ventilators have been widely used in the treatment of a variety of diseases such as sleep apnea syndrome, chronic obstructive pulmonary disease, and altitude sickness. In special cases, an oxygen concentrator is usually connected to the breathing tube or mask to increase the oxygen concentration and achieve the purpose of auxiliary treatment. In the prior art, ventilators mainly adjust ventilation parameters by monitoring blood oxygen saturation. However, this single monitoring method has obvious limitations. Studies have shown that even patients with chronic obstructive pulmonary disease with normal blood oxygen saturation at rest during the day may experience hypoxemia at night, and this is more significant during the acute exacerbation period. In this case, relying solely on monitoring blood oxygen saturation cannot detect potential respiratory function abnormalities in a timely manner. Especially in plateau environments, human exposure to a low oxygen environment can lead to a rapid increase in ventilation. As ventilation increases, excessive discharge of carbon dioxide in the body forms hypocarbia, which in turn causes respiratory alkalosis. This pathological change inhibits the initial enhanced ventilation response and affects the human body's adaptation process to the plateau environment. Existing ventilators lack an effective regulatory mechanism for this complex physiological process. In addition, in patients with sleep apnea syndrome, especially those with central sleep apnea associated with heart failure, frequent episodes of apnea occur due to reduced levels of carbon dioxide in the blood. This not only causes intermittent hypoxia, but also further damages heart function and increases the risk of death. Although existing technologies can improve symptoms by providing continuous positive airway pressure ventilation, they cannot fundamentally solve the problem of regulating respiratory rhythm.

[0003] The main technical problem at present is that the ventilator lacks the ability to accurately regulate the partial pressure of carbon dioxide, which may lead to complications such as carbon dioxide retention or insufficiency during long-term mechanical ventilation. This problem is particularly prominent in the treatment of high altitude environments and sleep apnea, which directly affects the treatment effect and patient prognosis. Summary of the invention

[0004] In view of this, the present invention provides a carbon dioxide ventilator, which can solve the problem that the existing ventilators have insufficient ability to regulate the carbon dioxide partial pressure.

[0005] The present invention is achieved in that:

[0006] The present invention provides a carbon dioxide respirator, which comprises: a CO2 gas circuit, a normal air circuit, a mixed air circuit, an O2 gas circuit, a humidifying and heating device, a terminal monitoring system and an environmental monitoring system; the CO2 gas circuit is provided with a first blower, a CO2 concentration sensor, a flow sensor and a CO2 circuit switch; the normal air circuit is provided with an air filter intake silencer, a second blower and a pressure difference sensor; the mixed air circuit is provided with an O2 concentration sensor, a CO2 concentration sensor and a flow sensor; the O2 gas circuit is provided with an O2 gas source oxygen generator, a third blower, an O2 concentration sensor, a flow sensor and an O2 circuit switch; the terminal monitoring system comprises a breathing mask, a blood oxygen concentration tester and a PETCO2 sensor; the environmental monitoring system comprises a CO2 concentration sensor, an O2 concentration sensor, a barometer and a temperature and humidity sensor.

[0007] On the basis of the above technical solution, a carbon dioxide breathing machine of the present invention can also be improved as follows:

[0008] Among them, one side of the CO2 gas circuit is connected to the CO2 gas source, and the other side merges with the mixed air circuit. The first fan is arranged between the CO2 concentration sensor and the flow sensor; the normal air circuit is connected to the mixed air circuit through a grille, and the second fan is arranged between the air filter intake silencer and the pressure difference sensor.

[0009] Furthermore, one side of the O2 gas circuit is connected to the O2 gas source oxygen generator, and the other side merges with the mixed air circuit. The third fan is arranged between the O2 concentration sensor and the flow sensor; the mixed air circuit is connected to the humidification and heating device.

[0010] Furthermore, the grille is composed of a plurality of guide plates arranged in parallel, and air flow channels with equal spacing are formed between the guide plates. Two ends of the guide plates are fixedly connected to the inner wall of the normal air path and the inner wall of the mixed air path respectively.

[0011] Furthermore, the humidifying and heating device includes a heating cavity and a heating unit. A water storage tank is provided in the heating cavity, and the heating unit is arranged at the bottom of the water storage tank. A delivery pipeline is provided between the heating cavity and the breathing mask.

[0012] Furthermore, the breathing mask includes a mask body and a fixing structure, the mask body is bowl-shaped, and a sealing cushion is provided on the edge; the fixing structure includes a headband and a strap buckle, and the headband is connected to both sides of the mask body through the strap buckle.

[0013] Furthermore, the CO2 gas source is a high-pressure gas cylinder, which is connected to the CO2 gas circuit switch via a pressure reducing valve; the O2 gas source oxygen generator is connected to the O2 gas circuit switch via a pressure stabilizing valve.

[0014] Furthermore, the CO2 concentration sensor, O2 concentration sensor, barometer and temperature and humidity sensor in the environmental monitoring system are all fixedly installed on the surface of the outer shell; the outer shell is composed of an upper and lower shell that are buckled together, and a partition is provided inside to separate the space into a gas path area and a monitoring area.

[0015] Furthermore, the PETCO2 sensor is arranged at the connection between the breathing mask and the humidification and heating device; the blood oxygen concentration tester includes a measuring probe and a numerical display unit, and the measuring probe is electrically connected to the numerical display unit through a signal line.

[0016] Furthermore, it also includes a main control single chip microcomputer, which is connected to the CO2 concentration sensor, O2 concentration sensor, PETCO2 sensor, blood oxygen concentration tester, temperature and humidity sensor and barometer through a terminal block; the main control single chip microcomputer is provided with a signal acquisition and output processing control module, and the signal acquisition and output processing control module is respectively connected to the first fan, the second fan and the third fan through a drive circuit; the main control single chip microcomputer is respectively connected to the CO2 gas circuit switch and the O2 gas circuit switch through an electromagnetic valve drive circuit; the measurement value of the blood oxygen concentration tester and the measurement value of the PETCO2 sensor are fed back to the signal acquisition and output processing control module, and the fan speed is adjusted by establishing a directed graph shortest path problem.

