Leakage calculation method and system for ventilation equipment

Abstract

The invention relates to the technical field of ventilation equipment, in particular to a leakage calculation method and system of ventilation equipment, and the method comprises the following steps: when a patient inhales autonomously, determining the flow output of the ventilation equipment by adopting a gradient filtering method, thereby judging whether the flow velocity of the patient end has leakage abrupt change or not; if leakage exists, the next step is carried out; a classical leakage model is adopted, the value of the leakage amount is updated in combination with the motion equation of the patient and the breathing machine, and therefore real-time monitoring and updating of the leakage amount of the breathing equipment are achieved in the whole breathing process. According to the peak flow monitoring and gradient filtering combined method provided by the invention, the abnormal leakage of the inspiratory phase can be quickly monitored, and the leakage rate and leakage parameters of the breathing machine are updated in real time after the flow rate and the pressure signal are stable, so that the leakage rate can be quickly updated in the ventilation process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of respiratory ventilation equipment, and particularly relates to a ventilation equipment leakage calculation method and system. BACKGROUND

[0002] In the treatment of patients with respiratory diseases by a breathing machine, invasive or non-invasive mechanical ventilation treatment can be used according to the severity of the respiratory disease of the patient. The breathing machine provides sufficient pressure or tidal volume to the patient through a breathing mask or a cannula by means of a power device such as a turbine, which is an important way to treat respiratory diseases. Generally, excessive or insufficient ventilation of the breathing machine will have a negative impact on the treatment of the patient. Therefore, it is important for the breathing machine to monitor the tidal volume and flow rate actually entering the patient's body.

[0003] The breathing machine equipment can make the flow and pressure of the breathing machine smoothly enter the patient's body through the intervention of a leakage mask or a cannula, thereby avoiding alveolar collapse caused by respiratory diseases or treating actual conditions such as snoring caused by airway collapse. However, due to the size and fit of the ventilation mask, the breathing machine inevitably causes some unexpected leakage in addition to the leakage of the mask leakage hole. However, due to the limited number of sensors, it is necessary to monitor the leakage in real time, so as to accurately determine the respiratory switching point of the patient. In many cases, it can be necessary to set a reference pressure and / or flow trajectory for specific respiratory treatment. Generally, it is necessary to measure or determine the volume of respiratory gas delivered to the patient's lungs and the volume of gas exhaled by the patient, and to take into account the measured or predicted / estimated leakage amount to ensure accurate delivery, data reporting and monitoring. Therefore, the more accurate the leakage estimation, the more accurate the calculated reference value of the delivery and exhalation volume, and the better the reference calculation of the delivery and exhalation volume and event detection (trigger and cycle phase transition detection).

[0004] In the current prior art, a multiple time window scheme is used to perform least squares regression analysis in each time window, to synthesize the leakage amounts of different time windows, and to increase a leakage forgetting factor to weaken the influence of old data on the leakage model, so as to adjust the model parameters in real time to adapt to environmental changes to monitor the leakage amount of the respiratory ventilation device in real time.

[0005] However, during inhalation, more flow is required to achieve the same pressure level as in the case of no leak. During exhalation, a portion of the gas exhaled by the patient escapes through the leak, which is missed by the ventilator exhalation flow measurement subsystem, and in many cases, the goal of the respiratory ventilation device is to provide a controlled pressure or flow profile or trajectory, e.g., pressure or flow as a function of time, during the inhalation phase of the breathing cycle. While some success has been achieved in current respiratory ventilation systems in attempting to take measures to compensate for leaks in ventilation device components, previous compensation mechanisms have generally been based on simplified assumptions or limited information, which limits their ability to accurately and dynamically calculate system leaks overall and with respect to inhalation or specific instantaneous leak rates.

