Control system, control method, controller of medical device and medical device

Abstract

The application relates to the technical field of medical equipment control, and discloses a control system, a control method, a controller and medical equipment of medical equipment, the control system comprising: a first sensor configured to collect inhaled end gas parameters including an inhaled end temperature and an inhaled end relative humidity; a second sensor configured to collect a pipe wall temperature; and a controller connected with the first sensor and the second sensor respectively and configured to: calculate a loop dew point temperature according to the inhaled end temperature and the inhaled end relative humidity; calculate a condensation risk value according to the loop dew point temperature and the pipe wall temperature; when the condensation risk value is less than a first preset risk threshold, control a heating element and a humidification assembly to work cooperatively so that the inhaled end temperature and the inhaled end relative humidity reach corresponding target parameter values; or otherwise, execute a preset hierarchical protection strategy. The scheme solves the problem that condensate influences normal operation of a loop due to the inability to perceive condensation risks, and improves the safety and stability of loop operation.

Description

Technical Field

[0001] This application relates to the field of medical device control technology, and in particular to a control system, control method, controller and medical device for medical equipment. Background Technology

[0002] Breathing equipment is typically equipped with a heating and humidification system to heat and humidify the gas delivered to the inhalation end. Existing heating and humidification solutions mainly include two types: mechanically integrated and independent humidifiers, both of which are controlled based on preset values ​​or manual adjustment.

[0003] The drawback of the above solution is that when the temperature of the tubing wall in the breathing equipment's circuit is lower than the dew point temperature of the inhaled gas, water vapor will condense on the inner wall of the tubing, forming condensate. Because the open-loop control scheme does not monitor the temperature and humidity at the inhalation end, nor does it monitor the tubing wall temperature, the system cannot detect whether condensate is forming or has already accumulated. When condensate accumulates to a certain level, it increases tubing resistance, affects the circuit's ventilation function, and in severe cases, condensate can backflow into related equipment in the breathing circuit, impacting the normal operation of the circuit system.

[0004] Therefore, how to detect and control the risk of condensation in the breathing circuit has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] Based on this, the present application provides a control system, control method, controller, and medical device for medical equipment, in order to solve the problem that the risk of condensation in the breathing circuit cannot be detected because the temperature and humidity at the inhalation end of the breathing circuit and the temperature of the tube wall are not monitored during the heating and humidification control process, which leads to the formation of condensate and affects the normal operation of the circuit.

[0006] In a first aspect, embodiments of this application provide a control system for a medical device, the control system comprising: The first sensor is configured to collect inhalation end gas parameters, including inhalation end temperature and inhalation end relative humidity. The second sensor is configured to collect the pipe wall temperature; A controller is connected to both the first sensor and the second sensor; wherein the controller is configured as follows: Calculate the circuit dew point temperature based on the inhalation end temperature and the relative humidity at the inhalation end; Calculate the condensation risk value based on the dew point temperature of the circuit and the pipe wall temperature; When the condensation risk value is less than the first preset risk threshold, the heating element of the medical device is controlled to heat, and the humidification component of the medical device is controlled to humidify, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values. When the condensation risk value is greater than or equal to the first preset risk threshold, a preset graded protection strategy is executed.

[0007] Secondly, embodiments of this application provide a control method for a medical device, applied to a controller, the control method comprising: Acquire inhalation end gas parameters and tube wall temperature, wherein the inhalation end gas parameters include inhalation end temperature and inhalation end relative humidity; Calculate the circuit dew point temperature based on the inhalation end temperature and the relative humidity at the inhalation end; Calculate the condensation risk value based on the dew point temperature of the circuit and the pipe wall temperature; When the condensation risk value is less than the first preset risk threshold, the heating element of the medical device is controlled to heat, and the humidification component of the medical device is controlled to humidify, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values. When the condensation risk value is greater than or equal to the first preset risk threshold, a preset graded protection strategy is executed.

[0008] Thirdly, embodiments of this application provide a controller, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the control method for the medical device as described in the second aspect above.

[0009] Fourthly, embodiments of this application provide a medical device, the medical device comprising: Heating elements and humidification components; and, The control system of the medical device described in the first aspect above.

[0010] In the control system, control method, controller, and implementation scheme of the aforementioned medical device, the controller acquires measured data of the loop temperature, humidity, and tube wall temperature through a first sensor that collects the inhalation end temperature and relative humidity in real time, and a second sensor that collects the tube wall temperature. Based on this, the controller calculates the condensation risk value according to the inhalation end temperature and relative humidity, and the difference between the loop dew point temperature and the tube wall temperature. This transforms the qualitative judgment of the loop condensation risk into a continuously quantified risk indicator, achieving quantitative perception of condensation risk. Furthermore, when the condensation risk value is below a threshold, the controller uses the inhalation end temperature and humidity as feedback to control the heating element and humidification component. By implementing closed-loop operation, the heating power and humidification amount are adaptively adjusted according to the measured values ​​of the suction end temperature and humidity. When the condensation risk value reaches a threshold, a graded protection strategy is implemented to match the strength of the protection action with the severity of the condensation risk. This allows the actions of the heating element and humidification component to be adjusted in real time based on the measured suction end temperature and humidity and pipe wall temperature in the circuit. Thus, this application solves the problem in existing solutions where the lack of monitoring of suction end temperature and humidity and pipe wall temperature prevents the detection of condensation risk, leading to the formation of condensate that affects the normal operation of the circuit. It achieves quantitative perception and graded prevention and control of condensation risk based on the measured circuit status, improving the safety and stability of circuit operation. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the control system of a medical device in one embodiment of this application; Figure 2 This is a schematic diagram of a processing flow of the control system of a medical device in one embodiment of this application; Figure 3 This is a flowchart illustrating a method for controlling a medical device according to one embodiment of this application; Figure 4 This is a schematic diagram of the controller in one embodiment of this application; Figure 5 This is a schematic diagram of the structure of a medical device in one embodiment of this application; Figure 6 This is a schematic diagram of the structure of a control device for a medical device in one embodiment of this application. Detailed Implementation

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0014] This application provides a control system 10 for a medical device. The control system 10 can be applied to scenarios involving heating and humidifying the respiratory circuit.

[0015] Please see Figure 1 The control system 10 of the medical device may include a first sensor 11, a second sensor 12, and a controller 13, etc.

[0016] The first sensor 11 is configured to collect inhalation end gas parameters, which may include inhalation end temperature and inhalation end relative humidity.

[0017] As an example, the first sensor 11 can be positioned in the inspiratory branch of the breathing circuit near the patient end (e.g., in the tubing before the gas enters the patient's airway) to monitor the inhaled gas temperature and relative humidity in real time. The first sensor 11 may include an integrated temperature and humidity sensor capable of simultaneously outputting temperature and relative humidity signals. The inhaled temperature refers to the actual temperature of the gas in the inspiratory branch of the breathing circuit, measured in °C. The inhaled relative humidity refers to the actual relative humidity of the gas in the inspiratory branch of the breathing circuit, measured in %.

[0018] The second sensor 12 is configured to collect the tube wall temperature. Preferably, the second sensor 12 can be located on the inner wall of the inspiratory branch tubing near the patient's Y-connector (approximately 10-15 cm from the Y-connector), at the end of the heating wire coverage area. The tube wall temperature refers to the actual temperature of the inspiratory branch tubing wall, measured in °C. The second sensor 12 may include an NTC thermistor or a PT1000 platinum resistance thermometer. The second sensor 12 can directly contact the inner surface of the tubing wall to obtain an accurate tube wall temperature value. Tube wall temperature is a key parameter for determining whether condensation will form on the inner wall of the tubing. For example, when the tube wall temperature is lower than the dew point temperature of the inhaled gas, water vapor will condense on the inner wall of the tubing to form condensate.

[0019] The reason for choosing the above installation location is that: the area near the patient is where condensation is most likely to form, and the inhaled gas has the lowest temperature and the highest relative humidity at this location. Therefore, measuring the tube wall temperature at this location can most directly reflect the critical conditions for condensation formation. In addition, this location is at the end of the heating wire coverage area, which can directly reflect the heating and heat preservation effect of the heating wire on the tube wall.

[0020] As an alternative, a temperature sensor can be placed in the middle of the tubing and at the patient's end, and the weighted average of the two measurements can be taken as the tubing wall temperature. If no tubing wall temperature sensor is installed in the tubing, the tubing wall temperature can be estimated by establishing a heat balance model based on ambient temperature, heating wire power, and gas flow rate. No limitation is made here.

[0021] Please see Figure 2 The controller 13 is connected to the first sensor 11 and the second sensor 12 respectively; wherein the controller 13 is configured to perform the following steps: S1: Calculate the loop dew point temperature based on the suction end temperature and suction end relative humidity; S2: Calculate the condensation risk value based on the loop dew point temperature and pipe wall temperature.