[0017] The signal acquisition and output processing control module performs the following steps to achieve precise adjustment of the first fan, the second fan, and the third fan:

[0018] S10, constructing a directed graph network structure, setting the rotation speeds of the first fan, the second fan, and the third fan as nodes in the graph, the lines between the nodes representing the conversion path of the rotation speed combination, and the weights of the lines representing the energy consumption value of the conversion process;

[0019] S20, collecting the measured values ​​of the blood oxygen concentration tester and the PETCO2 sensor, mapping the measured values ​​to the directed graph network structure, and obtaining the starting node corresponding to the current speed combination;

[0020] S30, determining a target node in a directed graph network structure according to a preset blood oxygen concentration target value and a PETCO2 concentration target value, wherein the target node corresponds to a target rotation speed combination;

[0021] S40, using the Dijkstra algorithm to calculate the shortest path from the start node to the target node, the shortest path corresponds to the optimal route for adjusting the speed of the fan, and the path length corresponds to the total energy consumption of the speed adjustment;

[0022] S50, traversing all nodes on the shortest path, recording the speed difference between every two adjacent nodes, and generating a speed adjustment sequence, wherein the speed adjustment sequence includes an adjustment direction and an adjustment amount;

[0023] S60, adjusting the speeds of the first fan, the second fan, and the third fan in steps according to the speed adjustment sequence, wherein each adjustment scheme is obtained by solving a speed adjustment equation group; the speed adjustment equation group includes a load balance equation, a power allocation equation, a ventilation volume constraint equation, and an efficiency maximization equation;

[0024] S70, collecting blood oxygen concentration and PETCO2 concentration after each speed adjustment, and defining a combined value of the blood oxygen concentration and PETCO2 concentration as an actual arrival node;

[0025] S80, determining the deviation between the actual arrival node and the path planning node, and when the deviation exceeds a threshold, taking the actual arrival node as a new starting node, and returning to step S40 to replan the path;

[0026] S90, repeating steps S40 to S80 until the deviation between the actual arrival node and the target node is less than a threshold.

[0027] The load balancing equation is used to ensure that the load distribution of the three fans is reasonable. The input includes the current speed and rated power of the three fans, and the output is the load distribution coefficient between the three fans.

[0028] The power distribution equation is used to calculate the target power values ​​of the three wind turbines, the input includes the load distribution coefficient and the target speed of the path planning, and the output is the target power value of each wind turbine;

[0029] The ventilation volume constraint equation is used to limit the range of total ventilation volume change, the input includes the difference between the current speed of the fan and the target speed, and the output is the maximum speed adjustment allowed;

[0030] The efficiency maximization equation is used to achieve the best working efficiency of the three fans. The input includes the characteristic curve parameters and the target power value of the fans. The output is the speed increment value corresponding to the best efficiency point.

[0031] The interval between two consecutive adjustments is 3 seconds, and the adjustment amount of each step does not exceed 20% of the current speed.

[0032] Furthermore, the shortest path calculation in step S40 adopts the Dijkstra algorithm, and its state transfer equation is specifically expressed as follows:

[0033] ;

[0034] In the formula, From the starting point to the node The shortest distance; For Node To Node The weight value of represents the energy consumption; For the node The adjacent node number.

[0035] The speed difference calculation in step S50 is specifically expressed as follows:

[0036] ;

[0037] In the formula, For the The speed adjustment of each fan; For the The target speed of each fan; For the The current speed of the fan; The values ​​are 1, 2, and 3, corresponding to the three fans respectively.

[0038] The speed regulation equation group in step S60 is specifically expressed as follows:

[0039] Load balancing equation:

[0040] ;

[0041] In the formula, For the Load sharing factor for each fan; For the Output power of each fan; The possible values ​​are 1, 2, or 3.

[0042] Power allocation equation:

[0043] ;

[0044] In the formula, For the The speed of the fan; is the fan characteristic curve fitting coefficient; The possible values ​​are 1, 2, or 3.

[0045] Ventilation constraint equation:

[0046] ;

[0047] In the formula, is the total ventilation volume of the system; For the The ventilation volume of each fan; For the The ventilation efficiency of each fan; The maximum ventilation volume allowed by the system.

[0048] Efficiency maximization equation:

[0049] ;

[0050] In the formula, For the The efficiency of each fan; is the output power; is the input power; is the air density; is the acceleration due to gravity; For the pressure head; For ventilation volume.

[0051] The methods for obtaining each parameter are as follows:

[0052] (1) Fan characteristic curve fitting coefficient Obtained through experiments:

[0053] Step 1: Measure the fan power at different speeds;

[0054] Step 2: Fit the cubic curve using the least squares method.

[0055] (2) Ventilation efficiency Measure by following the steps below:

[0056] Step 1: Measure the fan input power;

[0057] Step 2: Measure the outlet air flow pressure and flow rate;

[0058] Step 3: Calculate output power and efficiency.

[0059] The principle of constructing the equation group:

[0060] (1) The load balancing equation is based on the principle of multi-machine coordination to ensure system stability;

[0061] (2) The power allocation equation uses a cubic polynomial to describe the fan characteristics, covering the performance of the fan under different operating conditions;

[0062] (3) The ventilation constraint equation takes into account safety requirements to prevent over-ventilation;

[0063] (4) The efficiency maximization equation is based on the basic principles of fluid mechanics and optimizes the system energy consumption.

[0064] The above speed regulation equations introduce a load distribution coefficient to achieve dynamic balance of multiple machines; a cubic polynomial is used to describe the fan characteristics to improve the model accuracy; ventilation efficiency is taken into account to optimize system energy consumption.

[0065] Compared with the prior art, the carbon dioxide ventilator provided by the present invention effectively solves the problem of insufficient regulation of carbon dioxide partial pressure in the prior art. This is specifically reflected in the following aspects:

[0066] First, the present invention adopts a dual-parameter real-time monitoring strategy of PETCO2 and blood oxygen saturation to establish a more comprehensive respiratory function evaluation system. The real-time monitoring of the end-tidal carbon dioxide partial pressure by the PETCO2 sensor can accurately reflect the carbon dioxide level in the blood, avoiding the monitoring blind spot that may be caused by relying solely on blood oxygen saturation.

[0067] Secondly, the present invention innovatively adopts a multi-dimensional parameter optimization control strategy based on the Dijkstra algorithm to achieve coordinated regulation of the speeds of the three fans. By constructing a directed graph network that takes energy consumption into consideration, the system can find the optimal energy consumption regulation path while ensuring the treatment effect. Test data shows that compared with traditional control schemes,

[0068] Thirdly, the present invention realizes active regulation of respiratory rhythm by precisely controlling the concentration of carbon dioxide in the inhaled gas. For patients with sleep apnea, the system can adjust the gas composition in advance according to the changing trend of PETCO2 to prevent the occurrence of apnea.

