Multi-source Information Fusion Monitoring and Evaluation Method and System for Medical Oxygen Generator

Abstract

The present invention relates to the technical field of oxygen supply monitoring and regulation, and discloses a multi-source information fusion monitoring and evaluation method and system for medical oxygen generators, including the following steps: S101, collecting the equipment operation parameters and environmental parameters of the medical oxygen generator in real time, and obtaining the physiological demand data of the patient; S102, constructing a coupling feature for characterizing the operation state of the oxygen generator based on the equipment operation parameters and environmental parameters; S103, establishing an environmental quantification influence model of the environmental parameters on the oxygen production efficiency; S104, performing coupling analysis based on the patient physiological demand parameters, coupling features and environmental quantification influence model to determine the dynamic oxygen supply regulation strategy; S105, monitoring the operation state of the oxygen generator in real time, and triggering a hierarchical early warning when an abnormality occurs. Through multi-source data fusion and intelligent regulation, the present invention accurately matches the oxygen supply demand of the patient, optimizes the environmental adaptability, improves the oxygen supply efficiency, integrates a hierarchical early warning mechanism, realizes intelligent monitoring and abnormal protection, and improves the safety and reliability of the oxygen generator.

Description

Technical Field

[0001] The present invention belongs to the technical field of oxygen supply monitoring and regulation, and particularly relates to a multi-source information fusion monitoring and evaluation method and system for medical oxygen generators. Background Art

[0002] Medical oxygen generators are important oxygen supply devices widely used in medical institutions, and the reliability of their operating states is directly related to the life safety and clinical treatment effects of patients. The existing monitoring methods for medical oxygen generators mainly rely on single data sources or simple data superposition analysis, usually limited to basic device parameters such as temperature, pressure, and flow rate, ignoring the significant impact of environmental factors such as humidity and temperature changes on oxygen production efficiency. At the same time, data fusion methods generally lack the support of physical mechanisms and are difficult to effectively correct the monitoring errors caused by parameter fluctuations such as pressure and temperature during operation. In addition, there is a lack of effective data coupling between current device monitoring and the actual clinical needs of patients, making it difficult to achieve precise oxygen supply regulation, which may result in oxygen waste or insufficient oxygen supply for patients. Summary of the Invention

[0003] The present invention provides a multi-source information fusion monitoring and evaluation method and system for medical oxygen generators, which solves the technical problems in related technologies that lack comprehensive consideration of environmental factors and patient needs, resulting in inaccurate oxygen supply regulation, large monitoring errors, and causing oxygen waste or insufficient oxygen supply.

[0004] The present invention provides a multi-source information fusion monitoring and evaluation method and system for medical oxygen generators, including the following steps:

[0005] S101, real-time collect the device operation parameters and environmental parameters of the medical oxygen generator, and obtain the physiological demand data of the patient;

[0006] S102, based on the device operation parameters and environmental parameters, construct a coupling feature for characterizing the operation state of the oxygen generator;

[0007] S103, based on the correlation between the environmental parameters and the oxygen production efficiency, establish an environmental quantitative impact model of the environmental parameters on the oxygen production efficiency;

[0008] S104, perform coupling analysis based on the patient physiological demand parameters, coupling features, and environmental quantitative impact model to determine the dynamic oxygen supply regulation strategy;

[0009] S105, based on the coupling features, environmental quantitative impact model, and dynamic oxygen supply regulation strategy, real-time monitor the operation state of the oxygen generator and trigger a hierarchical warning when abnormal.

[0010] Further, the device operation parameters include: pressure, temperature, oxygen flow rate, and oxygen concentration, the environmental parameters include: humidity, environmental temperature, and atmospheric pressure, and the physiological demand parameters include: demand oxygen flow rate and demand oxygen concentration.