[0022] As an example, the loop dew point temperature refers to the temperature at which the gas is cooled to saturation (i.e., relative humidity reaches 100%) while maintaining a constant water vapor content, under the current intake gas temperature and relative humidity conditions. It is denoted as... The unit is °C. That is, the loop dew point temperature is a calculated value uniquely determined by the current suction gas temperature and relative humidity; it characterizes the critical temperature at which water vapor begins to condense under the current gas conditions. (Pipe wall temperature) This refers to the actual temperature of the inspiratory branch tube wall in the breathing circuit, which is collected by the second sensor 12 and is expressed in °C. The difference between the tube wall temperature and the circuit dew point temperature directly determines whether condensation will occur in the circuit. That is, when the tube wall temperature is lower than the circuit dew point temperature, water vapor will condense on the tube wall surface to form condensate.

[0023] The loop dew point temperature can be calculated using the Magnus-Tetens approximation formula, specifically: in: in, Inhalation temperature, Here, denoted as ...

[0024] The condensation risk value R is a quantitative indicator used to characterize the probability of condensation occurring in the breathing circuit under current operating conditions, ranging from 0 to 1. A condensation risk value close to 1 indicates an extremely high probability of condensation; a condensation risk value close to 0 indicates an extremely low probability of condensation. The condensation risk value is calculated as follows: First, calculate the circuit dew point temperature. and pipe wall temperature The second difference between Then, obtain the temperature tolerance value. The temperature tolerance value is determined based on the first accuracy parameter of the first sensor 11 and the second accuracy parameter of the second sensor 12. Finally, based on the second difference and the temperature tolerance value, a sigmoid function mapping is performed to calculate the condensation risk value R. Specifically, the following formula can be used: Where R is the condensation risk value. The circuit dew point temperature. Here, Δ represents the pipe wall temperature, and Δ represents the preset temperature tolerance. This is the sigmoid function.

[0025] The preset temperature tolerance can range from 1℃ to 3℃, with a preferred value of 2℃.

[0026] The preset temperature tolerance can be determined based on the following: the typical error of the NTC temperature sensor in the range of 30℃ to 40℃ is ±0.3℃ to ±0.5℃; the cumulative error of the two sensors (first sensor 11 and second sensor 12) is approximately ±0.7℃; the temperature change of the heating wire within one control cycle is approximately 0.3℃ to 0.5℃; a safety margin of approximately 1℃ is retained based on the above errors and delays, totaling approximately 2℃. The physical meaning of the temperature tolerance Δ is: when the temperature difference... exist Within a certain range, the probability of condensation changes continuously with the temperature difference, rather than abruptly, thus allowing the condensation risk value to smoothly reflect the gradual change in the likelihood of condensation.

[0027] For example, if the first sensor 11 collects the inhalation end temperature relative humidity at the inhalation end The second sensor 12 collected the pipe wall temperature. Preset temperature tolerance The calculation process for the loop dew point temperature is as follows: Further, calculate the condensation risk value: After mapping by the sigmoid function, the condensation risk value R≈0.69, indicating that the current condensation risk is high, and it is necessary to decide whether to implement a protection strategy based on this risk value.

[0028] Thus, step S1 calculates the loop dew point temperature using the Magnus-Tetens approximation formula based on the suction end temperature and relative humidity, transforming the saturation state of water vapor in the gas from an indirectly observable physical property into a calculable, quantifiable temperature value. Step S2 maps the temperature difference between the loop dew point temperature and the pipe wall temperature to a condensation risk value between 0 and 1 using the sigmoid function, transforming the condensation probability from a qualitative judgment into a continuously quantified risk indicator. The loop dew point temperature... As an input parameter for step S2, the pipe wall temperature They jointly participate in the calculation of the condensation risk value, which is... This will serve as the basis for decisions in subsequent steps S3 and S4, providing fundamental data for the quantitative assessment and tiered prevention and control of condensation risk.

[0029] S3: When the condensation risk value is less than the first preset risk threshold, control the heating element of the medical device to heat and control the humidification component of the medical device to humidify, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values. S4: When the condensation risk value is greater than or equal to the first preset risk threshold, the preset graded protection strategy is executed.

[0030] As an example, the medical device can be a respiratory device (such as anesthesia machines, ventilators, etc.). This medical device may include a heating element and a humidification assembly. The heating element may include a heating wire disposed in the inspiratory branch for heating the gas in the circuit through resistance heating (e.g., heating the inhaled gas). The humidification assembly may include a humidification evaporation assembly disposed in the breathing circuit (e.g., a humidification canister and its internal heater) for heating water in the humidification canister to generate water vapor, thereby supplementing the inhaled gas with water vapor and increasing the relative humidity of the gas.

[0031] First preset risk threshold This is a pre-set safety boundary value for condensation risk, ranging from 0.5 to 0.8. When the condensation risk value... When the temperature is below the first preset risk threshold, it indicates that the current circuit has a low risk of condensation and the heating and humidification functions can operate normally. Target parameter values ​​may include target temperature values. and target humidity value , representing the desired target inhaled gas temperature and target inhaled gas relative humidity, respectively. The target temperature value ranges from 32℃ to 37℃, and the target humidity value ranges from 60% to 100%. The target temperature and target humidity values ​​can be preset fixed values, or adaptive values ​​that are corrected based on dynamic parameters such as patient body temperature and / or fresh gas flow rate. For example, the target temperature value can be the actual control target obtained by correcting the preset temperature value based on the patient's body temperature, and the target humidity value can be the actual control target obtained by correcting the preset humidity value based on the patient's body temperature and fresh gas flow rate.

[0032] In one possible implementation, when the condensation risk value is less than a first preset risk threshold, the heating element is controlled to heat, and the humidification component is controlled to humidify, so that the suction end temperature reaches the target temperature value, and the suction end relative humidity reaches the target humidity value. When the condensation risk value... Greater than or equal to the first preset risk threshold When this value is displayed, it indicates a high risk of condensation in the current circuit, requiring protective measures to prevent condensation formation or accumulation. Both control paths described above are based on the condensation risk value output from step S2. The system makes decisions and achieves adaptive control and hierarchical prevention driven by condensation risk, which not only ensures the stable output of intake gas temperature and humidity, but also effectively prevents condensate from affecting the normal operation of the loop system.

[0033] In summary, based on the above technical solution, by using the first sensor 11 to collect the inhalation end temperature and relative humidity in real time, and the second sensor 12 to collect the tube wall temperature, the controller 13 can obtain the measured data of the loop temperature and humidity and the tube wall temperature. Based on this, the controller 13 calculates the condensation risk value according to the inhalation end temperature and relative humidity, and the difference between the loop dew point temperature and the tube wall temperature, transforming the loop condensation risk from a qualitative judgment into a continuously quantified risk indicator, thus achieving quantitative perception of condensation risk. Furthermore, when the condensation risk value is lower than a threshold, the controller 13 uses the inhalation end temperature and humidity as feedback to control the heating element and humidification component to execute a closed loop. The system adaptively adjusts the heating power and humidification amount based on the measured values ​​of the suction end temperature and humidity. When the condensation risk value reaches a threshold, a graded protection strategy is implemented, matching the strength of the protection action with the severity of the condensation risk. This allows the actions of the heating element and humidification component to be adjusted in real time based on the measured suction end temperature and humidity and pipe wall temperature in the circuit. Thus, this application solves the problem in existing solutions where the lack of monitoring of suction end temperature and humidity and pipe wall temperature prevents the detection of condensation risk, leading to the formation of condensate that affects the normal operation of the circuit. It achieves quantitative perception and graded prevention and control of condensation risk based on the measured circuit status, improving the safety and stability of circuit operation.

[0034] In one embodiment, the target parameter values ​​include a target temperature value and a target humidity value.

[0035] Please see Figure 1 The control system 10 also includes a third sensor 14 and a fourth sensor 15.

[0036] The third sensor 14 is configured to collect the patient's body temperature. For example, the third sensor 14 can be any one of an esophageal temperature sensor, a bladder temperature sensor, or a skin temperature sensor. The unit of the patient's body temperature is °C. The fourth sensor 15 is configured to collect fresh gas flow rate. For example, the fourth sensor 15 can be a gas flow sensor used to measure the flow rate of fresh gas delivered to the breathing circuit. Fresh gas flow rate refers to the volume of fresh gas delivered by the medical device to the breathing circuit per unit time, measured in liters per minute (L / min). The magnitude of the fresh gas flow rate directly affects the residence time of the gas in the humidifier and the heat and moisture exchange efficiency in the tubing.

[0037] The controller 13 is also connected to the third sensor 14 and the fourth sensor 15; in controlling the heating element of the medical device to heat and the humidification component of the medical device to humidify so that the inhalation end temperature and relative humidity reach the corresponding target parameter values, it is also configured to perform the following steps: S31: Obtain preset temperature and preset humidity values; S32: Correct the preset temperature value based on the patient's body temperature to obtain the target temperature value; S33: Correct the preset humidity value based on the patient's body temperature and fresh air flow rate to obtain the target humidity value; S34: Determine the first control parameter of the heating element based on the suction end temperature and the target temperature value; S35: Determine the second control parameter of the humidification component based on the relative humidity at the inhalation end and the target humidity value; S36: Control the heating element to heat according to the first control parameter so that the suction end temperature reaches the target temperature value; S37: Control the humidification component to humidify according to the second control parameter so that the relative humidity at the inhalation end reaches the target humidity value.