[0069] Finally, the present invention integrates an environmental monitoring system, which can automatically adjust the control strategy according to environmental parameters. This feature makes the device more adaptable in plateau environments and can help users complete the physiological adaptation process faster. In summary, the present invention solves the problem that the existing ventilator has insufficient ability to regulate the partial pressure of carbon dioxide. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A schematic diagram of the structure of the carbon dioxide ventilator provided by the present invention;

[0071] Figure 2 Schematic diagram of the execution steps of the signal acquisition and output processing control module. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solution and advantages of the embodiments of the present invention more clear, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0073] like Figure 1, which is a schematic diagram of the structure of a carbon dioxide ventilator provided by the present invention, including a CO2 gas circuit 1, a normal air circuit 2, a mixed air circuit 3, an O2 gas circuit 4, a humidifying and heating device 12, a terminal monitoring system 18 and an environmental monitoring system 29. This embodiment integrates CO2 and O2 dual gas source inputs and adopts a multi-sensor real-time monitoring method to achieve precise control of respiratory gas components, and can provide personalized respiratory support solutions according to the actual needs of users.

[0074] The CO2 gas circuit 1 is made of medical-grade 316L stainless steel pipe with a diameter range of 8 to 12 mm and a wall thickness of 0.8 to 1.2 mm. The material has excellent corrosion resistance and biocompatibility, and can operate stably for a long time without oxidation or release of harmful substances. The inner wall of the pipeline is precisely polished, and the surface roughness is controlled below 0.4 microns. This smooth inner wall can effectively reduce airflow resistance and reduce energy consumption. The first fan A set in the gas circuit is driven by a brushless DC motor with a rated power of 35 to 55 watts, a maximum speed of 4500 to 5000 rpm, and a stepless speed regulation function. This configuration ensures the accuracy and stability of CO2 delivery, and the delivery volume can be adjusted in real time according to demand. The measurement range of the CO2 concentration sensor 5 is 0 to 50000 ppm, the accuracy reaches ±50ppm, and the response time is less than 60 seconds, which can accurately monitor the concentration change of CO2 in the gas circuit. The flow sensor 6 has a range of 0 to 120 cubic meters per hour and an accuracy of ±1.5%, which can accurately control the gas flow. The CO2 gas circuit switch 24 has a rated pressure of 0.5 to 1.0 MPa, a response time of less than 25 milliseconds, and good sealing and reliability.

[0075] The normal air path 2 uses food-grade PP pipes or medical-grade silicone pipes with a diameter of 15 to 20 mm. This type of material has good toughness and weather resistance and can withstand repeated bending and disinfection. The air filtration intake silencer 7 adopts a multi-layer composite filter element structure, with an outer layer of 80 to 120 grams per square meter of non-woven fabric for filtering larger particles; the middle layer is a HEPA filter with a filtration efficiency of not less than 99.97%, which can effectively block particles larger than 0.3 microns; the inner layer is an activated carbon layer with a specific surface area of ​​not less than 800 square meters per gram, which can absorb odors and harmful gases in the air. This multi-layer filtration structure not only ensures the cleanliness of the intake air, but also reduces noise through the sound absorption characteristics of the material. The second fan B adopts a centrifugal structure with a rated power of 75 to 95 watts and a maximum air volume of 600 to 700 cubic meters per hour. The differential pressure sensor 8 has a range of ±5 to 10 millibars and an accuracy of ±0.25%, which is used to monitor the degree of blockage of the filtration system.

[0076] The mixed air path 3 uses a medical-grade silicone hose with an inner diameter of 18 to 25 mm, and the material complies with the ISO 10993 biocompatibility standard. This material has good elasticity and chemical stability and can adapt to different usage environments. The measurement range of the O2 concentration sensor 9 is 0 to 100%, with an accuracy of ±1 to 2%, and can monitor the oxygen content in the mixed gas in real time. The performance parameters of the CO2 concentration sensor 10 and the flow sensor 11 are the same as those mentioned above. The design of the mixed gas path adopts a special geometric structure, the length of the mixing section is not less than 10 times the pipe diameter, and a vortex promotion device is provided to ensure the uniformity of gas mixing and the air flow distribution deviation is controlled within 5%.

[0077] The O2 gas circuit 4 is made of oxygen-specific materials, with a tube diameter of 10 to 15 mm and an inner wall surface roughness of no more than 0.4 microns. This smooth inner wall can reduce the interaction between oxygen molecules and the tube wall and reduce oxygen loss. The oxygen production range of the O2 gas source oxygen generator 19 is 0.5 to 5 liters per minute, and the oxygen concentration is 93±3%. The third fan C adopts an outer rotor structure with a rated power of 35 to 45 watts and has the characteristics of low noise and high efficiency. The technical indicators of the O2 concentration sensor 20 and the flow sensor 21 are the same as those mentioned above. The O2 gas circuit switch 23 adopts a special sealing structure to ensure safe and reliable operation in a high-concentration oxygen environment.

[0078] The outer shell of the humidifying and heating device 12 is made of transparent material and has a volume of 300 to 500 ml. The rated power of the heating element is 35 to 45 watts, and the surface temperature is precisely controlled within the range of 30 to 40 degrees Celsius. The water tank is made of corrosion-resistant material and has an automatic liquid level compensation function to maintain a stable humidification effect. The device can heat the gas to 35 to 37 degrees Celsius, and the relative humidity reaches more than 95%, which significantly improves the breathing comfort.

[0079] In the terminal monitoring system 18, the breathing mask 13 is made of medical grade silicone with a hardness of 40 to 60 Shore A. The design of the mask fully considers the principles of ergonomics and adopts anatomical contours to fit the facial contours and reduce air leakage. The measurement range of the blood oxygen concentration tester 15 is 70 to 100%, with an accuracy of ±2%. It uses a high-sensitivity photoelectric sensor to accurately monitor blood oxygen changes. The sampling flow rate of the PETCO2 sensor 16 is 45 to 55 ml per minute, and the response time is less than 3 seconds, which can achieve accurate measurement of end-tidal CO2.

[0080] The environmental monitoring system 29 adopts a distributed layout, and each sensor is connected through a digital bus to realize real-time data collection and transmission. The CO2 concentration sensor 25 and the O2 concentration sensor 26 are used to monitor the environmental gas components. The measurement range of the barometer 27 is 300 to 1250 hPa, with an accuracy of ±0.5 to 1.0 hPa, which can accurately reflect the change in altitude. The temperature measurement range of the temperature and humidity sensor 28 is -40 to 125 degrees Celsius, with an accuracy of ±0.1 to 0.2 degrees Celsius, and the humidity measurement range is 0 to 100%, with an accuracy of ±1.5 to 2%. The monitoring of these environmental parameters provides a basis for the intelligent adjustment of the equipment.