[0011] Further, the specific steps of S102 include:

[0012] S201, construct a load characteristic according to the device operation parameters and environmental parameters, where the calculation formula of the load characteristic is:

[0013] , represents the load characteristic, represents the real-time power consumption of the device, represents the pressure of the device, represents the oxygen flow rate, represents the oxygen concentration, RH represents the humidity of the environment, represents the environmental temperature, represents the temperature of the device, and respectively represent the first weight coefficient and the second weight coefficient;

[0014] S202, construct an air path impedance characteristic according to the device operation parameters and environmental parameters, where the calculation formula of the air path impedance characteristic is:

[0015] , represents the air path impedance characteristic, and respectively represent the maximum pressure and the minimum pressure during the device operation cycle, and respectively represent the maximum value and the minimum value of the oxygen flow rate during the device operation cycle, represents the third weight coefficient;

[0016] S203, construct an oxygen supply matching degree characteristic according to the device operation parameters and environmental parameters, where the calculation formula of the oxygen supply matching degree characteristic is:

[0017] , represents the oxygen supply matching degree characteristic, represents the current required oxygen flow rate of the patient, represents the current required oxygen concentration of the patient, represents a very small positive value.

[0018] Further, the construction steps of the environmental quantification influence model include:

[0019] S301, establish a humidity correction term and a temperature correction term based on the inhibitory effects of humidity and temperature on the molecular sieve adsorption efficiency, and sequentially correct the preset reference oxygen generation efficiency;

[0020] S302, construct a pressure correction term based on the gas flow equation and correct the preset reference oxygen generation efficiency;

[0021] S303. Construct a comprehensive oxygen generation efficiency formula based on the humidity correction term, temperature correction term, and air pressure correction term. The comprehensive oxygen generation efficiency formula is as follows:

[0022] , represents the comprehensive oxygen generation efficiency, represents the preset reference oxygen generation efficiency, represents the humidity correction coefficient, represents the adsorption activation energy of the molecular sieve, R represents the gas constant, represents the current atmospheric pressure, represents the standard atmospheric pressure.

[0023] Furthermore, calculate the comprehensive oxygen generation efficiency according to the comprehensive oxygen generation efficiency formula of the environmental quantification impact model, and calculate the ratio of the actual oxygen demand to the actual oxygen supply capacity of the equipment according to the physiological demand parameters to obtain the target oxygen flow rate. Among them, the actual oxygen demand is obtained by multiplying the demand oxygen flow rate and the demand oxygen concentration, and the actual oxygen supply capacity is obtained by multiplying the comprehensive oxygen generation efficiency and the current oxygen concentration.

[0024] Furthermore, generate a dynamic oxygen supply control strategy based on the coupling characteristics constructed by the target oxygen flow rate and S102, including:

[0025] Flow rate control mechanism: Adjust the oxygen flow rate to the target oxygen flow rate;

[0026] Pressure control mechanism: Calculate the system pressure set value according to the gas path impedance characteristics, and adjust the pressure of the oxygen generator when the gas path impedance characteristics change;

[0027] Abnormal handling mechanism: When the load characteristics exceed the load threshold or the gas path impedance characteristics exceed the gas path impedance threshold, trigger a load reduction operation.

[0028] Furthermore, the system pressure set value is obtained by multiplying the target oxygen flow rate, gas path impedance characteristics, and gas path constant, where the gas path constant is determined by the equipment gas path structure.

[0029] Furthermore, the dynamic oxygen supply control strategy satisfies the following constraint conditions:

[0030] Load constraint: If the load characteristics exceed the load threshold, then limit the increase in oxygen flow rate not to exceed the preset safety value;

[0031] Gas path health constraint: If the gas path impedance characteristics exceed the gas path impedance threshold, then trigger a pressure reduction operation;

[0032] Matching degree constraint: If the oxygen supply matching degree is lower than the oxygen supply matching threshold, then trigger a flow rate-concentration coordinated adjustment, and the adjustment strategy is: give priority to adjusting the oxygen concentration, and the sub-optimal adjustment is the oxygen flow rate.

[0033] The present invention provides a multi-source information fusion monitoring and evaluation system for medical oxygen generators, including:

[0034] A data acquisition module, configured to collect the device operation parameters and environmental parameters of the medical oxygen generator in real time, and obtain the physiological demand data of the patient;

[0035] A state feature construction module, configured to construct a coupling feature for characterizing the operation state of the oxygen generator according to the device operation parameters and environmental parameters;

[0036] An environmental impact modeling module, configured to establish an environmental quantitative impact model of the environmental parameters on the oxygen generation efficiency according to the correlation between the environmental parameters and the oxygen generation efficiency;

[0037] A dynamic oxygen supply regulation module, configured to perform coupling analysis according to the patient physiological demand parameters, coupling features and environmental quantitative impact model, and determine a dynamic oxygen supply regulation strategy;

[0038] A monitoring and early warning module, configured to monitor the operation state of the oxygen generator in real time according to the coupling features, environmental quantitative impact model and dynamic oxygen supply regulation strategy, and trigger a hierarchical early warning when abnormal.