[0038] As an example, the preset temperature and preset humidity values ​​are pre-set benchmark target values. The preset temperature value can be 34°C, and the preset humidity value can be 85%. The patient's body temperature is collected by the third sensor 14, in °C. The fresh air flow rate is collected by the fourth sensor 15, in liters per minute (L / min). The first control parameter is a control signal used to control the output of the heating element, which can be a pulse width modulation duty cycle, in %. The second control parameter is a control signal used to control the output of the humidification component, which can be a power value, in watts (W).

[0039] As can be seen, this embodiment achieves linkage between patient status and heating control by adjusting the temperature target based on the patient's body temperature; and enables humidification control to adaptively compensate for changes in humidification demand under different operating conditions by adjusting the humidity target based on the patient's body temperature and fresh air flow.

[0040] Specifically, the process of correcting the preset temperature value based on the patient's body temperature to obtain the target temperature value includes the following steps: S321: When the patient's body temperature is lower than the first preset body temperature threshold, calculate the first difference between the patient's body temperature and the first preset body temperature threshold. S322: Determine the first temperature increment based on the first difference and the first preset coefficient; S323: Obtain the target temperature value based on the preset temperature value and the first temperature increment.

[0041] As an example, the first preset body temperature threshold is a boundary value used to determine whether a patient needs additional warming, such as 36.0°C. When a patient's body temperature is below 36.0°C, it indicates that the patient is at risk of hypothermia, and the temperature of the inhaled gas needs to be appropriately increased to compensate for the patient's heat loss. The first preset coefficient is a proportional coefficient used to convert the body temperature difference into a temperature increment, such as 0.5, which physically means the temperature increment that needs to be compensated for every 1°C of insufficient body temperature. The first temperature increment is equal to the first difference multiplied by the first preset coefficient. The target temperature value is equal to the preset temperature value plus the first temperature increment.

[0042] For example, if the preset temperature value is 34℃, the first preset body temperature threshold is 36.0℃, the first preset coefficient is 0.5, and the patient's body temperature is 35.8℃, then the first difference = 36.0 - 35.8 = 0.2℃, the first temperature increment = 0.2 × 0.5 = 0.1℃, and the target temperature value = 34 + 0.1 = 34.1℃. When the patient's body temperature is higher than the second preset body temperature threshold, such as 37.5℃, the target temperature value is taken as the preset temperature value and is not increased further to avoid overheating the febrile patient.

[0043] As can be seen, this embodiment determines the temperature increment by multiplying the body temperature difference by a preset coefficient, thus achieving linear adaptive correction of the target inhalation temperature as the patient's body temperature changes. When the patient's body temperature drops, the target inhalation temperature automatically increases to compensate for heat loss; when the patient's body temperature is normal or high, the target inhalation temperature remains unchanged at the preset value, effectively avoiding overheating.

[0044] Specifically, the process of adjusting the preset humidity value based on the patient's body temperature and fresh air flow to obtain the target humidity value includes the following steps: S331: Calculate the change in saturated humidity corresponding to the target temperature value; S332: Obtain the intermediate humidity value based on the preset humidity value and the change in saturated humidity; S333: Get the current fresh air flow rate; S334: Determine the second humidity increment based on the fresh air flow rate and the second preset coefficient; S335: Obtain the target humidity value based on the intermediate humidity value and the second humidity increment.

[0045] As an example, the change in saturated humidity refers to the change in saturated water vapor content caused by a change in the target temperature. When the target temperature increases, the amount of water vapor the gas can hold increases. To maintain constant absolute humidity, the relative humidity target needs to be increased accordingly; this increase is the humidity increment corresponding to the change in saturated humidity. The second preset coefficient is a proportionality coefficient used to convert fresh air flow rate into humidity increment, with units of % / L / min. The higher the fresh air flow rate, the shorter the residence time of the gas in the humidifier, resulting in a reduced mixing time between water vapor and gas, and a corresponding decrease in humidification efficiency. Therefore, it is necessary to appropriately increase the humidity target to compensate for insufficient humidification. The intermediate humidity value equals the preset humidity value plus the humidity increment corresponding to the change in saturated humidity. The second humidity increment equals the current fresh air flow rate multiplied by the second preset coefficient. The target humidity value equals the intermediate humidity value plus the second humidity increment.

[0046] For example, if the preset humidity value is 85%, and the target temperature value increases from 34°C to 34.4°C, the humidity increment corresponding to the change in saturated humidity is 2%, then the intermediate humidity value is 87%. If the current fresh air flow rate is 3L / min, and the second preset coefficient is 2% / L / min, then the second humidity increment is 6%, and the target humidity value is 93%.

[0047] As can be seen, this embodiment achieves comprehensive adaptive correction of the target humidity at the inhalation end as the target temperature and fresh air flow rate change with each other through two layers of correction: the change in saturated humidity and the compensation for air flow rate. When the target temperature increases, the change in saturated water vapor content caused by the temperature increase is compensated by the change in saturated humidity, maintaining a constant absolute humidity. When the fresh air flow rate increases, the second humidity increment compensates for the decrease in humidification efficiency caused by the increase in air flow rate, ensuring the effectiveness and stability of humidification control under different operating conditions.

[0048] It should be noted that the controller 13 is also configured to acquire the end-tidal carbon dioxide partial pressure (EtCO2), measured in mmHg. When the patient's end-tidal carbon dioxide partial pressure is higher than a preset threshold, it indicates that the patient may have insufficient ventilation. In this case, to avoid intervening in ventilation, the controller 13 does not actively adjust the current target temperature and humidity values; that is, it keeps the current target temperature and humidity values ​​unchanged and records the patient's end-tidal carbon dioxide partial pressure (e.g., recording the patient's current end-tidal carbon dioxide partial pressure in the system log) for subsequent trend analysis and clinical assessment of ventilation status, without participating in real-time correction of temperature and humidity targets. The partial pressure of carbon dioxide at the end of expiration can be collected by an end-expiratory carbon dioxide sensor (not shown in the figure). The end-expiratory carbon dioxide sensor can be set in the expiratory circuit to monitor the concentration of carbon dioxide in the patient's exhaled gas in real time, and there is no limitation here.

[0049] Specifically, in determining the first control parameters of the heating element based on the suction end temperature and the target temperature value, either of the following two methods can be used: Method 1: S341A1: Calculate the first deviation between the inhalation temperature and the target temperature value; S342A1: The first deviation value is proportionally amplified to obtain the first proportional component; S343A1: Based on the first integral coefficient, the first deviation value is integrated and accumulated to obtain the first integral component; S344A1: Determine the first control parameters of the heating element based on the first proportional component and the first integral component.

[0050] As an example, the first deviation value equals the target temperature value minus the suction end temperature. When the suction end temperature is lower than the target temperature value, the first deviation value is positive, indicating that the heating power needs to be increased; when the suction end temperature is higher than the target temperature value, the first deviation value is negative, indicating that the heating power needs to be decreased. Proportional amplification processing multiplies the first deviation value by a first proportional coefficient to obtain a first proportional component. This first proportional component is proportional to the current deviation; the larger the deviation, the larger the output proportional component, used for rapid response to the current temperature deviation. Integral accumulation processing multiplies the accumulated amount of the first deviation value over time by a first integral coefficient to obtain a first integral component. This first integral component is proportional to the accumulated amount of the deviation over time, used to eliminate steady-state temperature residuals. The first control parameter is the sum of the first proportional component and the first integral component, and the output is the power duty cycle of the heating element, ranging from 0 to 100%. To prevent overshoot caused by integral saturation, when the integral component exceeds the preset upper limit or falls below the preset lower limit, the integral component is clamped to the preset boundary value; at the same time, the output of the first control parameter is limited to ensure that it does not exceed the range of 0 to 100%, so as to protect the heating element from overload damage.

[0051] For example, assuming the target temperature is 34.0℃ and the current suction end temperature is 33.2℃, the controller 13 calculates a first deviation value as 34.0℃ minus 33.2℃, resulting in 0.8℃, indicating that the current temperature is 0.8℃ away from the target value. The controller 13 multiplies this deviation value by a first proportional coefficient of 10 to obtain a first proportional component of 8.0%. This component reflects the immediate demand for heating power due to the current deviation; that is, the larger the deviation, the more power needs to be increased. Simultaneously, the controller 13 multiplies the cumulative deviation over time (assumed to be 0.5℃·s) by... With a first integral coefficient of 0.3, a first integral component of 0.15% is obtained. This component reflects the cumulative demand for heating power due to the persistent deviation over a period of time. Even if the current deviation is decreasing, the integral component will still maintain a certain output to eliminate the steady-state residual. The controller 13 adds the first proportional component of 8.0% to the first integral component of 0.15% to obtain the first control parameter of 8.15%, which indicates that the heating element should be heated with a power duty cycle of 8.15% in the current control cycle. Thus, the determination of the first control parameter of the heating element is completed.