[0081] The control system uses a 32-bit processor with a main frequency of no less than 150 MHz and is equipped with sufficient storage space. The display module uses a 5 to 7-inch display screen with a resolution of no less than 800×480 and a capacitive touch screen to provide an intuitive human-computer interaction interface. The power supply uses a medical-grade switching power supply with multiple protection functions to ensure the safe and stable operation of the equipment.

[0082] This ventilator achieves precise regulation of respiratory parameters through reasonable structural design and precise control strategy. In the treatment of sleep apnea, the respiratory rhythm can be stabilized by precise control of CO2 concentration (1 to 3%), while hypoxemia can be alleviated by oxygen therapy (flow rate 0.5 to 5 liters per minute). When used in plateau environments, the system can automatically adjust ventilation parameters according to changes in air pressure to help users better adapt to low-oxygen environments. The design of the entire system fully considers safety, reliability and comfort of use, and can meet the treatment needs in different scenarios.

[0083] The innovation of the present invention is reflected in the following aspects: first, through the coordinated control of multiple gas paths, the precise adjustment of the respiratory gas composition is achieved; second, the use of a comprehensive monitoring system ensures the safety and effectiveness of the treatment process; third, through the intelligent control algorithm, the adaptive adjustment of the equipment is achieved; finally, the good human-computer interaction design improves the convenience of the equipment. These innovative designs give the present device a significant technical advantage in the field of respiratory therapy.

[0084] like Figure 2 As shown, for the specific implementation of the signal acquisition and output processing control module, the steps executed are described in detail as follows: The specific implementation of step S10 is to construct a directed graph network structure for speed regulation. First, the speeds of the three fans are set as nodes in the graph, and each node is represented by a 3D vector Indicates that , , They represent the speeds of fans 1, 2, and 3, respectively, with a speed range of 0 to 5000 rpm. The directed edges between nodes represent the conversion path from one speed combination to another. The weight of the edge is calculated using the energy consumption model, which takes into account the kinetic energy change and mechanical loss caused by the speed change. The weight calculation formula is: ,in is the moment of inertia of the kth fan, is the speed change, is the mechanical damping coefficient. The network structure is stored in an adjacency matrix. The matrix elements represent the energy consumption values ​​between the corresponding speed combinations. The elements without conversion paths are set to infinity. The network structure constructed in this way includes all possible speed adjustment schemes, laying the foundation for the subsequent search for the optimal adjustment path. When constructing the network, the speed space is discretized into a 100×100×100 grid, and the speed difference between adjacent grid points does not exceed 50rpm, ensuring the smoothness of the adjustment. The total number of nodes is controlled within 1 million to ensure computational efficiency.

[0085] The specific implementation of step S20 is to collect physiological parameters and map them to network nodes. First, blood oxygen saturation is collected by a blood oxygen concentration tester with a sampling frequency of 1Hz, and the data is subjected to median filtering to remove abnormal values. At the same time, PETCO2 concentration is collected with a sampling frequency of 1Hz, and Kalman filtering is used to eliminate measurement noise. The filtered data is converted into a fan speed combination through a mapping function, and the mapping function is implemented using fuzzy control rules. The input variables of fuzzy control are blood oxygen saturation and PETCO2 concentration, and the output variable is the target speed of the three fans. The fuzzy rules are set based on the experience of medical experts. For example, when blood oxygen is low and PETCO2 is normal, the speed of the second and third fans is increased, and the speed of the first fan is kept unchanged. Fuzzy reasoning uses the Mamdani algorithm, and the membership function uses the Gaussian function. Finally, the obtained speed combination is matched to the nearest node in the network as the starting point of path planning. During the mapping process, the normal range of blood oxygen saturation is 92% to 100%, and the normal range of PETCO2 is 35 to 45mmHg.

[0086] The specific implementation method of step S30 is to determine the target node. According to the preset target parameter range, the target physiological parameters are converted into a target speed combination using the same mapping method. The target value of blood oxygen saturation is set to 96% to 98%, and the target value of PETCO2 is set to 38 to 42 mmHg. The output limit of the fuzzy control rule ensures that the target speed is within the allowable range of the equipment. The upper limit of the speed of the first fan is 3000rpm, the second fan is 4000rpm, and the third fan is 3500rpm. At the same time, the matching relationship between the fans is considered, such as the speed of the second fan should not be less than 1.2 times the speed of the first fan, and not more than 1.5 times the speed of the third fan. The speed combination that meets the constraint conditions is used as the target node. If multiple nodes that meet the conditions appear, select the node with the lowest energy consumption at the current working point as the target node.

[0087] The specific implementation of step S40 is to calculate the shortest path based on the Dijkstra algorithm. First, initialize the distance array and the predecessor node array ,in From the starting point to the node The shortest distance, the initial value is infinite except for the starting point. A small root heap is used to store the nodes to be expanded, and the capacity of the heap does not exceed 1000 nodes. Each time the top node of the heap is taken out , scan all its adjacent nodes , according to the state transfer equation Update the shortest distance. For Node To Node The weight value of the node If the distance value of is updated, its predecessor node is updated to , and the node Add to the heap. The algorithm terminates when the heap is empty or the target node is found. Finally, the shortest path is obtained by backtracking based on the predecessor node array. The speed change between adjacent nodes on the path is limited, and the single-step speed change of any fan does not exceed 20% of the current speed.

[0088] The specific implementation of step S50 is to generate a speed adjustment sequence. The nodes on the shortest path are processed in sequence, and the speed difference between adjacent nodes is calculated. .in For the The speed adjustment of each fan, is the target speed, is the current speed. Since the dynamic characteristics of the fan need to be considered in actual control, the speed regulation is divided into several sub-intervals. The sub-intervals are divided at equal time intervals, each of which is 3 seconds. The speed change in each sub-interval adopts parabolic planning to ensure continuous acceleration. The regulation sequence includes the starting speed, end speed and transition point speed of each sub-interval. The length of the sequence is determined by the path length and the regulation constraints, usually between 10 and 30 intervals.

[0089] The specific implementation of step S60 is to solve the speed regulation equations. First, establish the load balance equation ,in is the load sharing factor, is the output power. The power allocation equation uses a cubic polynomial model ,in , , , is the fan characteristic coefficient. The ventilation constraint equation is ,in is the total ventilation volume, For ventilation efficiency, is the maximum allowable ventilation volume. The efficiency maximization equation is ,in is the air density, is the acceleration due to gravity, is the pressure head. The equations are solved by Newton iteration method, and the initial value of iteration is provided by the solution of the previous moment. The iteration convergence criterion is that the maximum relative error between two adjacent iteration solutions is less than 0.1%. The fan characteristic constraint is introduced in the solution process to ensure that the working point is in the stable area of ​​the fan characteristic curve.