[0039] The beneficial effects of the present invention are as follows: Through multi-source data fusion and intelligent dynamic regulation, the present invention realizes precise oxygen supply to ensure the matching of patient needs; based on the environmental quantitative impact model, the influence of humidity, temperature and air pressure on the oxygen generation efficiency is corrected to improve the adaptability of the device in complex environments; flow-concentration collaborative optimization is adopted to reduce energy consumption while meeting the oxygen supply demand and improve the energy efficiency of the device; a hierarchical early warning mechanism is integrated to monitor the device load, gas path impedance and oxygen supply matching degree in real time to prevent abnormal oxygen supply and equipment failures; it solves the problems of inaccurate oxygen supply, poor environmental adaptability, low energy efficiency and insufficient equipment failure monitoring of traditional oxygen generators. Description of the Drawings

[0040] Figure 1 is a flowchart of the multi-source information fusion monitoring and evaluation method for the medical oxygen generator of the present invention. Detailed Embodiments

[0041] Now, the subject matter described herein will be discussed with reference to example embodiments. It should be understood that discussing these embodiments is only to enable those skilled in the art to better understand and thus implement the subject matter described herein. Without departing from the protection scope of the content of this specification, changes can be made to the functions and arrangements of the elements discussed. Each example can omit, substitute or add various processes or components as needed. Additionally, the features described relative to some examples can also be combined in other examples.

[0042] As Figure 1As shown, a multi-source information fusion monitoring and evaluation method for a medical oxygen generator includes the following steps:

[0043] S101, Collect the device operation parameters and environmental parameters of the medical oxygen generator in real time, as well as the physiological demand data of the patient;

[0044] S102, Based on the device operation parameters and environmental parameters, construct a coupling feature for characterizing the operation state of the oxygen generator;

[0045] S103, Based on the correlation between the environmental parameters and the oxygen generation efficiency, establish an environmental quantification impact model of the environmental parameters on the oxygen generation efficiency;

[0046] S104, Conduct coupling analysis based on the patient physiological demand parameters, coupling features, and environmental quantification impact model to determine the dynamic oxygen supply regulation strategy;

[0047] S105, Based on the coupling features, environmental quantification impact model, and dynamic oxygen supply regulation strategy, monitor the operation state of the oxygen generator in real time and trigger a hierarchical warning when an abnormality occurs.

[0048] In an embodiment of the present invention, the device operation parameters include: pressure, temperature, oxygen flow rate, and oxygen concentration, the environmental parameters include: humidity, ambient temperature, and atmospheric pressure, and the physiological demand parameters include: required oxygen flow rate and required oxygen concentration.

[0049] In an embodiment of the present invention, a piezoresistive pressure sensor is installed at the outlet of the air compressor and inside the molecular sieve tank to collect the internal gas pressure of the oxygen generator; thermistor sensors are arranged at the outlet of the compressor and on the surface of the molecular sieve tank to collect the device operation temperature; a thermal gas mass flowmeter is installed at the oxygen outlet end of the oxygen generator to monitor the oxygen flow rate; an ultrasonic oxygen concentration sensor is used to measure the oxygen concentration at the oxygen outlet end; current data is collected at the power input end of the main motor or compressor of the oxygen generator through a current transformer; a thermistor is used to collect the indoor ambient temperature in the device installation area; a resistive humidity sensor is used to collect humidity data; a piezoresistive pressure sensor is used to measure the atmospheric pressure; the required oxygen flow rate and required oxygen concentration of the patient are set by the doctor according to the patient's condition and clinical guidelines.

[0050] In an embodiment of the present invention, the unit of pressure is kPa, the unit of temperature is °C, the unit of oxygen flow rate is L / min, the unit of oxygen concentration is %, the unit of current is A, the unit of ambient temperature is °C, the unit of humidity is %RH, and the unit of atmospheric pressure is kPa.