[0052] It should be noted that you should refer to [link / reference]. Figure 1 The control system 10 also includes a fifth sensor 16. The fifth sensor 16 is configured to collect ambient temperature data. For example, the fifth sensor 16 can be a temperature sensor, which can be installed outside the breathing circuit, on the surface of the anesthesia machine or ventilator chassis, to monitor the ambient temperature around the equipment, measured in °C.

[0053] In practical applications, the intake temperature is also affected by various factors such as changes in fresh air flow rate, ambient temperature, and the humidification-heating coupling effect. Specifically, when the fresh air flow rate increases, more low-temperature gas enters the circuit and carries away heat, causing the intake temperature to drop; when the ambient temperature decreases, the heat dissipation from the pipeline to the environment increases, which also causes the intake temperature to drop; when the humidification power increases, more water evaporation requires the absorption of latent heat of vaporization, which also leads to a drop in the intake temperature.

[0054] To counteract the effects of the aforementioned disturbances on temperature control, the controller 13 can also introduce the following feedforward compensation based on the above proportional-integral control: The first compensation component is determined based on the change in fresh air flow rate between the current and previous times and the first feedforward coefficient, to compensate for the heat disturbance caused by the change in fresh air flow rate. The second compensation component is determined based on the change in ambient temperature between the current and previous times and the second feedforward coefficient, to compensate for the heat dissipation disturbance caused by the change in ambient temperature. The third compensation component is determined based on the change between the second control parameter (humidification component power) and the second control parameter at the previous time and the third feedforward coefficient, to compensate for the temperature drop disturbance caused by evaporative heat absorption when the humidification power changes. The controller 13 superimposes the first proportional component, the first integral component, and the above three compensation components to jointly determine the first control parameter of the heating element, so that the adjustment of the heating power can be compensated in advance before the disturbance affects the suction end temperature, further improving the response speed and anti-interference capability of temperature control under multi-disturbance conditions.

[0055] For example, assuming the current fresh air flow rate is 3.0 L / min, and the previous flow rate was 2.5 L / min, the change in flow rate is 0.5 L / min, and the first feedforward coefficient is 1.2% / (L / min), then the first compensation component is 0.6%; the current ambient temperature is 22℃, and the previous temperature was 23℃, the change in ambient temperature is -1℃, and the second feedforward coefficient is 0.3% / ℃, then the second compensation component is -0.3%; the current value of the second control parameter is 60W, and the previous value was 55W, the change is 5W, and the third feedforward coefficient is 0.15% / W, then the third compensation component is 0.75%; superimposing the first proportional component of 8.0% and the first integral component of 0.15%, the final first control parameter is 9.2%. Thus, the determination of the first control parameter of the heating element is completed.

[0056] Method 2: S341A3: Acquires the current inhalation temperature, target temperature, inhalation relative humidity, fresh air flow rate, ambient temperature, current power of the heating element, and current power of the humidification component; S342A3: The current inhalation temperature, target temperature, inhalation relative humidity, fresh air flow rate, ambient temperature, current power of the heating element, current power of the humidification component, and the above parameters from the previous moment are used as input features and input into the pre-trained temperature change prediction model. S343A3: Outputs the predicted temperature change through a temperature change prediction model; S344A3: Obtain the feedforward compensation power value corresponding to the predicted temperature change; S345A3: Calculates the first deviation between the inhalation temperature and the target temperature value; S346A3: Determine the first control parameters of the heating element based on the first deviation value and the feedforward compensation power value.

[0057] As an example, the current inhalation temperature refers to the gas temperature value collected by the first sensor 11 during the current control cycle, in °C. The target temperature value refers to the desired inhalation gas temperature target. The inhalation relative humidity refers to the inhalation gas relative humidity value during the current control cycle, in %. The fresh air flow rate refers to the fresh air flow rate value collected by the fourth sensor 15 during the current control cycle, in L / min. The ambient temperature refers to the ambient temperature value collected by the fifth sensor 16 during the current control cycle, in °C. The current power of the heating element refers to the power duty cycle of the heating element at the current moment, in %. The current power of the humidification component refers to the output power value of the humidification component at the current moment, in W.

[0058] The temperature change prediction model is a machine learning model pre-trained using historical operating data to predict the change in inlet temperature over a predetermined time period (e.g., the next 5 seconds) under current operating conditions. The temperature change prediction model can employ model structures such as XGBoost, LightGBM, or neural networks. The model's input features include the current inlet temperature, target temperature, inlet relative humidity, fresh air flow rate, ambient temperature, current power of the heating element, current power of the humidifier, and historical values ​​of these parameters at historical moments (e.g., 1 second, 5 seconds, 10 seconds ago). Among these, the current power of the heating element is the most direct factor affecting temperature change; increased power leads to increased heating and a higher temperature. The current power of the humidifier is used to capture the coupled perturbation of temperature caused by evaporative heat absorption when humidification power changes; increased power leads to increased evaporative heat absorption and a lower temperature. The fresh air flow rate characterizes the change in heat carried in by the gas; increased flow rate means more low-temperature gas enters the circuit, carrying away heat and causing a lower temperature. The ambient temperature characterizes changes in the pipeline's heat dissipation conditions; decreased ambient temperature leads to increased heat dissipation from the pipeline to the environment and a lower temperature. Before using the model, operational data under different working conditions are collected as training samples, and the actual observed temperature changes are used as labels to train the model until the prediction error of the model on the validation set meets the preset accuracy requirements.

[0059] After the temperature change prediction model outputs the predicted temperature change, the feedforward compensation power value is determined based on this predicted temperature change. When the predicted temperature change is negative (predicting a future temperature decrease), the feedforward compensation power value is positive, increasing the heating power in advance to offset the predicted temperature drop; when the predicted temperature change is positive (predicting a future temperature increase), the feedforward compensation power value is negative, decreasing the heating power in advance to avoid the predicted temperature rise. The formula for calculating the feedforward compensation power value is: Feedforward compensation power value = Predicted temperature change × Feedforward compensation coefficient, where the feedforward compensation coefficient is determined through experimental calibration, and its physical meaning is the percentage of heating power required to compensate for each 1℃ predicted temperature change. The first deviation value is equal to the target temperature value minus the suction end temperature, used for feedback control. The first control parameter is the feedforward compensation power value plus the first proportional component and the first integral component (the first proportional component and the first integral component are obtained from the first deviation value through proportional-integral control), that is, the feedback control part is responsible for eliminating the current deviation, and the feedforward compensation part is responsible for offsetting the predicted disturbance in advance.

[0060] For example, suppose the current intake temperature is 33.2℃, the target temperature is 34.0℃, the relative humidity at the intake is 80%, the fresh air flow rate is 3.0L / min, the previous fresh air flow rate was 2.5L / min, the ambient temperature is 22℃, the current power of the heating element is 40%, and the current power of the humidification component is 60W. The controller 13 inputs the above parameters into a pre-trained temperature change prediction model. Based on the input characteristics, the model predicts that the temperature will drop by 0.3℃ within the next 5 seconds. This is because the fresh air flow rate increases from 2.5L / min to 3.0L / min, allowing more low-temperature gas to enter the loop and carry away heat, while the humidification component operates at 60W, generating an evaporative heat absorption effect. With a feedforward compensation coefficient of 5% / ℃, the feedforward compensation power value is 0.3×5=1.5%. Simultaneously, the controller 13 calculates the first deviation value as 34.0-33.2=0.8℃, and after proportional-integral control, obtains a proportional component of 8.0% and an integral component of 0.15%. The first control parameter is a feedforward compensation power value of 1.5%, plus a proportional component of 8.0% and an integral component of 0.15%, totaling 9.65%. The proportional and integral components are responsible for eliminating the current 0.8℃ temperature deviation, while the feedforward compensation power value is responsible for increasing the heating power by 1.5% in advance to offset the upcoming cooling disturbance. This completes the determination of the first control parameter for the heating element.

[0061] As can be seen, this embodiment, by introducing model-based feedforward predictive compensation, enables the heating element's power adjustment to predict and compensate for temperature changes in advance based on multivariate inputs. This allows the heating power to be adjusted before disturbances such as changes in fresh air flow rate and humidification power actually affect the intake temperature, overcoming the hysteresis of pure feedback control, which only responds after a temperature deviation has occurred. The first control parameter consists of a feedforward compensation section and a feedback control section. The feedforward section is responsible for offsetting predicted disturbances in advance, while the feedback section is responsible for eliminating residual steady-state deviations. Their combined operation ensures that the intake temperature can respond quickly and remain accurately stable near the target temperature value even under complex multivariate coupling conditions.

[0062] Specifically, in determining the second control parameter of the humidification component based on the relative humidity at the inhalation end and the target humidity value, either of the following two implementation methods can be adopted: Method 1: S341B1: Calculate the second deviation between the relative humidity at the inhalation end and the target humidity value; S342B1: The second deviation value is proportionally amplified to obtain the second proportional component; S343B1: Based on the second integral coefficient, the second deviation value is integrated and accumulated to obtain the second integral component; S344B1: Determine the second control parameter of the humidification component based on the second proportional component and the second integral component.