[0006] A leakage simulation test method, system, computer device and storage medium are disclosed in the invention patent with publication number CN118983068A, which connects the measured ventilator and the simulation lung through the target pipeline, and simultaneously connects the simulation leakage ventilator and the target pipeline; the operating parameters of the measured ventilator and the simulation lung are set, and the measured ventilator is controlled to start ventilation according to its operating parameters; based on the ventilation data recorded by the measured ventilator and the leakage data recorded by the simulation leakage ventilator during the ventilation process, the actual leakage result corresponding to the target pipeline is calculated; based on the actual leakage result, the performance of the measured ventilator is analyzed, and the invention patent with publication number CN117752906A discloses a device for detecting respiratory abnormalities and a ventilator. In the above device, the first detection module can determine whether the ventilator is in a gas leakage abnormal state caused by improper use according to the real-time gas leakage amount and the basic gas leakage amount of the ventilator, and the second detection module can calculate a respiratory detection threshold in the gas leakage abnormal state when the ventilator is in the gas leakage abnormal state, and detect whether the user wearing the ventilator has a respiratory abnormal event (i.e., an apnea event and a hypopnea event) based on the respiratory detection threshold in the gas leakage abnormal state, so as to reduce the false detection probability of the respiratory abnormal event in the gas leakage abnormal state and improve the accuracy and reliability of the detection result. The two disclosed inventions only use a simple leakage factor to calculate the leakage amount, so the accuracy in the leakage rate cannot be guaranteed. SUMMARY

[0007] The present application provides a leakage calculation method for a ventilation device, which solves the problem of low accuracy and poor dynamic calculation ability of system leaks overall and with respect to inhalation or specific instantaneous leak rates in the prior art, and further discloses a leakage calculation system for a ventilation device.

[0008] Technical solution: In a first aspect, the present application provides a leakage calculation method for a ventilation device, which is used in a ventilator, and the method comprises the following steps:

[0009] S1 When the patient is in spontaneous inspiration, the gradient filtering method is used to determine the output of the filter, so as to determine whether there is a sudden leakage mutation in the patient end flow rate, specifically: the peak flow rate is identified through the patient end flow rate, when the target pressure output is stable and the flow rate slowly decreases, the patient end flow rate after gradient filtering will gradually converge to the zero baseline, at this time, if there is a sudden leakage, the filter will output a positive value on the basis of the zero baseline; if there is leakage, the next step S2 is performed, otherwise, the step S1 is cycled to monitor the state of the ventilation equipment in real time;

[0010] S2 The classical leakage model is used to update the value of the leakage according to the motion equation of the patient and the ventilator, so as to realize real-time monitoring and updating of the leakage of the breathing equipment in the whole breathing process.

[0011] Further, comprising:

[0012] If there is a sudden leakage, the filter will output a positive value on the basis of the zero baseline, comprising:

[0013] Let U(k) and y(k) be the kth output and input of the filter respectively, and let the kth input value y(k)≡Q(k), calculate the gradient filtering value ΔU(k) of the flow rate Q(k), when the flow rate baseline is zero, observe the value of |ΔU(k)|, if it is greater than a certain constant value, it is judged as leakage, otherwise, it is not leakage, and continue to use gradient filtering to identify the flow rate.

[0014] Further, comprising:

[0015] The calculation process of the gradient filtering value ΔU(k) comprises:

[0016] The k+1th input is represented as:

[0017] y(k+1)=F(y(k),…,y(k-m),U(k),…,U(k-n));

[0018] Wherein, m and n represent the order of the system;

[0019] A pseudo partial derivative φ(k) is introduced, which describes the sensitivity of the function to the change of other variables when a variable is disturbed, so that the above system is transformed into a dynamic linearization data model:

[0020] Δy(k+1)=ΔU(k)*φ(k);

[0021] Wherein: Δy(k+1)=y(k+1)-y(k), ΔU(k)=U(k)-U(k-1);

[0022] A criterion function is introduced and substituted into the dynamic linearization data model, and then U(k) is derived, and d(U(k))=0 is obtained:

[0023]

[0024] wherein ρ k is a step factor, and the introduction of λ avoids singular situations in which the denominator of the system can be zero, and φ'(k) is the derivative of the pseudo partial derivative φ(k);

[0025] The output of the system, i.e., the flow rate, is represented as:

[0026]

[0027] Further, comprising:

[0028] The criterion function is represented as:

[0029] J(u(k))=|y'(k+1)-y(k+1)| 2 +λ|U(k)-U(k-1)| 2 ;

[0030] wherein λ is a system output change weight coefficient, and in the criterion function, the introduction of the term λ|U(k)-U(k-1) 2 limits the change of the system output and overcomes the steady-state error.