[0090] The specific implementation method of step S70 is to perform real-time parameter monitoring. After each speed adjustment is completed, wait for 1 second for the system to reach stability, and then collect blood oxygen concentration and PETCO2 data within 300ms. The data collection adopts a sampling rate of 100Hz, and the power frequency interference is removed by digital filtering. The processed data is subjected to outlier detection, and data points exceeding 3 times the standard deviation are eliminated. Then the mean is calculated as the eigenvalue of the current working point. The eigenvalue is converted into the actual arrival node in the speed space through the aforementioned fuzzy mapping method. The influence of measurement error is considered in the mapping process. The measurement error of blood oxygen concentration is within ±2%, and the measurement error of PETCO2 is within ±3mmHg.

[0091] The specific implementation method of step S80 is to evaluate the control effect. The deviation value between the actual arrival node and the path planning node is calculated, and the deviation value includes the node coordinate deviation and the corresponding physiological parameter deviation. The node coordinate deviation is measured by Euclidean distance, and the threshold is set to 5% of the maximum speed. The physiological parameter deviation is measured by weighted square sum, the weight of blood oxygen concentration deviation is 0.7, and the weight of PETCO2 deviation is 0.3. The threshold of the total deviation value is set to 0.15. When any deviation exceeds the threshold, the actual arrival node is used as the new starting node, and the path is replanned by returning to step S40. During the deviation evaluation process, the system stability is checked at the same time. If the deviation does not show a decreasing trend after three consecutive adjustments, the diagonal elements of the weight matrix are increased to improve the robustness of the control.

[0092] The specific implementation of step S90 is iterative optimization control. Repeat steps S40 to S80 until the deviation between the actual arrival node and the target node is less than the threshold. Adaptive step control is adopted in the iterative process, and the initial step is 80% of the maximum allowable adjustment amount, and then dynamically adjusted according to the deviation change trend. If the deviation decreases continuously, the step length is kept unchanged; if the deviation fluctuates, the step length is reduced to 0.8 times the current value; if the deviation increases continuously, the step length is reduced to 0.5 times the current value. At the same time, a time constraint is introduced. If it has not converged for more than 90 seconds, the deviation threshold is increased to 1.2 times the original value. During the entire control process, the system parameters are always kept within the safe range, the blood oxygen saturation is not less than 90%, and the PETCO2 does not exceed 50mmHg. When the system reaches the target state, it switches to the steady-state control mode, and the path planning is re-triggered only when the parameters change significantly.

[0093] Specifically, the principle of the present invention is: based on the physiological mechanism of human respiratory regulation, active regulation of respiratory function is achieved by precisely controlling the composition of the inhaled gas. Carbon dioxide, as the most important chemical regulator of the respiratory center, affects respiratory activity through two pathways: one is to stimulate peripheral chemoreceptors and affect respiratory rhythm through nerve reflexes; the other is to directly act on central chemoreceptors through the blood-brain barrier. The present invention is based on this physiological mechanism and achieves precise regulation of respiratory function by precisely controlling the concentration of carbon dioxide in the inhaled gas.

[0094] In the design of control strategy, the present invention adopts a multi-objective optimization method based on graph theory. By mapping the speed combination of the three fans into network nodes, the change process of the system state is converted into a path search problem in the network. This mathematical model not only considers the achievement of control objectives, but also includes energy consumption as the weight of the edge into the optimization range, ensuring the economy of the control process.

[0095] In terms of specific implementation, the present invention uses fuzzy control rules to map physiological parameters to the fan speed space. This mapping relationship fully considers the nonlinear characteristics of human respiratory regulation. At the same time, the optimal regulation path is found through the Dijkstra algorithm to ensure the stability of the regulation process and minimize energy consumption. The system also introduces an adaptive step control mechanism, which can dynamically adjust the regulation strategy according to the control effect, thereby improving the robustness of the system.

[0096] From a physiological point of view, the solution of the present invention avoids respiratory alkalosis that may be caused by traditional ventilation therapy by maintaining an appropriate carbon dioxide partial pressure. At the same time, preventive regulation prevents apnea caused by low carbon dioxide levels. This regulatory mechanism is coordinated with the body's own respiratory regulation mechanism, so a better treatment effect can be achieved.

[0097] A specific embodiment 1 of the present invention is provided below: a carbon dioxide ventilator, comprising a CO2 gas circuit 1, a normal air circuit 2, a mixed air circuit 3, an O2 gas circuit 4, a humidifying and heating device 12, a terminal monitoring system 18 and an environmental monitoring system 29. This embodiment achieves precise control of respiratory gas components by integrating CO2 and O2 dual gas source inputs and adopting a multi-sensor real-time monitoring method, and can provide a personalized respiratory support plan according to the actual needs of the user.

[0098] The CO2 gas circuit 1 is made of medical grade 316L stainless steel pipe with a diameter range of 8-12mm and a wall thickness of 0.8-1.2mm. The first fan A set in the gas circuit can be a brushless DC fan with a rated power range of 35-55W, a maximum speed of 4500-5000rpm, and a stepless speed regulation function. The fan models available include D1225C series, G1225M series or R1225M series, etc. The measurement range of the CO2 concentration sensor 5 should be 0-50000ppm, the accuracy requirement is ±(50ppm+5% reading), and the response time is required to be less than 60s. NDIR double-beam sensor or photoacoustic spectrum sensor can be selected, and the specific model can be selected from SCD40 series, K33 series or CM1106 series, etc. The range of the flow sensor 6 is 0-120m³ / h, and the accuracy requirement is ±1.5%. Thermal mass flow sensor or vortex flow sensor can be selected, such as FLOWSIC series, VA series or D6F series, etc. CO2 gas circuit switch 24 can use solenoid valve, rated pressure requirement is 0.5-1.0MPa, response time requirement is within 25ms, VXZ series, 2W series or PU220 series can be selected.

[0099] Normal air path 2 uses food-grade PP pipes or medical-grade silicone pipes with a diameter of 15-20mm. The air filter intake silencer 7 uses a multi-layer composite filter element structure, with the outer layer being a primary filter layer (using 80-120g / m² non-woven fabric), the middle layer being a HEPA filter (filtration efficiency requirement ≥99.97%@0.3μm), and the inner layer being an activated carbon layer (specific surface area requirement ≥800m² / g). The second fan B should preferably use a centrifugal fan with a rated power range of 75-95W and a maximum air volume requirement of 600-700m³ / h. Models such as R3G series, D4E series or G3G series can be selected. The range of the differential pressure sensor 8 requires ±5-10mbar and the accuracy requires ±0.25%. HSC series, MS series or DPS series can be selected.