[0063] The second integral coefficient is smaller than the first integral coefficient.

[0064] As an example, the second deviation value is equal to the target humidity value minus the relative humidity at the intake end. When the relative humidity at the intake end is lower than the target humidity value, the second deviation value is positive, indicating that the humidification power needs to be increased; when the relative humidity at the intake end is higher than the target humidity value, the second deviation value is negative, indicating that the humidification power needs to be decreased. The proportional amplification process multiplies the second deviation value by a second proportional coefficient to obtain a second proportional component. This second proportional component is proportional to the current deviation; the larger the deviation, the larger the output proportional component, used to quickly respond to the current humidity deviation. The integral accumulation process multiplies the accumulated amount of the second deviation value over time by a second integral coefficient to obtain a second integral component. This second integral component is proportional to the accumulated amount of the deviation over time, used to eliminate steady-state humidity residuals. The second control parameter is the sum of the second proportional component and the second integral component, and the output is the power value of the humidification component, ranging from 0 to the maximum power value. The second integral coefficient is smaller than the first integral coefficient because the response speed of the humidification system is slower than that of the temperature system. A smaller integral coefficient can prevent overshoot and oscillation caused by integral saturation, ensuring that the response characteristics of the humidification controller 13 match the physical response characteristics of the humidification system. To prevent overshoot caused by integral saturation, when the second integral component exceeds the preset upper limit or falls below the preset lower limit, the second integral component is clamped to the preset boundary value; at the same time, the output of the second control parameter is limited to ensure that it does not exceed the maximum power value of the humidification component, so as to protect the humidification component from overload damage.

[0065] For example, assuming a target humidity of 93% and a current relative humidity at the inhalation end of 80%, the second deviation is 93% minus 80%, resulting in 13%. The second proportional coefficient is set to 3, so the second proportional component is 13% multiplied by 3, yielding 39%. The integral term is the cumulative deviation over time multiplied by the integral coefficient. In the initial stage, the cumulative integral is 2%·s, and the second integral coefficient is set to 0.05, so the second integral component is 2%·s multiplied by 0.05, yielding 0.1%. The second control parameter is 39% plus 0.1%, resulting in 39.1%, indicating that the humidification component humidifies at 39.1% of its maximum power. Assuming the maximum power of the humidification component is 200W, the actual power is 200W multiplied by 39.1%, yielding 78.2W. This completes the determination of the second control parameter for the humidification component. Since the second integral coefficient is smaller than the first integral coefficient, the response speed of the humidification controller 13 is slower than that of the temperature controller 13, which matches the slower physical response characteristics of the humidification system and effectively prevents overshoot and oscillation in humidification control.

[0066] It should be noted that in practical applications, the relative humidity at the intake end is also affected by changes in the fresh air flow rate. Specifically, when the fresh air flow rate increases, the residence time of the gas in the humidifier is shortened, the mixing time between water vapor and gas is reduced, the humidification efficiency decreases, and the relative humidity at the intake end decreases.

[0067] To counteract the impact of the aforementioned disturbances on humidity control, in addition to the proportional-integral control described above, controller 13 can also introduce the following feedforward compensation: The first compensation component is determined based on the change in fresh air flow rate between the current and previous moments and the first feedforward coefficient (humidification channel) to compensate for the humidification efficiency disturbance caused by the change in fresh air flow rate. The controller 13 superimposes the second proportional component, the second integral component, and the first compensation component to jointly determine the second control parameters of the humidification component. This allows the adjustment of humidification power to be compensated in advance before the change in air flow rate affects the relative humidity at the inhalation end, further improving the response speed and anti-interference capability of humidity control under conditions of frequent changes in air flow rate.

[0068] For example, if the current fresh air flow rate is 3.0 L / min, and the previous flow rate was 2.5 L / min, the change in air flow rate is 0.5 L / min. If the first feedforward coefficient (humidification channel) is 10 W / (L / min), then the first compensation component is 5 W; the second proportional component is 78 W; the second integral component is 0.2 W; and the summed second control parameter is 83.2 W. Thus, the determination of the second control parameter for the humidification component is complete.

[0069] Method 2: S341B3: Obtain the current relative humidity at the inhalation end, target humidity value, inhalation end temperature, fresh air flow rate, and current power of the humidification component; S342B3: The current relative humidity at the inhalation end, the target humidity value, the inhalation end temperature, the fresh air flow rate, the current power of the humidification component, and the above parameters from the previous moment are used as input features and input into the pre-trained humidity change prediction model. S343B3: Outputs the predicted humidity change through a humidity change prediction model; S344B3: Obtain the feedforward compensation humidity value corresponding to the predicted humidity change; S345B3: Calculate the second deviation between the relative humidity at the inhalation end and the target humidity value; S346B3: Determine the second control parameter of the humidification component based on the second deviation value and the feedforward compensation humidity value.

[0070] As an example, the current relative humidity at the inhalation end refers to the relative humidity value of the inhalation gas collected by the first sensor 11 during the current control cycle, expressed as a percentage (%). The target humidity value refers to the desired relative humidity target for the inhalation gas. The inhalation temperature refers to the gas temperature value collected by the first sensor 11 during the current control cycle, expressed as a temperature (°C). The fresh air flow rate refers to the fresh air flow rate value collected by the fourth sensor 15 during the current control cycle, expressed as a flow rate (L / min). The current power of the humidification component refers to the output power value of the humidification component at the current moment, expressed as a power (W).

[0071] The humidity change prediction model is a machine learning model pre-trained using historical operating data to predict the change in relative humidity at the inlet end within a preset time period (e.g., the next 5 seconds) under current operating conditions. The humidity change prediction model can employ model structures such as XGBoost, LightGBM, or neural networks. The model's input features include the current relative humidity at the inlet end, the target humidity value, the inlet temperature, the fresh air flow rate, the current power of the humidifier, and the historical values ​​of these parameters at historical moments (e.g., the previous 1 second, 5 seconds, and 10 seconds). Among these, the current power of the humidifier is the most direct factor affecting humidity change; increased power leads to increased vapor production and a rise in relative humidity. The inlet temperature captures the indirect impact of temperature-induced changes in saturated water vapor content on relative humidity—increased temperature leads to increased saturated water vapor content, resulting in a decrease in relative humidity even if the absolute humidity remains constant. The fresh air flow rate characterizes the impact of changes in gas residence time on humidification efficiency; increased flow rate shortens the gas residence time in the humidifier, reducing humidification efficiency and leading to a decrease in relative humidity. Before using the model, operational data under different working conditions are collected as training samples, and the actual observed humidity changes are used as labels to train the model until the prediction error of the model on the validation set meets the preset accuracy requirements.

[0072] After the humidity change prediction model outputs the predicted humidity change, a feedforward compensation humidity value is determined based on the predicted humidity change. When the predicted humidity change is negative (predicting a future decrease in humidity), the feedforward compensation humidity value is positive, and the humidification power is increased in advance to compensate for the predicted humidity decrease; when the predicted humidity change is positive (predicting a future increase in humidity), the feedforward compensation humidity value is negative, and the humidification power is reduced in advance to avoid the predicted humidity increase. The formula for calculating the power adjustment corresponding to the feedforward compensation humidity value is: Feedforward compensation power = Predicted humidity change × Feedforward compensation coefficient, where the feedforward compensation coefficient is determined through experimental calibration, and its physical meaning is the amount of humidification power adjustment required to compensate for every 1% change in predicted humidity, in W / %. The second deviation value is equal to the target humidity value minus the relative humidity at the intake end, and is used for feedback control. The second control parameter is the feedforward compensation power plus the second proportional component and the second integral component (the second proportional component and the second integral component are obtained from the second deviation value through proportional-integral control), that is, the feedback control part is responsible for eliminating the current humidity deviation, and the feedforward compensation part is responsible for offsetting the predicted humidity disturbance in advance.

[0073] For example, suppose the current relative humidity at the inhalation end is 80%, the target humidity is 93%, the inhalation end temperature is 34°C, the fresh air flow rate is 3.0 L / min, the previous fresh air flow rate was 2.0 L / min, and the current power of the humidification component is 70 W. The controller 13 inputs these parameters into a pre-trained humidity change prediction model. Based on the input characteristics, the model predicts that the relative humidity will decrease by 4% within the next 5 seconds. This is because the fresh air flow rate increases from 2.0 L / min to 3.0 L / min, shortening the residence time of the gas in the humidifier and reducing the humidification efficiency. The feedforward compensation coefficient is 3 W / %, so the feedforward compensation power is 4 × 3 = 12 W. Simultaneously, the controller 13 calculates the second deviation value as 93 - 80 = 13%, and through proportional-integral control, obtains a second proportional component of 39% (corresponding to 78 W) and a second integral component of 0.1% (corresponding to 0.2 W). The second control parameter is the feedforward compensation power of 12 W plus 78 W plus 0.2 W, totaling 90.2 W. The proportional and integral components are responsible for eliminating the current 13% humidity deviation, while the feedforward compensation power is responsible for increasing the humidification power by 12W in advance to offset the upcoming humidity drop disturbance. This completes the determination of the second control parameter for the humidification component.