[0031] Further, comprising:

[0032] The classical leakage model is used to update the value of the leakage according to the motion equation of the patient and the ventilator, comprising:

[0033] Let the total flow of the system output be Q V , the flow rate into the patient be Q P , and the total leakage flow rate be Q L , and the classical leakage model is introduced and represented as:

[0034] Q L (k)=G orf P γ (k);

[0035] wherein G orf and γ are two parameters assumed to remain constant during one breath, and P is the pressure value when the leakage occurs;

[0036] The classical leakage model is integrated to obtain:

[0037]

[0038] Leakage coefficient G is obtained:

[0039]

[0040] wherein, in the ventilation device, if there is dual level ventilation or single level pressure release ventilation, when the patient is in the inhalation state, P = P aw , when the patient is in the exhalation state, P = EPAP, wherein, EPAP is the exhalation pressure, P aw is the airway pressure of the ventilation system.

[0041] Further comprising:

[0042] The airway pressure P of the ventilation system aw Using the general respiratory motion equation of the patient and the ventilator:

[0043]

[0044] wherein, R and E in the model respectively represent the respiratory resistance caused by the airway and the elastic resistance caused by the lung and the chest wall, P mus is the muscle pressure of the patient, and t is time;

[0045] Therefore, when the respiratory system is in a steady state, at this time, whether the patient is in inhalation or exhalation, there is:

[0046] P mus = 0;

[0047]

[0048] When the respiratory flow rate is in a steady state, Q′ P = 0, therefore, there is:

[0049] Q L = Q V - Q P ;

[0050] In a period of stable time, there is:

[0051]

[0052] At this time, the stable platform in exhalation updates the leakage coefficient G orf .

[0053] In a second aspect, the present application provides a leakage calculation system of a ventilation device, which is used in a ventilator, the system comprising:

[0054] The state monitoring module is used for determining the output of the filter system by using the gradient filtering method when the patient is in spontaneous inhalation, so as to determine whether there is a sudden leakage mutation of the patient end flow rate, and specifically, the peak flow rate is identified through the patient end flow rate, when the target pressure output is stable and the flow rate slowly decreases, the patient end flow rate after the gradient filtering gradually converges to the zero baseline, at this time, if a sudden leakage occurs, the filter outputs a positive value on the basis of the zero baseline, if there is leakage, the leakage value updating module is performed, otherwise, the module is recycled, so as to monitor the state of the ventilation equipment in real time.

[0055] The leakage value updating module is used for updating the value of the leakage amount by using a classical leakage model according to the motion equation of the patient and the respirator, so as to realize real-time monitoring and updating of the leakage amount of the breathing equipment in the whole breathing process.

[0056] In a third aspect, the present application provides a breathing ventilation equipment, wherein the ventilation equipment is provided with the leakage calculation system of the ventilation equipment as described above, and is used for executing the leakage calculation method of the ventilation equipment as described above.

[0057] In a fourth aspect, the present application further provides a readable storage medium, wherein the readable storage medium stores programs or instructions, and the programs or instructions are executed by the ventilation equipment to realize the steps of the leakage calculation method of the ventilation equipment as described above.

[0058] Advantages: Compared with the prior art, the present application has the following advantages:

[0059] The present application mainly uses the peak flow detection and the gradient filtering method to quickly detect the sudden leakage of the breathing ventilation equipment, so as to quickly compensate the leakage amount, and especially improve the effect of the reference calculation of the delivery and exhalation volume and the event detection when the patient inhales.

[0060] Specifically, the gradient filtering method provided by the present application can filter the patient end flow rate, and the output of the gradient filtering can accurately determine the patient inhalation and exhalation state and the leakage state, so as to improve the accuracy of the leakage identification, so as to dynamically calculate the leakage amount in the inhalation and exhalation process.

[0061] Unlike the fixed model parameter assumption method in the prior art, the leakage coefficient G orf The updating strategy can adapt to different patients, and can accurately estimate the leakage amount of the respirator, improve the accuracy of the leakage calculation and the monitoring precision of the leakage, and improve the man-machine synchronization comfort of the respirator. BRIEF DESCRIPTION OF DRAWINGS

[0062] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0063] Figure 1 A structural diagram of a leaking ventilator in operation for a patient;

[0064] Figure 2 This is a schematic diagram of the structure of the ventilation equipment described in this invention that is leaking.