[0100] The mixed air path 3 uses a medical grade silicone hose with an inner diameter of 18-25mm, and the material must comply with the ISO 10993 biocompatibility standard. The measurement range of the O2 concentration sensor 9 is required to be 0-100%, and the accuracy is required to be ±1-2%. Electrochemical sensors or fluorescence quenching sensors can be selected, such as the R-17 series, KE series or OOM series. The technical requirements of the CO2 concentration sensor 10 and the flow sensor 11 are the same as those mentioned above. The geometric design of the mixed air path requires that the length of the mixing section is not less than 10 times the pipe diameter, and the deviation of the uniformity of the air flow distribution is controlled within 5%.

[0101] O2 gas circuit 4 uses copper tubes or stainless steel tubes for oxygen, with a diameter of 10-15mm and an inner wall surface roughness requirement of Ra≤0.4μm. The oxygen production range of O2 gas source / oxygen generator 19 is required to be 0.5-5L / min, and the oxygen concentration is 93%±3%. Molecular sieve pressure swing adsorption oxygen generators can be selected, such as 5L series, 8L series or 10L series. The third fan C can use an external rotor fan with a rated power of 35-45W, and can use K3G series, D3G series or R3G series. The technical requirements of O2 concentration sensor 20 and flow sensor 21 are the same as above. O2 gas circuit switch 23 uses a solenoid valve, and the technical requirements are the same as those of CO2 gas circuit switch.

[0102] The shell of the humidifying and heating device 12 is made of transparent PC or acrylic material, with a volume of 300-500ml. The heating element is a PTC ceramic heating plate or a silicone heating plate, with a rated power of 35-45W and a surface temperature control range of 30-40°C. The water tank can be made of stainless steel liner or food-grade PP material, with automatic water replenishment function. The performance index requirements of the device are: gas outlet temperature 35-37°C, relative humidity ≥95%.

[0103] In the terminal monitoring system 18, the breathing mask 13 is made of medical grade silicone with a hardness range of 40-60 Shore A. The measurement range of the blood oxygen concentration tester 15 is required to be 70-100%, the accuracy is required to be ±2%, and a reflective or transmissive pulse oximeter sensor can be used. The sampling flow rate of the PETCO2 sensor 16 is required to be 45-55ml / min, and the response time is required to be <3s. A mainstream or sidestream sensor can be used, such as the NomoLine series, LoFlo series or Capnostat series.

[0104] The sensors of the environmental monitoring system 29 are connected via RS485 bus or CAN bus. The technical requirements of CO2 concentration sensor 25 and O2 concentration sensor 26 are the same as above. The measurement range of barometer 27 is required to be 300-1250hPa, and the accuracy is required to be ±0.5-1.0hPa. BMP series, MS series or HP series can be selected. The temperature and humidity sensor 28 has a temperature measurement range of -40 to 125℃, an accuracy of ±0.1-0.2℃, a humidity measurement range of 0-100%RH, and an accuracy of ±1.5-2%RH. SHT series, HTS series or AM series can be selected.

[0105] The control system can use a 32-bit ARM Cortex-M4 or M7 core processor, with a main frequency of no less than 150MHz, a Flash capacity of ≥1MB, and a RAM capacity of ≥128KB. The display screen uses a 5-7 inch LCD (resolution no less than 800×480) and is equipped with a capacitive touch screen. The power supply requires a medical-grade switching power supply, with an input of 220V AC, an output of 24V DC / 8-12A and 12V DC / 3-5A, and must have overvoltage, overcurrent, short circuit and other protection functions.

[0106] The connection between each gas path adopts a quick connector, the material can be selected from 316L stainless steel or brass, and the sealing ring is made of fluororubber or EPDM rubber. After system integration, the recommended size range of the whole machine is 350-450mm×250-350mm×200-300mm (length×width×height), and the weight is controlled at 7-9kg. All materials must meet the biocompatibility requirements of medical devices and can withstand conventional disinfectant wiping.

[0107] This embodiment 1 achieves the regulation of respiratory rhythm through the precise delivery and monitoring of CO2 gas; relieves hypoxia symptoms through real-time regulation of O2 concentration; and improves the adaptability of the device in different scenarios through monitoring and compensation of environmental parameters. In the treatment of sleep apnea syndrome, the device can stabilize the respiratory rhythm through precise control of CO2 concentration (1-3%), and relieve hypoxemia through oxygen therapy (flow rate 0.5-5L / min). When used in plateau environments, the device can automatically adjust ventilation parameters according to changes in air pressure to help users better adapt to low-oxygen environments. The multiple redundant settings of each sensor ensure the reliability of system operation, and multiple safety protection measures ensure safe use.

[0108] Embodiment 2: This embodiment provides a specific implementation scheme of a carbon dioxide ventilator device for treating sleep apnea syndrome. The device is mainly used in respiratory departments of medical institutions to treat patients with moderate to severe sleep apnea syndrome.

[0109] The carbon dioxide ventilator in this embodiment adopts a modular design, mainly including four parts: gas supply system, hybrid control system, monitoring system and human-computer interaction system. The gas supply system includes a CO2 gas source, an oxygen generator and an air filter device, the hybrid control system includes three independently controlled fans and corresponding sensor arrays, the monitoring system includes blood oxygen and end-tidal CO2 monitoring devices, and the human-computer interaction system includes a touch screen and an alarm device.

[0110] In terms of the gas supply system, the CO2 gas source uses a medical-grade 40L high-pressure gas cylinder, the CO2 purity reaches 99.99%, and the cylinder pressure is 15MPa. The pressure reducing valve adopts a two-stage pressure reducing structure, the first stage reduces the pressure to 0.8MPa, and the second stage reduces it to 0.2MPa. The oxygen concentrator adopts molecular sieve pressure swing adsorption technology, the rated oxygen production is 3L / min, and the oxygen concentration can reach 93%±3%. The air filtration device adopts a three-stage filtration structure, including primary, medium and high efficiency filters, with filtration accuracies of 10μm, 5μm and 0.3μm respectively.

[0111] In terms of the hybrid control system, all three fans are centrifugal fans driven by brushless DC motors. The specific parameters are shown in the following table.

[0112] Table 1 Fan parameter specifications

[0113]

[0114] The sensor system configuration is shown in the following table.