[0074] As can be seen, this embodiment, by introducing model-based feedforward prediction compensation, enables the humidification component's power adjustment to predict humidity change trends in advance based on multivariate inputs and apply compensation. The humidification power is adjusted before disturbances such as changes in fresh air flow actually affect the relative humidity at the inhalation end, overcoming the hysteresis defect of pure feedback control, which can only respond after humidity deviations have occurred. The second control parameter consists of a feedforward compensation section and a feedback control section. The feedforward section is responsible for offsetting predicted humidity disturbances in advance, while the feedback section is responsible for eliminating residual steady-state deviations. Their collaborative work ensures that the relative humidity at the inhalation end can still respond quickly and remain accurately stable near the target humidity value even under complex multivariate coupling conditions.

[0075] In one embodiment, the preset graded protection strategy includes a first-level protection strategy and a second-level protection strategy. The first-level protection strategy controls the heating element to increase the pipe wall temperature and / or controls the humidification component to reduce humidification output. The second-level protection strategy controls the humidification component to cut off humidification output, controls the heating element to operate at full power, and / or increases the fresh air flow rate.

[0076] When the condensation risk value is greater than or equal to the first preset risk threshold, the controller 13 is also configured to execute the following steps in the preset graded protection strategy: S41: Obtain a second preset risk threshold, which is greater than the first preset risk threshold; S42: When the condensation risk value is greater than or equal to the first preset risk threshold and less than the second preset risk threshold, the first-level protection strategy is executed; S43: When the condensation risk value is greater than or equal to the second preset risk threshold, the second-level protection strategy is executed.

[0077] As an example, the first preset risk threshold The first preset risk threshold is a pre-defined safety boundary value for condensation risk, ranging from 0.5 to 0.8, used to distinguish between low-risk and medium-to-high-risk ranges. The second preset risk threshold, R_high, is a pre-defined high-risk boundary value, ranging from 0.8 to 0.9, used to distinguish between medium-risk and high-risk ranges. The first and second preset risk thresholds divide the range of condensation risk into three levels: low-risk range ( ), medium-risk zone ( ) and high-risk areas ( ).

[0078] For S41, controller 13 acquires the second preset risk threshold. This is used to distinguish between medium and high levels of condensation risk.

[0079] Regarding S42, when controller 13 determines the current condensation risk value... When the risk level is in the medium-risk range, the first-level protection strategy is implemented. This strategy involves mild regulation, including simultaneously increasing the pipe wall temperature and moderately reducing the humidification output, with priority given to heating the pipe wall and secondary to reducing humidification. The logic is that when the condensation risk is moderate, increasing the pipe wall temperature above the dew point temperature while moderately reducing the water vapor source effectively reduces the condensation risk without excessively affecting normal heating and humidification functions. Specifically, controller 13 acquires the target pipe wall temperature value, calculates the temperature difference gap between the loop dew point temperature and the pipe wall temperature, increases the target pipe wall temperature value based on the sum of the temperature difference gap and the safety margin, generates a third control parameter to control the heating element to heat the pipe wall, and simultaneously acquires the current output of the humidification component to generate a fourth control parameter to reduce the output of the humidification component by a first magnitude.

[0080] Regarding S43, when controller 13 determines the current condensation risk value... When the risk level is high, a second-level protection strategy is implemented. This second-level protection strategy is mandatory and includes more forceful intervention measures such as immediately cutting off the water vapor source, heating the pipe wall at full power, and temporarily increasing the fresh air flow rate. The logic is that when the risk of condensation reaches a high level, condensate may form at any time, necessitating rapid and forceful intervention to eliminate the risk in the shortest possible time. Specifically, controller 13 generates a fifth control parameter of zero, controls the humidification component to cut off humidification output, generates a sixth control parameter of full power, controls the heating element to heat the pipe wall at full power, and simultaneously acquires the current fresh air flow rate. The increased fresh air flow rate is determined based on the product of the current fresh air flow rate and the temporary increment, and the air source output is controlled to accelerate the removal of water vapor from the pipe.

[0081] For example, if the first preset risk threshold Set to 0.6, the second preset risk threshold. Set to 0.85, controller 13 monitors the condensation risk value in real time. .when When the value is 0.55, the risk of condensation is low, no protection strategy is implemented, and the heating element and humidification component perform normal temperature and humidity control. When the value rises to 0.75 (greater than 0.6 and less than 0.85), controller 13 executes the first-level protection strategy, which simultaneously increases the pipe wall temperature and moderately reduces the humidification output. When When the value continues to rise to 0.92 (greater than 0.85), controller 13 executes the second-level protection strategy, namely cutting off the humidification output, heating the pipe wall at full power, and increasing the fresh air flow rate. In another example, if the first preset risk threshold is reached... =0.7, second preset risk threshold When h=0.9, the condensation risk value is... When the value is 0.8, the first-level protection strategy is executed. When the value is 0.95, the second-level protection strategy is executed.

[0082] As can be seen, this embodiment divides the risk into three levels between two risk thresholds and implements differentiated protection strategies, enabling the system to take matched control actions under different risk levels. Specifically, at medium risk, the first-level protection strategy is implemented to provide gentle intervention by increasing the pipe wall temperature and moderately reducing the humidification output; at high risk, the second-level protection strategy is implemented to provide rapid and strong intervention by cutting off the water vapor source, heating the pipe wall at full power, and increasing the fresh air flow. The graded protection strategy avoids excessive intervention at the risk of slight condensation while ensuring rapid response at the risk of severe condensation, achieving graded and precise control of condensation risk and effectively preventing the impact of condensate on the normal operation of the loop system.

[0083] In one embodiment, after executing the preset hierarchical protection strategy, the following steps are further included: S44: Start the timer, which is used to record the duration for which the condensation risk value is continuously greater than or equal to the first preset risk threshold; S45: Continuously acquire updated condensation risk values ​​during the timer period; S46: When the updated condensation risk value is always greater than or equal to the first preset risk threshold for a certain duration, and the duration reaches the preset duration threshold, the humidification component is cut off, the water collection cup solenoid valve is opened, and a drainage prompt message is generated.

[0084] The timer can be started at the same time that the controller 13 begins to execute the preset hierarchical protection strategy.

[0085] As an example, the preset duration threshold is a pre-set time threshold used to determine whether the condensation risk is a persistently high risk; for example, it can be set to 30 seconds. When the cumulative time for which the condensation risk value is continuously greater than or equal to the first preset risk threshold reaches this preset duration threshold, it indicates that the condensation risk has not been effectively controlled after the implementation of the graded protection strategy, and condensate may have formed in the pipeline, requiring active drainage. The water collection cup solenoid valve is an electric valve installed at the water collection cup in the breathing circuit, used to automatically drain accumulated water when needed. After the water collection cup solenoid valve is opened, the condensate in the water collection cup is discharged through the drain pipeline, preventing condensate from accumulating and flowing back into the breathing equipment. The drainage prompt message is a prompt message displayed to medical staff, such as "Water accumulation in the pipeline, please check the water collection cup." The controller 13 outputs the drainage prompt message to the user interface. The reset condition is that after the condensation risk value is less than the first preset risk threshold and a preset reset time (e.g., 10 seconds) is continuously maintained, the timer is cleared, and normal control is restored.

[0086] For example, the preset duration threshold is set to 30 seconds, and the condensation risk value is... If the value of 0.7 remains above 0.7 for more than 30 seconds, controller 13 determines that there is a persistent high risk of condensation and initiates an active drainage action: cutting off the output of the humidification component, opening the solenoid valve of the water collection cup to drain the accumulated water, and displaying the message "Water accumulation in the pipeline, please check the water collection cup" to the user interface. After the temperature drops to 0.4 and remains there for 10 seconds, the timer is reset, the drainage indicator is turned off, and normal temperature and humidity control is restored.

[0087] As can be seen, this embodiment continuously monitors the risk of condensation after the preset graded protection strategy is executed, and triggers active drainage when the risk continues to exceed the preset time threshold, thus achieving the final active handling of the risk of continuous condensation, effectively preventing the accumulation of condensate in the pipeline, and effectively avoiding the harm caused by condensate backflow to the normal operation of the circuit.

[0088] Secondly, please refer to Figure 3 This application provides a control method for a medical device, applicable to a controller 13, the control method comprising: S101: Obtain the gas parameters at the inhalation end and the tube wall temperature, wherein the gas parameters at the inhalation end include the inhalation end temperature and the relative humidity at the inhalation end; S102: Calculate the circuit dew point temperature based on the suction end temperature and the suction end relative humidity; S103: Calculate the condensation risk value based on the dew point temperature of the circuit and the pipe wall temperature; S104: When the condensation risk value is less than the first preset risk threshold, control the heating element of the medical device to heat, and control the humidification component of the medical device to humidify, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values. S105: When the condensation risk value is greater than or equal to the first preset risk threshold, a preset graded protection strategy is executed.