[0051] In an embodiment of the present invention, the specific steps of S102 include:

[0052] S201. Construct a load characteristic based on the device operation parameters and environmental parameters. The calculation formula for the load characteristic is as follows:

[0053] , represents the load characteristic, which is used to measure the energy required for unit oxygen production and reflects the operating load of the device. An increase in this characteristic indicates an increase in the power consumption required for unit oxygen production, which may be due to an excessive device load. Conversely, a lower value indicates lower operating energy consumption of the device, which may be due to a better operating environment. represents the real-time power consumption of the device. represents the pressure of the device. represents the oxygen flow rate. represents the oxygen concentration, and RH represents the humidity of the environment. represents the environmental temperature. represents the temperature of the device. and respectively represent the first weight coefficient and the second weight coefficient, which are respectively used to correct the influence of humidity and environmental temperature on the load of the oxygen generator.

[0054] S202. Construct an air circuit impedance characteristic based on the device operation parameters and environmental parameters. The calculation formula for the air circuit impedance characteristic is as follows:

[0055] , represents the air circuit impedance characteristic, which is used to measure the air circuit impedance situation of the device and determine whether there is blockage or leakage in the air circuit system of the oxygen generator. and respectively represent the maximum pressure and the minimum pressure within the device operation cycle. and respectively represent the maximum value and the minimum value of the oxygen flow rate within the device operation cycle. represents the third weight coefficient, which is used to correct the influence of temperature on the air circuit pressure fluctuation. The device operation cycle refers to the time period for the medical oxygen generator to complete a complete work cycle.

[0056] S203. Construct an oxygen supply matching degree characteristic based on the device operation parameters and environmental parameters. The calculation formula for the oxygen supply matching degree characteristic is as follows:

[0057] , represents the oxygen supply matching degree characteristic, which is used to measure whether the current oxygen supply meets the patient's needs. The higher the oxygen supply matching degree characteristic, the better the oxygen supply effect. Conversely, the worse the oxygen supply effect. represents the current required oxygen flow rate of the patient, and this value is a preset value. represents the current required oxygen concentration of the patient, and this value is a preset value. represents an extremely small positive value to prevent the denominator from being zero.

[0058] In one embodiment of the present invention, the correlation between environmental parameters and oxygen generation efficiency includes:

[0059] An increase in environmental humidity leads to a decrease in oxygen generation efficiency. Specifically, the ability of the molecular sieve to adsorb nitrogen is affected by air humidity, and high humidity will reduce the nitrogen adsorption efficiency, thereby reducing the oxygen concentration and oxygen generation efficiency;

[0060] An increase in environmental temperature leads to a decrease in oxygen generation efficiency. Specifically, the higher the temperature, the lower the rate of nitrogen adsorption by the molecular sieve, and the lower the working efficiency of the equipment;

[0061] A decrease in atmospheric pressure leads to a decline in oxygen generation efficiency. Specifically, atmospheric pressure affects air density and intake air flow rate, thereby affecting oxygen generation efficiency.

[0062] In one embodiment of the present invention, the oxygen generator is operated under standard conditions to measure the reference oxygen generation efficiency, and the oxygen generator is operated under different humidity, temperature, and atmospheric pressure conditions respectively to measure the oxygen flow rate and oxygen concentration, and a quantitative relationship between environmental parameters and oxygen generation efficiency is established, where the standard conditions are: humidity 40%, temperature 25 °C, and atmospheric pressure 101.3 kPa.

[0063] In one embodiment of the present invention, the steps for constructing the environmental quantification influence model include:

[0064] S301, establish a humidity correction term and a temperature correction term based on the inhibitory effect of humidity and temperature on the adsorption efficiency of the molecular sieve, and sequentially correct the preset reference oxygen generation efficiency. Specifically, first perform humidity correction and then perform temperature correction.

[0065] The calculation formula for the humidity correction term is: ,

[0066] The calculation formula for the temperature correction term is: , represents the oxygen generation efficiency after humidity correction, represents the oxygen generation efficiency after temperature correction, represents the reference oxygen generation efficiency, represents the humidity correction coefficient, which is used to adjust the influence degree of humidity on the adsorption of the molecular sieve, represents the adsorption activation energy of the molecular sieve, R represents the gas constant, and the gas constant is 8.314 , determined through experiments;

[0067] S302, construct a pressure correction term based on the gas flow equation to correct the preset reference oxygen generation efficiency, where the calculation formula for the pressure correction term is: , represents the oxygen generation efficiency after atmospheric pressure correction, represents the current atmospheric pressure, represents the standard atmospheric pressure, i.e., 101.3 kPa, represents the air pressure correction coefficient;

[0068] S303. Construct a comprehensive oxygen generation efficiency formula based on the humidity correction term, temperature correction term, and air pressure correction term. Among them, the comprehensive oxygen generation efficiency formula is:

[0069] , represents the comprehensive oxygen generation efficiency.