[0065] Figure 3 This is a circuit diagram illustrating the patient's muscle pressure and respiratory process as described in this invention.

[0066] Figure 4 This is a flowchart of the leakage method for the expiratory ventilation device described in this invention;

[0067] Figure 5 This is a schematic diagram of the leakage calculation system of the ventilation equipment described in this invention. Detailed Implementation

[0068] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0069] Example 1: As Figure 4 As shown, this invention provides a leakage calculation method for ventilation equipment, used in ventilators, designed to quickly compensate for sudden leaks, especially unexpected leaks occurring during patient inhalation. Specifically, in this embodiment, gradient filtering is applied to the flow velocity at the patient end. This filter ensures that the flow velocity baseline at the patient end is zero. Therefore, when the patient is inspiring spontaneously, the filter output will cause its value to fluctuate in the positive direction of the zero baseline; conversely, when the patient is exhaling, the filter output will cause its value to fluctuate in the negative direction of the zero baseline.

[0070] Therefore, when the patient is in spontaneous inhalation, the first peak flow rate is identified by the patient end flow rate, and when the target pressure plateau flow rate slowly decreases, the patient end flow rate filtered by the gradient filter gradually converges to the zero baseline, at this time, if sudden leakage occurs, the filter outputs a relatively large positive value based on the zero baseline, at this time, the sudden leakage amount can be quickly captured, and when the patient end flow rate and the pressure have a relatively stable platform, the leakage amount of the ventilation device is quickly updated.

[0071] When the patient is in exhalation, it is assumed that the average amount of gas delivered to the patient is equal to the amount of gas exhaled by the patient, and the mean values of the pressure and the flow rate in the calculation period are calculated, the leakage hole size and the treatment pressure are estimated by a typical flow rate leakage model, and the leakage flow rate of the ventilation device is calculated.

[0072] The method comprises the following steps:

[0073] S1 When the patient is in spontaneous inhalation, the output of the filter is determined by using a gradient filtering method, so as to determine whether there is a sudden leakage of the patient end flow rate, specifically: the peak flow rate is identified by the patient end flow rate, and when the target pressure plateau flow rate slowly decreases, the patient end flow rate filtered by the gradient filter gradually converges to the zero baseline, at this time, if sudden leakage occurs, the filter outputs a positive value based on the zero baseline; if there is leakage, the next step S2 is performed, otherwise, the step S1 is recycled, and the state of the ventilation device is monitored in real time;

[0074] S2 The value of the leakage amount is updated according to the motion equation of the patient and the ventilator by using a classical leakage model, so as to realize real-time monitoring and updating of the leakage amount of the breathing device in the whole breathing process.

[0075] The specific implementation process of the above method comprises:

[0076] The main core of a gradient filtering method is a pseudo-gradient estimation algorithm, and the core is as follows:

[0077] Let U(k) and y(k) be the kth output and input of the filter respectively:

[0078] y(k+1)=F(y(k),...,y(k-m),U(k),...,U(k-n));(1)

[0079] Wherein, m and n represent the system order of the filter.

[0080] A pseudo partial derivative φ(k) is introduced, which describes the sensitivity of the function to the change of other variables when a variable is disturbed, so that the above system is transformed into a dynamic linearization data model:

[0081] Δy(k+1)=ΔU(k)*φ(k);(2)

[0082] where: Δy(k+1) = y(k+1) - y(k), ΔU(k) = U(k) - U(k-1),

[0083] Differentiate φ(k) with respect to k:

[0084]

[0085] where μ > 0 is a weight factor for pseudo-derivative adjustment rate.

[0086] η k ∈(0,1] is an adjustment parameter for variation sensitivity, and we have:

[0087]

[0088] To avoid sharp changes in data that lead to the inadmissible derivative φ'(k), the upper limit of variation of φ'(k) is limited to φ(Limit).

[0089] Introduce a criterion function:

[0090] J(u(k)) = |y'(k+1) - y(k+1)| 2 + λ|U(k) - U(k-1)| 2 ; (5)

[0091] λ is a weight coefficient for system output variation.