[0089] In summary, based on the above technical solution, by acquiring measured data of the suction end temperature, relative humidity, and pipe wall temperature, and calculating the loop dew point temperature based on the suction end temperature and relative humidity, and calculating the condensation risk value based on the difference between the loop dew point temperature and the pipe wall temperature, the condensation risk of the loop is transformed from a qualitative judgment into a continuously quantified risk indicator, realizing the quantitative perception of condensation risk. When the condensation risk value is below the threshold, the heating element and humidification component are controlled to perform closed-loop actions using the suction end temperature and humidity as feedback quantities, so that the heating power and humidification amount are adaptively adjusted according to the measured values ​​of the suction end temperature and humidity. When the condensation risk value reaches the threshold, a graded protection strategy is implemented, so that the intensity of the protection action matches the severity of the condensation risk, thereby enabling the actions of the heating element and humidification component to be adjusted in real time based on the measured suction end temperature and humidity and pipe wall temperature in the loop. Thus, the problem of existing solutions failing to detect condensation risk due to the lack of monitoring of suction end temperature and humidity and pipe wall temperature, resulting in condensate formation affecting the normal operation of the loop, is solved. This achieves quantitative perception and graded prevention and control of condensation risk based on the measured loop status, improving the safety and stability of loop operation.

[0090] In one embodiment, calculating the condensation risk value based on the loop dew point temperature and the pipe wall temperature includes: S131: Calculate the second difference between the loop dew point temperature and the pipe wall temperature; S132: Obtain the temperature tolerance value, which is determined based on the first accuracy parameter of the first sensor 11 and the second accuracy parameter of the second sensor 12; S133: Based on the second difference and the temperature tolerance value, perform sigmoid function mapping to obtain the condensation risk value.

[0091] In one embodiment, the target parameter value includes a target temperature value and a target humidity value; The method of controlling the heating element of the medical device to heat and controlling the humidification component of the medical device to humidify, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values, includes: S141: Obtain preset temperature and preset humidity values; S142: Correct the preset temperature value based on the patient's body temperature to obtain the target temperature value; S143: Correct the preset humidity value based on the patient's body temperature and the fresh air flow rate to obtain the target humidity value; S144: Determine the first control parameter of the heating element based on the suction end temperature and the target temperature value; S145: Determine the second control parameter of the humidification component based on the relative humidity at the inhalation end and the target humidity value; S146: Control the heating element to heat according to the first control parameter so that the temperature of the suction end reaches the target temperature value; S147: Control the humidification component to humidify according to the second control parameter so that the relative humidity at the inhalation end reaches the target humidity value.

[0092] In one embodiment, the step of correcting the preset temperature value based on the patient's body temperature to obtain the target temperature value includes: S1421: When the patient's body temperature is lower than a first preset body temperature threshold, calculate a first difference between the patient's body temperature and the first preset body temperature threshold. S1422: Determine the first temperature increment based on the first difference and the first preset coefficient; S1423: Obtain the target temperature value based on the preset temperature value and the first temperature increment.

[0093] In one embodiment, the step of correcting the preset humidity value based on the patient's body temperature and the fresh air flow rate to obtain the target humidity value includes: S1431: Calculate the change in saturated humidity corresponding to the target temperature value; S1432: Obtain the intermediate humidity value based on the preset humidity value and the change in saturated humidity; S1433: Get the current fresh air flow rate; S1434: Determine the second humidity increment based on the fresh air flow rate and the second preset coefficient; S1435: The target humidity value is obtained based on the intermediate humidity value and the second humidity increment.

[0094] In one embodiment, determining the first control parameter of the heating element based on the suction end temperature and the target temperature value includes: S1441: Calculate the first deviation value between the inhalation end temperature and the target temperature value; S1442: The first deviation value is proportionally amplified to obtain a first proportional component; S1443: Based on the first integral coefficient, the first deviation value is integrated and accumulated to obtain the first integral component; S1444: Determine the first control parameter of the heating element based on the first proportional component and the first integral component; In one embodiment, determining the second control parameter of the humidification component based on the relative humidity at the inhalation end and the target humidity value includes: S1451: Calculate the second deviation value between the relative humidity at the inhalation end and the target humidity value; S1452: The second deviation value is proportionally amplified to obtain a second proportional component; S1453: Based on the second integral coefficient, the second deviation value is integrated and accumulated to obtain the second integral component; S1454: Determine the second control parameter of the humidification component based on the second proportional component and the second integral component; Wherein, the second integral coefficient is smaller than the first integral coefficient.

[0095] In one embodiment, the preset graded protection strategy includes a first-level protection strategy and a second-level protection strategy; wherein, the first-level protection strategy is used to control the heating element to increase the pipe wall temperature and / or control the humidification component to reduce the humidification output, and the second-level protection strategy is used to control the humidification component to cut off the humidification output, control the heating element to operate at full power, and / or increase the fresh air flow rate; When the condensation risk value is greater than or equal to the first preset risk threshold, a preset graded protection strategy is executed, including: S151: Obtain a second preset risk threshold, wherein the second preset risk threshold is greater than the first preset risk threshold; S152: When the condensation risk value is greater than or equal to the first preset risk threshold and less than the second preset risk threshold, the first level of protection strategy is executed. S153: When the condensation risk value is greater than or equal to the second preset risk threshold, the second level of protection strategy is executed.

[0096] It should be noted that the implementation steps / functions of the medical device control method described in the second aspect and the medical device control system 10 described in the first aspect correspond one-to-one, and the specific limitations of the medical device control method can be found in the limitations of the medical device control system 10 above, which will not be repeated here.

[0097] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0098] Thirdly, embodiments of this application provide a controller 13, the internal structure of which can be shown in the following diagram. Figure 4As shown. The controller 13 includes a processor, memory, and a network interface connected via a system bus. The processor of the controller 13 provides computing and control capabilities. The memory of the controller 13 includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the controller 13 is used to communicate with external terminals. When the computer program is executed by the processor, it implements the functions or steps of a control method for a medical device.

[0099] In one embodiment, this application provides a controller 13, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the control method for the medical device as described in the second aspect above.

[0100] Fourthly, such as Figure 5 As shown in the embodiment of this application, this application provides a medical device, the medical device comprising: Heating element 20 and humidification assembly 30; and, The control system 10 of the medical device described in the first aspect above.

[0101] It should be noted that the functions or steps that the controller 13 or the medical device can achieve are described in the relevant descriptions in the aforementioned embodiment of the control system 10 of the medical device. To avoid repetition, they will not be described one by one here.

[0102] Fifthly, embodiments of this application provide a control device for a medical device, which corresponds one-to-one with the control methods for the medical devices described in the above embodiments. For example... Figure 6 As shown, the control device of the medical equipment includes an acquisition module 100, a first calculation module 200, a second calculation module 300, a first control module 400, and a second control module 500. Detailed descriptions of each functional module are as follows: The acquisition module 100 is used to acquire the gas parameters at the inhalation end and the tube wall temperature, wherein the gas parameters at the inhalation end include the inhalation end temperature and the relative humidity at the inhalation end. The first calculation module 200 is used to calculate the circuit dew point temperature based on the inhalation end temperature and the inhalation end relative humidity; The second calculation module 300 is used to calculate the condensation risk value based on the dew point temperature of the circuit and the pipe wall temperature. The first control module 400 is used to control the heating element of the medical device to heat and control the humidification component of the medical device to humidify when the condensation risk value is less than the first preset risk threshold, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values. The second control module 500 is used to execute a preset graded protection strategy when the condensation risk value is greater than or equal to the first preset risk threshold.

[0103] In summary, based on the above technical solution, by acquiring measured data of the suction end temperature, relative humidity, and pipe wall temperature, and calculating the loop dew point temperature based on the suction end temperature and relative humidity, and calculating the condensation risk value based on the difference between the loop dew point temperature and the pipe wall temperature, the condensation risk of the loop is transformed from a qualitative judgment into a continuously quantified risk indicator, realizing the quantitative perception of condensation risk. When the condensation risk value is below the threshold, the heating element and humidification component are controlled to perform closed-loop actions using the suction end temperature and humidity as feedback quantities, so that the heating power and humidification amount are adaptively adjusted according to the measured values ​​of the suction end temperature and humidity. When the condensation risk value reaches the threshold, a graded protection strategy is implemented, so that the intensity of the protection action matches the severity of the condensation risk, thereby enabling the actions of the heating element and humidification component to be adjusted in real time based on the measured suction end temperature and humidity and pipe wall temperature in the loop. Thus, the problem of existing solutions failing to detect condensation risk due to the lack of monitoring of suction end temperature and humidity and pipe wall temperature, resulting in condensate formation affecting the normal operation of the loop, is solved. This achieves quantitative perception and graded prevention and control of condensation risk based on the measured loop status, improving the safety and stability of loop operation.

[0104] In one embodiment, the second computing module 300 is further configured to: Calculate the second difference between the loop dew point temperature and the pipe wall temperature; A temperature tolerance value is obtained, which is determined based on a first accuracy parameter of the first sensor 11 and a second accuracy parameter of the second sensor 12. Based on the second difference and the temperature tolerance value, a sigmoid function mapping process is performed to obtain the condensation risk value.