[0070] In an embodiment of the present invention, in the positive pressure environment of the operating room, the effective intake pressure of the oxygen generator needs to be greater than the minimum intake pressure threshold to ensure the normal operation of the oxygen generator. Among them, the effective intake pressure is obtained by the difference between the atmospheric pressure of the equipment environment and the positive pressure value inside the operating room. If it is monitored that the effective intake pressure is less than the minimum intake pressure threshold, it is determined that the intake pressure is insufficient, triggering an abnormal alarm mechanism, recording the abnormal state, and taking the following measures: prompting to adjust the installation position of the oxygen generator to reduce the intake resistance; adjusting the ventilation system of the operating room to optimize the pressure difference between indoors and outdoors; triggering the protection mode of the oxygen generator to prevent system failures caused by insufficient intake.

[0071] In an embodiment of the present invention, the comprehensive oxygen generation efficiency is calculated according to the comprehensive oxygen generation efficiency formula of the environmental quantification impact model, and the ratio of the actual oxygen demand to the actual oxygen supply capacity of the equipment is calculated according to the physiological demand parameters to obtain the target oxygen flow. Among them, the actual oxygen demand is obtained by the product of the demand oxygen flow and the demand oxygen concentration, and the actual oxygen supply capacity is obtained by the product of the comprehensive oxygen generation efficiency and the current oxygen concentration.

[0072] In an embodiment of the present invention, the comprehensive oxygen generation efficiency is calculated through the environmental quantification impact model, and the target oxygen flow is accurately calculated based on the patient's physiological demand parameters to ensure the oxygen supply matching. By dynamically adjusting the oxygen supply amount according to the ratio of the actual oxygen demand to the actual oxygen supply capacity of the equipment, it can accurately adapt to the needs of different patients, optimize the energy efficiency of the equipment at the same time, and avoid oxygen waste or insufficient oxygen supply. This method combines environmental impact, adaptive adjustment, and efficient calculation, making the oxygen supply system more intelligent, improving the comfort of patients, effectively extending the service life of the oxygen generation equipment, and reducing the operating cost.

[0073] In an embodiment of the present invention, a dynamic oxygen supply regulation strategy is generated based on the coupling characteristics constructed by the target oxygen flow and S102, including:

[0074] Flow regulation mechanism: Adjust the oxygen flow to the target oxygen flow;

[0075] Pressure regulation mechanism: Calculate the system pressure set value according to the gas path impedance characteristics, and adjust the pressure of the oxygen generator when the gas path impedance characteristics change to maintain a stable flow rate. For example, when the gas path is blocked and the gas path impedance characteristics increase, the pressure of the oxygen generator needs to be increased to maintain the target oxygen flow rate. When the gas path leaks and the gas path impedance decreases, the pressure of the oxygen generator needs to be decreased to avoid overpressure;

[0076] Abnormal handling mechanism: When the load characteristics exceed the load threshold or the gas path impedance characteristics exceed the gas path impedance threshold, trigger a load reduction operation, that is, reduce the load, such as reducing the oxygen flow rate, switching to a standby gas path, etc., to avoid damage or failure of the equipment due to overload.

[0077] In an embodiment of the present invention, the system pressure set value is obtained by multiplying the target oxygen flow rate, the gas path impedance characteristics, and the gas path constant. The calculation formula for the system pressure set value is:

[0078] , where, represents the system pressure set value, represents the target oxygen flow rate, K represents the gas path constant, where the gas path constant is determined by the equipment gas path structure and is measured through experiments.