[0092] In this criterion function, the introduction of the term λ|U(k) - U(k-1)| 2 limits the system output variation and overcomes the steady-state error.

[0093] Substitute the criterion function into the dynamic linearization data model, and differentiate U(k) with respect to k, and let d(U(k)) = 0, we have:

[0094]

[0095] where: ρ k is a step factor, and the introduction of λ avoids the singular situation that the denominator of the system can be zero.

[0096] The output of the system is:

[0097]

[0098] So, when the parameter of the system y(k)≡Q(k), the output of the system ΔU(k) is the gradient filter value of the flow rate Q(k), which is only related to the flow rate, so it can be used to determine whether the flow rate has a large mutation; moreover, the output of the system ΔU(k) is consistent with the change direction of the flow rate Q(k).

[0099] The system described below in the embodiment is only used for detecting the flow rate mutation, for detecting the sudden change of the flow rate caused by the sudden leakage. The filter system described above is mainly used for identifying the leakage in the inhalation phase. Therefore, the gradient filter method proposed in the application can filter the flow rate at the patient end, and the output of the gradient filter can accurately determine the inhalation and exhalation states of the patient and the leakage state, thereby improving the accuracy of the leakage identification, so as to dynamically calculate the leakage amount in the inhalation and exhalation processes. In combination with the leakage system described below, the gradient filter method proposed in the application can quickly identify the sudden leakage in the breathing process, can update the leakage coefficient G orf in time, and can calculate the real-time leakage amount, thereby improving the accuracy of the leakage calculation and the monitoring precision of the leakage. Different from the method of assuming that the model parameters are fixed, the leakage coefficient G orf updating strategy proposed in the application can adapt to different patients, can accurately estimate the leakage amount of the ventilator, and improves the human-machine synchronization comfort of the ventilator.

[0100] The embodiment also provides a general leakage system:

[0101] As shown in FIGS. Figure 1 and 2 , the total flow rate of the system output is Q V , the flow rate entering the patient is Q P , and the total leakage flow rate is Q L . The classical leakage model is introduced as follows:

[0102] Q L (k)=G orf P γ (k);(8)

[0103] wherein G orf and γ are two parameters assumed to be constant in one breathing process, and P is the pressure value when the leakage occurs. γ takes the classical value 0.5.

[0104] In the ventilation equipment, if there is bi-level ventilation or single-level pressure release ventilation, when the patient is in the inhalation state, P=P aw , and when the patient is in the exhalation state, P=EPAP, EPAP is the exhalation pressure, and P aw is the airway pressure of the ventilation system.

[0105] The integral of the same can be obtained as follows:

[0106]

[0107] Leakage coefficient is obtained as:

[0108]

[0109] As shown in Fig. 1, the general respiratory motion equation of a patient and a ventilator is: Figure 3

[0110]

[0111] This model has two parameters, i.e. R and E, which represent the respiratory resistance and the elastic resistance respectively. The respiratory resistance is mainly caused by the airway, and the elastic resistance is mainly caused by the lung and the chest wall. P mus is the muscle pressure of the patient, and t is time.

[0112] When the respiratory system is in a steady state, at this time, no matter whether the patient is in inhalation or exhalation, there is:

[0113] P mus = 0; (12)

[0114]

[0115] When the respiratory flow rate is in a steady state, there is Q' P = 0, so there is:

[0116] Q L = Q V - Q P ; (14)

[0117] In a period of stable time, there is:

[0118]

[0119] Therefore, during inhalation, if there is a sudden leakage, the filtered system output ΔU(k) has a relatively obvious positive change, at this time, the system leakage state can be quickly identified, and when the flow rate and the pressure of the respiratory system have a relatively obvious stable platform, the value of the leakage amount can be updated according to the motion equation of the patient and the ventilator. Because the average tidal volume inhaled by the patient in one cycle or multiple cycles is equal to the average tidal volume exhaled, therefore, the leakage coefficient G orf can be updated at the stable platform during exhalation.

[0120] ​In addition, the embodiment can further include: when the patient has a long expiration time constant RCexp or a high frequency, resulting in that the patient end flow rate does not converge to a zero baseline during expiration, so that the steady state interval can be determined according to the output of ΔU(k), and the leakage value is updated according to the above method, so that the leakage of the breathing device is monitored and updated in real time throughout the breathing process.