[0115] Table 2 Sensor configuration parameters

[0116]

[0117] In terms of the monitoring system, blood oxygen saturation monitoring uses a reflective pulse oximeter with a measurement range of 35%-100% and an accuracy of ±2% within the range of 70%-100%. End-tidal CO2 monitoring uses an infrared absorption sensor with a measurement range of 0-100mmHg and an accuracy of ±2mmHg. The monitoring data sampling frequency is 100Hz and the data update rate is 1Hz.

[0118] The humidification and heating system uses a PTC heating element with a heating power of 200W, a water tank capacity of 500ml, and a maximum humidification capacity of 400ml / h. The heating temperature can be adjusted within the range of 30-40℃, and the relative humidity can reach 95%RH. The delivery pipeline is made of medical grade silicone material, and the inner wall is equipped with a heating wire to maintain the gas temperature and prevent the formation of condensed water.

[0119] The breathing mask is made of medical grade silicone and is available in three sizes: S, M, and L. The edge of the mask adopts a double-layer airbag sealing structure, and the inner layer inflation pressure is 0.2kPa. The headband is made of elastic nylon, with a width of 25mm, and the tightness can be adjusted through a quick adjustment buckle.

[0120] The gas mixing control adopts a three-stage adjustment strategy. The first stage is the startup stage, in which the system gradually adjusts the mixed gas to the initial setting value within 60 seconds. The second stage is the stable operation stage, in which the system makes real-time fine adjustments based on the patient's blood oxygen saturation and end-tidal CO2 level. The third stage is the end stage, in which the system gradually adjusts the mixed gas back to normal air composition within 30 seconds. The specific operating parameters are shown in the following table.

[0121] Table 3 Gas mixing control parameters

[0122]

[0123] In actual operation, the system automatically adjusts according to the patient's physiological indicators. The target value of blood oxygen saturation is set to 95%, and the allowable fluctuation range is ±2%. The target value of end-tidal CO2 is set to 40mmHg, and the allowable fluctuation range is ±5mmHg. When the monitored value exceeds the range, the system automatically adjusts the composition and flow of the mixed gas.

[0124] The device of this embodiment also includes multiple security protection mechanisms. Mainly including the following aspects:

[0125] 1. Air pressure protection: When the pipeline pressure exceeds 40kPa, the system automatically reduces the fan speed. When the pressure exceeds 50kPa, the system immediately shuts down and alarms.

[0126] 2. Concentration protection: When the CO2 concentration exceeds 3.5%, the system automatically cuts off the CO2 supply and alarms. When the O2 concentration is lower than 19%, the system automatically increases the output of the oxygen generator.

[0127] 3. Flow protection: When the total flow is lower than 15L / min, the system automatically increases the fan speed. When the flow exceeds 80L / min, the system automatically reduces the fan speed.

[0128] 4. Temperature protection: When the airway temperature exceeds 42°C, the system automatically reduces the heating power. When the temperature is lower than 28°C, the system automatically increases the heating power.

[0129] The device of this embodiment has the following advantages in clinical application:

[0130] 1. High gas mixing accuracy: CO2 concentration control accuracy reaches ±0.1%, O2 concentration control accuracy reaches ±1%, meeting clinical use requirements.

[0131] 2. Fast response speed: The system responds to changes in blood oxygen saturation in less than 3 seconds, and to changes in end-tidal CO2 in less than 2 seconds.

[0132] 3. Good noise control: Under normal working conditions, the equipment noise level is controlled below 45dB and does not affect the patient's sleep.

[0133] 4. High safety: Multiple protection mechanisms ensure the safety of the treatment process and effectively prevent accidents.

[0134] 5. Easy to operate: It adopts touch screen control, friendly interface, simple operation steps, and is suitable for medical staff.

[0135] In the actual operation test, the device of this embodiment treated 10 patients with moderate to severe sleep apnea for 7 days and achieved good results. The various indicators during the treatment process are shown in the following table.

[0136] Table 4 Clinical application effect data table

[0137]

[0138] This embodiment realizes a safe and reliable carbon dioxide ventilator device through reasonable structural design and parameter configuration. The device has good user experience and safety performance while ensuring the treatment effect. The practical value of the device in the treatment of sleep apnea syndrome has been verified through clinical application.

[0139] Embodiment 3: Optimization embodiment of carbon dioxide ventilator based on intelligent control algorithm

[0140] Based on Example 2, this embodiment focuses on optimizing the design of the signal acquisition and output processing control module, and achieves precise adjustment of the fan speed and optimization of system energy consumption by introducing an intelligent control algorithm. The improvements mainly include the following aspects.

[0141] 1. System control structure optimization

[0142] This embodiment adopts a hierarchical control structure, including three levels: decision layer, coordination layer and execution layer. The decision layer is responsible for determining the control target according to the patient's physiological parameters, the coordination layer is responsible for calculating the optimal control strategy, and the execution layer is responsible for implementing specific control actions. The functional configuration of each level is shown in the following table.

[0143] Table 5 Control system hierarchy table

[0144]

[0145] 2. Directed Graph Network Construction

[0146] This embodiment constructs a directed graph network containing 125 nodes, each node representing a specific speed combination of three wind turbines. The connection between nodes is established according to the following rules:

[0147] 1. The speed difference between adjacent nodes does not exceed 20% of the current speed. 2. The weight of the connection between nodes is determined by the energy consumption value, and the calculation formula is the weighted sum of the total power and the speed change. 3. Each node is connected to a maximum of 26 other nodes to ensure that the search space is moderate.

[0148] The specific node distribution parameters are shown in the following table.

[0149] Table 6 Network node distribution parameter table

[0150]

[0151] 3. Fan Characteristic Curve Modeling

[0152] The operating parameters of the fan at different speeds were obtained through experimental measurement, and the characteristic curve was obtained by cubic polynomial fitting. The measurement data and fitting results are shown in the following table.

[0153] Table 7 Fan characteristic curve measurement data table

[0154]

[0155] 4. Control Algorithm Implementation

[0156] This embodiment uses an iterative optimization method to achieve accurate control of the fan speed. The main steps include:

[0157] 1. Status parameter collection: System operating parameters are collected every 3 seconds, including blood oxygen saturation, end-tidal CO2, fan speed, etc.

[0158] 2. Target value determination: Set the target parameter range according to treatment requirements, blood oxygen saturation 95%±2%, end-tidal CO2 40±5mmHg.

[0159] 3. Path planning: Use the Dijkstra algorithm to calculate the shortest path and determine the fan speed adjustment sequence.

[0160] 4. Speed ​​adjustment: gradually adjust the fan speed according to the calculation results, and the adjustment range shall not exceed 20% each time.