[0105] In one embodiment, the target parameter value includes a target temperature value and a target humidity value; The first control module 400 is also used for: Obtain preset temperature and preset humidity values; The preset temperature value is corrected based on the patient's body temperature to obtain the target temperature value; The preset humidity value is corrected based on the patient's body temperature and the fresh air flow rate to obtain the target humidity value; The first control parameter of the heating element is determined based on the suction end temperature and the target temperature value; The second control parameter of the humidification component is determined based on the relative humidity at the inhalation end and the target humidity value; The heating element is controlled to heat according to the first control parameter so that the temperature at the suction end reaches the target temperature value. The humidification component is controlled to humidify according to the second control parameter so that the relative humidity at the inhalation end reaches the target humidity value.

[0106] In one embodiment, the first control module 400 is further configured to: When the patient's body temperature is lower than a first preset body temperature threshold, calculate a first difference between the patient's body temperature and the first preset body temperature threshold. The first temperature increment is determined based on the first difference and the first preset coefficient; The target temperature value is obtained based on the preset temperature value and the first temperature increment.

[0107] In one embodiment, the first control module 400 is further configured to: Calculate the change in saturated humidity corresponding to the target temperature value; The intermediate humidity value is obtained based on the preset humidity value and the change in saturated humidity; Get the current fresh air flow rate; The second humidity increment is determined based on the fresh air flow rate and the second preset coefficient; The target humidity value is obtained based on the intermediate humidity value and the second humidity increment.

[0108] In one embodiment, the first control module 400 is further configured to: Calculate the first deviation between the inhalation temperature and the target temperature value; The first deviation value is proportionally amplified to obtain the first proportional component; Based on the first integral coefficient, the first deviation value is integrated and accumulated to obtain the first integral component; The first control parameters of the heating element are determined based on the first proportional component and the first integral component. In one embodiment, the first control module 400 is further configured to: Calculate the second deviation value between the relative humidity at the inhalation end and the target humidity value; The second deviation value is proportionally amplified to obtain the second proportional component; Based on the second integral coefficient, the second deviation value is integrated and accumulated to obtain the second integral component; The second control parameter of the humidification component is determined based on the second proportional component and the second integral component; Wherein, the second integral coefficient is smaller than the first integral coefficient.

[0109] In one embodiment, the preset graded protection strategy includes a first-level protection strategy and a second-level protection strategy; wherein, the first-level protection strategy is used to control the heating element to increase the pipe wall temperature and / or control the humidification component to reduce the humidification output, and the second-level protection strategy is used to control the humidification component to cut off the humidification output, control the heating element to operate at full power, and / or increase the fresh air flow rate; The second control module 500 is also used for: Obtain a second preset risk threshold, which is greater than the first preset risk threshold; When the condensation risk value is greater than or equal to the first preset risk threshold and less than the second preset risk threshold, the first level of protection strategy is executed; When the condensation risk value is greater than or equal to the second preset risk threshold, the second level of protection strategy is executed.

[0110] It should be noted that the specific limitations regarding the control device of the medical device can be found in the limitations of the control system 10 of the medical device described above, and will not be repeated here. Each module in the control device of the aforementioned medical device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the controller 13 in hardware form or independent of it, or they can be stored in the memory of the controller 13 in software form, so that the processor can call and execute the operations corresponding to each module.

[0111] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A control system for a medical device, characterized in that, The control system includes: The first sensor is configured to collect inhalation end gas parameters, including inhalation end temperature and inhalation end relative humidity. The second sensor is configured to collect the pipe wall temperature; A controller is connected to both the first sensor and the second sensor; wherein the controller is configured as follows: Calculate the circuit dew point temperature based on the inhalation end temperature and the relative humidity at the inhalation end; Calculate the condensation risk value based on the dew point temperature of the circuit and the pipe wall temperature; When the condensation risk value is less than the first preset risk threshold, the heating element of the medical device is controlled to heat, and the humidification component of the medical device is controlled to humidify, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values. When the condensation risk value is greater than or equal to the first preset risk threshold, a preset graded protection strategy is executed.

2. The control system according to claim 1, characterized in that, The calculation of the condensation risk value based on the circuit dew point temperature and the pipe wall temperature includes: Calculate the second difference between the loop dew point temperature and the pipe wall temperature; A temperature tolerance value is obtained, which is determined based on a first accuracy parameter of the first sensor and a second accuracy parameter of the second sensor. Based on the second difference and the temperature tolerance value, a sigmoid function mapping process is performed to obtain the condensation risk value.

3. The control system according to claim 1, characterized in that, The target parameter values ​​include target temperature and target humidity values; the control system further includes: The third sensor is configured to collect the patient's body temperature; The fourth sensor is configured to collect fresh air flow rate; The controller is also connected to the third sensor and the fourth sensor; The method of controlling the heating element of the medical device to heat and controlling the humidification component of the medical device to humidify, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values, includes: Obtain preset temperature and preset humidity values; The preset temperature value is corrected based on the patient's body temperature to obtain the target temperature value; The preset humidity value is corrected based on the patient's body temperature and the fresh air flow rate to obtain the target humidity value; The first control parameter of the heating element is determined based on the suction end temperature and the target temperature value; The second control parameter of the humidification component is determined based on the relative humidity at the inhalation end and the target humidity value; The heating element is controlled to heat according to the first control parameter so that the temperature at the suction end reaches the target temperature value. The humidification component is controlled to humidify according to the second control parameter so that the relative humidity at the inhalation end reaches the target humidity value.

4. The control system according to claim 3, characterized in that, The step of correcting the preset temperature value based on the patient's body temperature to obtain the target temperature value includes: When the patient's body temperature is lower than a first preset body temperature threshold, calculate a first difference between the patient's body temperature and the first preset body temperature threshold. The first temperature increment is determined based on the first difference and the first preset coefficient; The target temperature value is obtained based on the preset temperature value and the first temperature increment.

5. The control system according to claim 3, characterized in that, The step of correcting the preset humidity value based on the patient's body temperature and the fresh air flow rate to obtain the target humidity value includes: Calculate the change in saturated humidity corresponding to the target temperature value; The intermediate humidity value is obtained based on the preset humidity value and the change in saturated humidity; Get the current fresh air flow rate; The second humidity increment is determined based on the fresh air flow rate and the second preset coefficient; The target humidity value is obtained based on the intermediate humidity value and the second humidity increment.

6. The control system according to claim 3, characterized in that: The step of determining the first control parameter of the heating element based on the suction end temperature and the target temperature value includes: Calculate the first deviation between the inhalation temperature and the target temperature value; The first deviation value is proportionally amplified to obtain the first proportional component; Based on the first integral coefficient, the first deviation value is integrated and accumulated to obtain the first integral component; The first control parameters of the heating element are determined based on the first proportional component and the first integral component. The step of determining the second control parameter of the humidification component based on the relative humidity at the inhalation end and the target humidity value includes: Calculate the second deviation value between the relative humidity at the inhalation end and the target humidity value; The second deviation value is proportionally amplified to obtain the second proportional component; Based on the second integral coefficient, the second deviation value is integrated and accumulated to obtain the second integral component; The second control parameter of the humidification component is determined based on the second proportional component and the second integral component; Wherein, the second integral coefficient is smaller than the first integral coefficient.

7. The control system according to claim 1, characterized in that, The preset graded protection strategy includes a first-level protection strategy and a second-level protection strategy; wherein, the first-level protection strategy is used to control the heating element to increase the pipe wall temperature and / or control the humidification component to reduce the humidification output, and the second-level protection strategy is used to control the humidification component to cut off the humidification output, control the heating element to operate at full power, and / or increase the fresh air flow rate. When the condensation risk value is greater than or equal to the first preset risk threshold, a preset graded protection strategy is executed, including: Obtain a second preset risk threshold, which is greater than the first preset risk threshold; When the condensation risk value is greater than or equal to the first preset risk threshold and less than the second preset risk threshold, the first level of protection strategy is executed; When the condensation risk value is greater than or equal to the second preset risk threshold, the second level of protection strategy is executed.

8. A method for controlling a medical device, characterized in that, Applied to a controller, the control method includes: Acquire inhalation end gas parameters and tube wall temperature, wherein the inhalation end gas parameters include inhalation end temperature and inhalation end relative humidity; Calculate the circuit dew point temperature based on the inhalation end temperature and the relative humidity at the inhalation end; Calculate the condensation risk value based on the dew point temperature of the circuit and the pipe wall temperature; When the condensation risk value is less than the first preset risk threshold, the heating element of the medical device is controlled to heat, and the humidification component of the medical device is controlled to humidify, so that the inhalation end temperature and the inhalation end relative humidity reach the corresponding target parameter values. When the condensation risk value is greater than or equal to the first preset risk threshold, a preset graded protection strategy is executed.

9. A controller comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the control method for the medical device as described in claim 8.

10. A medical device, characterized in that, The medical device includes: Heating elements and humidification components; and, The control system of the medical device as described in any one of claims 1 to 7.

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