[0121] According to the experiment, the method has achieved good and stable results in the leakage monitoring and compensation of the Philips home ventilator series.

[0122] Embodiment two: as Figure 5 described, the present application provides a leakage calculation system of a ventilation device, which is used in a ventilator, the system comprises:

[0123] The state monitoring module: real-time monitoring of the leakage state of the ventilator, specifically including: when the patient is inhaling autonomously, the gradient filtering method is used to determine the output of the filter, so as to determine whether there is a leakage mutation in the patient end flow rate, and the specific implementation includes:

[0124] The identification unit is used to identify the peak flow rate through the patient end flow rate, and when the target pressure plateau flow rate slowly decreases, the patient end flow rate after gradient filtering will gradually converge to a zero baseline;

[0125] The leakage judgment unit: if there is a sudden leakage, the filter will output a positive value based on the zero baseline; if there is leakage, the leakage value updating module is performed, otherwise, the module is recycled, so as to monitor the state of the ventilation device in real time;

[0126] The leakage value updating module: the classical leakage model is used to update the value of the leakage according to the motion equation of the patient and the ventilator, so that the leakage of the breathing device is monitored and updated in real time throughout the breathing process.

[0127] The other technical features of the leakage calculation system of the ventilation device described in the embodiment are similar to the corresponding leakage calculation method of the ventilation device, which will not be described here.

[0128] In a third aspect, the present application provides a breathing ventilation device, wherein the ventilation device is installed with the leakage calculation system of the ventilation device described above, and is used to execute the leakage calculation method of the ventilation device described above.

[0129] In a fourth aspect, the present application further provides a readable storage medium, wherein the readable storage medium stores programs or instructions, and the programs or instructions are executed by the ventilation device to realize the steps of the leakage calculation method of the ventilation device described above.

[0130] Those skilled in the art will appreciate that embodiments of the present application can be devised for a variety of other systems which are currently developed or later developed. Accordingly, the present application is intended to embrace all such departures from the present disclosure as fall within the scope of the present application, including legal equivalents thereof. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application cover modifications and variations of this application provided they come within the scope of the appended claims and their equivalents.

[0131] Although preferred embodiments of the application have been described herein, those skilled in the art will appreciate that other embodiments of the application can be developed in accordance with the principles of the application described herein. Therefore, it is to be understood that the scope of the application is not to be limited to the specific embodiments illustrated herein, but only by the claims that follow, including equivalents thereof.

[0132] It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application cover modifications and variations of this application provided they come within the scope of the appended claims and their equivalents.

Claims

1. A method of calculating a leak of a ventilation device, characterized by, The method is used in a breathing machine, and comprises the following steps: S1, when the patient is in spontaneous inhalation, the gradient filtering method is used to determine the output of the filter, so as to determine whether there is a sudden leakage mutation in the patient end flow rate, specifically: the peak flow rate is identified through the patient end flow rate, when the target pressure output is stable and the flow rate slowly decreases, the patient end flow rate after gradient filtering will gradually converge to the zero baseline, at this time, if there is a sudden leakage, the filter will output a positive value on the basis of the zero baseline; if there is leakage, the next step S2 is performed, otherwise, the step S1 is recycled to monitor the state of the ventilation equipment in real time; S2, a classical leakage model is used to update the value of the leakage according to the motion equation of the patient and the breathing machine, so as to realize the real-time monitoring and updating of the leakage of the breathing equipment in the whole breathing process.

2. The method of leak calculation of a ventilation device according to claim 1, characterized in that, The filter outputs a positive value on the basis of the zero baseline if there is a sudden leakage, including: Let U(k) and y(k) be the kth output and input of the filter respectively, and let the kth input value y(k)≡Q(k), calculate the gradient filtering value ΔU(k) of the flow rate Q(k), when the flow rate baseline is zero, observe the value of |ΔU(k)|, if it is greater than a certain constant value, it is determined as leakage, otherwise, it is not leakage, and the gradient filtering is continued to identify the flow rate.