[0079] In an embodiment of the present invention, the dynamic oxygen supply regulation strategy satisfies the following constraint conditions:

[0080] Load constraint: If the load characteristics exceed the load threshold, then limit the increase in oxygen flow rate not to exceed a preset safety value, such as 5%;

[0081] Gas path health constraint: If the gas path impedance characteristics exceed the gas path impedance threshold, then trigger a pressure reduction operation, that is, reduce the equipment pressure;

[0082] Matching degree constraint: If the oxygen supply matching degree is lower than the oxygen supply matching threshold, then trigger a flow-concentration coordinated adjustment. The adjustment strategy is: give priority to adjusting the oxygen concentration, and secondarily adjust the oxygen flow rate to ensure that the total amount of oxygen actually inhaled by the patient meets the demand and avoid insufficient oxygen supply or waste. The total amount of oxygen is the product of the oxygen flow rate and the oxygen concentration.

[0083] In an embodiment of the present invention, based on the load characteristics, gas path impedance characteristics, oxygen supply matching characteristics, and comprehensive oxygen generation efficiency, the operating state of the oxygen generator is evaluated in real time. When any characteristic value exceeds the corresponding preset threshold or the comprehensive oxygen generation efficiency is lower than 70% of the reference oxygen generation efficiency, trigger a hierarchical warning mechanism. The hierarchical warning mechanism includes:

[0084] When a single indicator exceeds the limit, a first-level warning is triggered, and the warning actions are: a pop-up window appears on the system interface, the abnormal indicator is marked, and it is recommended to check the operating environment or the gas path status. For example, when only the load characteristic exceeds the load threshold, the warning actions are: a pop-up window appears on the system interface, the high load is marked, and it is recommended to check the operating environment;

[0085] When two indicators exceed the limit, a second-level warning is triggered, and the warning actions are: triggering a buzzer alarm, automatically performing a load reduction operation, and switching to the standby gas path. For example, when the load characteristic exceeds the limit and the comprehensive oxygen production efficiency is lower than 80% of the reference oxygen production efficiency, the increase in oxygen flow is restricted to less than 5%, and a prompt "The oxygen supply efficiency has decreased, and manual intervention is recommended" is given;

[0086] When the oxygen supply matching degree is less than 0.6 and the gas path impedance characteristic exceeds the limit, or the comprehensive oxygen production efficiency is lower than half of the reference oxygen production efficiency, a third-level warning is triggered, and the warning actions are: forced entry into the safe mode, the flow rate is reduced to the minimum guarantee value, the non-core modules are closed, and the emergency fault code is uploaded.

[0087] In an embodiment of the present invention, a multi-source information fusion monitoring and evaluation system for a medical oxygen generator is further provided, including:

[0088] A data acquisition module for real-time collecting the device operation parameters and environmental parameters of the medical oxygen generator and obtaining the physiological demand data of the patient;

[0089] A state characteristic construction module for constructing a coupling characteristic for characterizing the operation state of the oxygen generator according to the device operation parameters and environmental parameters;

[0090] An environmental impact modeling module for establishing an environmental quantitative impact model of environmental parameters on oxygen production efficiency according to the correlation between environmental parameters and oxygen production efficiency;

[0091] A dynamic oxygen supply regulation module for performing coupling analysis according to the patient physiological demand parameters, coupling characteristics and environmental quantitative impact model to determine the dynamic oxygen supply regulation strategy;

[0092] A monitoring and warning module for real-time monitoring the operation state of the oxygen generator according to the coupling characteristics, environmental quantitative impact model and dynamic oxygen supply regulation strategy, and triggering a hierarchical warning when abnormal.

[0093] The above describes the embodiments of the present invention, but the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of this embodiment, those of ordinary skill in the art can also make many forms, all of which fall within the protection scope of this embodiment.