[0161] The specific control parameter settings are shown in the following table.

[0162] Table 8 Control parameter configuration table

[0163]

[0164] 5. System Performance Comparison

[0165] This embodiment was tested in comparison with embodiment 1, mainly examining the three aspects of control accuracy, energy consumption and treatment effect. The test results are shown in the following table.

[0166] Table 9 System performance comparison data table

[0167]

[0168] VI. Clinical application effect

[0169] This example conducted a 14-day treatment test on 15 patients and compared the treatment effect with that of Example 1. The results showed that this example significantly improved the treatment effect and patient comfort. The specific data are shown in the following table.

[0170] Table 10 Clinical effect comparison data table

[0171]

[0172] 7. System Reliability Verification

[0173] This embodiment has been subjected to a reliability test for 30 consecutive days, and the test contents include control accuracy maintenance capability, system stability and fault response capability. The test results are shown in the following table.

[0174] Table 11 System reliability test data table

[0175]

[0176] 8. Energy saving effect analysis

[0177] This embodiment significantly reduces system energy consumption by optimizing the control algorithm. The specific energy saving effect is shown in the following table.

[0178] Table 12 System energy saving effect data table

[0179]

[0180] From the above data comparison, it can be seen that this embodiment has achieved significant improvements in many aspects:

[0181] 1. Improved control accuracy: The control accuracy of CO2 and O2 concentrations has been improved by 50%, and the system response is more accurate.

[0182] 2. Reduced energy consumption: By optimizing the control algorithm, the system's average daily energy consumption was reduced by 33.3%, significantly reducing operating costs.

[0183] 3. Improved treatment outcomes: The treatment achievement rate increased by 10.9%, and the average time to achieve the goal was shortened by 37%.

[0184] 4. User experience optimization: Patient comfort scores increased by 14.1%, indicating that the system runs more smoothly.

[0185] 5. System reliability: Through 30 days of continuous operation test, it is proved that the system has good reliability and stability.

[0186] This embodiment achieves an overall improvement in system performance based on Embodiment 2 by introducing an intelligent control algorithm. This solution not only improves the treatment effect, but also reduces energy consumption, and has good application value and promotion prospects. Practice has proved that this control solution can meet clinical use requirements and provide better technical support for the treatment of sleep apnea syndrome.

[0187] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A carbon dioxide breathing machine, characterized in that: include: CO2 gas circuit, normal air circuit, mixed air circuit, O2 gas circuit, humidifying and heating device, terminal monitoring system and environmental monitoring system; the CO2 gas circuit is provided with a first fan, a CO2 concentration sensor, a flow sensor and a CO2 circuit switch; the normal air circuit is provided with an air filter intake silencer, a second fan and a pressure difference sensor; the mixed air circuit is provided with an O2 concentration sensor, a CO2 concentration sensor and a flow sensor; the O2 gas circuit is provided with an O2 gas source oxygen generator, a third fan, an O2 concentration sensor, a flow sensor and an O2 circuit switch; the terminal monitoring system includes a breathing mask, a blood oxygen concentration tester and a PETCO2 sensor; the environmental monitoring system includes a CO2 concentration sensor, an O2 concentration sensor, a barometer and a temperature and humidity sensor.

2. A carbon dioxide breathing machine according to claim 1, characterized in that: One side of the CO2 gas circuit is connected to the CO2 gas source, and the other side merges with the mixed air circuit. The first fan is arranged between the CO2 concentration sensor and the flow sensor; the normal air circuit is connected to the mixed air circuit through a grille, and the second fan is arranged between the air filter intake silencer and the pressure difference sensor.

3. A carbon dioxide breathing machine according to claim 2, characterized in that: One side of the O2 gas circuit is connected to the O2 gas source oxygen generator, and the other side is merged with the mixed air circuit. The third fan is arranged between the O2 concentration sensor and the flow sensor; the mixed air circuit is connected to the humidification and heating device.

4. A carbon dioxide breathing machine according to claim 3, characterized in that: The grille is composed of a plurality of guide plates arranged in parallel, and air flow channels with equal spacing are formed between the guide plates. Two ends of the guide plates are fixedly connected to the inner wall of the normal air path and the inner wall of the mixed air path respectively.

5. A carbon dioxide breathing machine according to claim 4, characterized in that: The humidifying and heating device comprises a heating cavity and a heating unit. A water storage tank is arranged in the heating cavity, and the heating unit is arranged at the bottom of the water storage tank. A delivery pipeline is arranged between the heating cavity and the breathing mask.

6. A carbon dioxide breathing machine according to claim 5, characterized in that: The breathing mask includes a mask body and a fixing structure. The mask body is bowl-shaped and has a sealing cushion on the edge. The fixing structure includes a headband and a strap buckle. The headband is connected to both sides of the mask body through the strap buckle.

7. A carbon dioxide breathing machine according to claim 6, characterized in that: The CO2 gas source is a high-pressure gas cylinder, which is connected to the CO2 gas circuit switch through a pressure reducing valve; the O2 gas source oxygen generator is connected to the O2 gas circuit switch through a pressure stabilizing valve.

8. A carbon dioxide breathing machine according to claim 7, characterized in that: The CO2 concentration sensor, O2 concentration sensor, barometer and temperature and humidity sensor in the environmental monitoring system are all fixedly mounted on the surface of the shell; the shell is composed of an upper and lower shell body that are buckled together, and a partition is arranged inside to separate the space into a gas path area and a monitoring area.

9. A carbon dioxide breathing machine according to claim 8, characterized in that: The PETCO2 sensor is arranged at the connection between the breathing mask and the humidifying and heating device; the blood oxygen concentration tester includes a measuring probe and a numerical display unit, and the measuring probe is electrically connected to the numerical display unit through a signal line.

10. A carbon dioxide breathing machine according to claim 9, characterized in that: It also includes a main control single chip microcomputer, which is connected to the CO2 concentration sensor, O2 concentration sensor, PETCO2 sensor, blood oxygen concentration tester, temperature and humidity sensor and barometer through a terminal block; the main control single chip microcomputer is provided with a signal acquisition and output processing control module, and the signal acquisition and output processing control module is respectively connected to the first fan, the second fan and the third fan through a drive circuit; the main control single chip microcomputer is respectively connected to the CO2 gas circuit switch and the O2 gas circuit switch through an electromagnetic valve drive circuit; the measured value of the blood oxygen concentration tester and the measured value of the PETCO2 sensor are fed back to the signal acquisition and output processing control module, and the fan speed is adjusted by establishing a directed graph shortest path problem.

Images