3. The method of leak calculation of a ventilation device according to claim 2, characterized in that, The calculation process of the gradient filtering value ΔU(k) includes: The k+1th input is represented as: y(k+1)=F(y(k),…,y(k-m),U(k),…,U(k-n)); Wherein, m and n represent the order of the system; A pseudo partial derivative φ(k) is introduced, which describes the sensitivity of the function to the change of other variables when a variable is disturbed, so that the above system is transformed into a dynamic linearization data model: Δy(k+1)=ΔU(k)*φ(k); Wherein: Δy(k+1)=y(k+1)-y(k), ΔU(k)=U(k)-U(k-1); A criterion function is introduced, and the criterion function is substituted into the dynamic linearization data model, then U(k) is derived, and d(U(k))=0 is obtained: where: p k is a step factor, the introduction of λ avoids singularities in which the denominator of the system can be zero, φ'(k) is the derivative of the pseudo partial derivative φ(k); The output of the system, i.e. the flow rate, is represented as:

4. The method of leak calculation of a ventilation device according to claim 3, characterized in that, The criterion function is represented as: J(u(k)) = |y'(k + 1) - y(k + 1)| 2 + λ |u(k) - u(k - 1)| 2 ; where λ is a system output variation weight coefficient, in this criterion function, since λ|U(k)-U(k-1) 2 The introduction of the term makes the system output variation limited and is able to overcome the steady-state error.

5. The method of leak calculation of a ventilation device according to claim 4, characterized in that, The classical leakage model is used to update the value of the leakage according to the motion equation of the patient and the breathing machine, including: Let the total flow rate of the system output be: Q V ; the flow rate into the patient be: Q P ; and the total leak flow rate be: Q L , introducing the classical leak model, expressed as: Q L (k) = G orf P γ (k); where G orf and γ are two parameters assumed to remain constant during a breath, and P is the pressure value at leak. Integrate the classical leakage model to obtain: Thus, the leakage coefficient is obtained: wherein in the ventilation device, if there is bi-level ventilation or single level pressure release ventilation, P = P aw when the patient is in the expiratory state, P = EPAP, where EPAP is the expiratory pressure, P aw is the airway pressure of the ventilation system.

6. The method of leak calculation of a ventilation device according to claim 5, characterized in that, Airway pressure P of the ventilation system aw The general respiratory motion equation of the patient and the ventilator is expressed as: where R and E in the model represent the respiratory resistance caused by the airway and the elastic resistance caused by the lung and chest wall, respectively, P mus Pmus is the muscle pressure of the patient, t is time; Therefore, when the respiratory system is in a steady state, at this time, whether the patient is in inhalation or exhalation, there is: P mus ＝0； When the respiratory flow rate is at steady state, there is Q' P = 0, so there is: Q L = Q V - Q P ; In a stable period of time, there is: At this time, the plateau at expiration is updated with the leak coefficient G orf .

7. A leak calculation system for a ventilation device, characterized by The system is used in a breathing machine, and comprises: The state monitoring module is used for determining the output of the filter by using the gradient filtering method to determine whether there is a sudden change in the patient end flow rate when the patient is inhaling autonomously, and specifically, the peak flow rate is identified by the patient end flow rate, when the target pressure output is stable and the flow rate slowly decreases, the patient end flow rate after the gradient filtering gradually converges to the zero baseline, at this time, if there is a sudden leakage, the filter outputs a positive value on the basis of the zero baseline; if there is leakage, the leakage value updating module is performed, otherwise, the module is recycled, so as to monitor the state of the ventilation equipment in real time. The leakage value updating module is used for updating the value of the leakage amount by using the classical leakage model according to the motion equation of the patient and the ventilator, so as to realize the real-time monitoring and updating of the leakage amount of the breathing equipment in the whole breathing process.

8. A respiratory ventilation apparatus, characterized by, The ventilation equipment is provided with the leakage calculation system of the ventilation equipment as claimed in claim 7, and is used for executing the leakage calculation method of the ventilation equipment as claimed in any one of claims 1-6.

9. A readable storage medium, characterized by, The readable storage medium stores programs or instructions, and the programs or instructions are executed by the ventilation equipment to realize the steps of the leakage calculation method of the ventilation equipment as claimed in any one of claims 1-6.

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