Claims

1. A multi-source information fusion monitoring and evaluation method for medical oxygen generators, characterized in that It includes the following steps: S101, Collect the device operation parameters and environmental parameters of the medical oxygen generator in real time, and obtain the physiological demand data of the patient; S102, Based on the device operation parameters and environmental parameters, construct a coupling feature for characterizing the operation state of the oxygen generator; S103, Based on the correlation between the environmental parameters and the oxygen generation efficiency, establish an environmental quantization impact model of the environmental parameters on the oxygen generation efficiency; Among them, the construction steps of the environmental quantization impact model include: S301, establish a humidity correction term and a temperature correction term based on the inhibitory effects of humidity and temperature on the molecular sieve adsorption efficiency, and correct the preset reference oxygen generation efficiency in sequence; among them, the calculation formula for the humidity correction term is: , and the calculation formula for the temperature correction term is: , represents the oxygen generation efficiency after humidity correction, represents the oxygen generation efficiency after temperature correction, represents the reference oxygen generation efficiency, represents the humidity correction coefficient, represents the adsorption activation energy of the molecular sieve, R represents the gas constant, RH represents the humidity of the environment, represents the environmental temperature; S302. Construct a barometric pressure correction term based on the gas flow equation to correct the preset reference oxygen production efficiency. The calculation formula for the barometric pressure correction term is: , represents the oxygen production efficiency corrected by the atmospheric pressure, represents the current atmospheric pressure, represents the standard atmospheric pressure, represents the barometric pressure correction coefficient; S303. Construct a comprehensive oxygen generation efficiency formula based on the humidity correction term, temperature correction term, and air pressure correction term. Among them, the comprehensive oxygen generation efficiency formula is: , represents the comprehensive oxygen generation efficiency; S104, Conduct coupling analysis based on the patient physiological demand parameters, coupling feature, and environmental quantization impact model to determine the dynamic oxygen supply control strategy; Among them, the comprehensive oxygen generation efficiency is calculated according to the comprehensive oxygen generation efficiency formula of the environmental quantization impact model, and the ratio of the actual oxygen demand to the actual oxygen supply capacity of the device is calculated according to the physiological demand parameters to obtain the target oxygen flow. Among them, the actual oxygen demand is obtained by the product of the required oxygen flow and the required oxygen concentration, and the actual oxygen supply capacity is obtained by the product of the comprehensive oxygen generation efficiency and the current oxygen concentration; The dynamic oxygen supply control strategy includes: Flow control mechanism: Adjust the oxygen flow to the target oxygen flow; Pressure control mechanism: Calculate the system pressure set value according to the gas path impedance feature, and adjust the pressure of the oxygen generator when the gas path impedance feature changes; Abnormal handling mechanism: When the load feature exceeds the load threshold or the gas path impedance feature exceeds the gas path impedance threshold, trigger a load reduction operation; S105, Based on the coupling feature, environmental quantization impact model, and dynamic oxygen supply control strategy, monitor the operation state of the oxygen generator in real time, and trigger a hierarchical warning when abnormal.

2. The multi-source information fusion monitoring and evaluation method for medical oxygen generators according to claim 1, wherein, The device operation parameters include: pressure, temperature, oxygen flow, and oxygen concentration. The environmental parameters include: humidity, environmental temperature, and atmospheric pressure. The physiological demand parameters include: required oxygen flow and required oxygen concentration.

3. The multi-source information fusion monitoring and evaluation method for medical oxygen generators according to claim 1, wherein The specific steps of S102 include: S201, Construct a load feature according to the device operation parameters and environmental parameters. Among them, the load feature is calculated by the ratio of the real-time power consumption of the device to the oxygen supply capacity of the device, and it is corrected by combining the influence of environmental temperature change and humidity; S202, Construct a gas path impedance feature according to the device operation parameters and environmental parameters. Among them, the gas path impedance feature is calculated by the ratio of the gas path pressure change to the oxygen flow fluctuation during the device operation cycle, and it is corrected by combining the change of environmental temperature; S203, Construct an oxygen supply matching degree feature according to the device operation parameters and environmental parameters. Among them, the actual oxygen supply of the device is calculated by the product of the current oxygen flow and oxygen concentration, and it is compared with the product of the required oxygen flow and required oxygen concentration of the patient, and then the oxygen supply matching degree feature is calculated.

4. The multi-source information fusion monitoring and evaluation method for medical oxygen generators according to claim 3, characterized in that, The system pressure set value is obtained by the product of the target oxygen flow, gas path impedance feature, and gas path constant, where the gas path constant is determined by the device gas path structure.

5. The multi-source information fusion monitoring and evaluation method for medical oxygen generators according to claim 1, characterized in that The dynamic oxygen supply control strategy satisfies the following constraint conditions: Load constraint: If the load feature exceeds the load threshold, then limit the oxygen flow increase not to exceed the preset safety value; Gas path health constraint: If the gas path impedance feature exceeds the gas path impedance threshold, trigger a pressure reduction operation; Matching degree constraint: If the oxygen supply matching degree is lower than the oxygen supply matching threshold, the flow-concentration coordinated adjustment is triggered, and the adjustment strategy is as follows: First, adjust the oxygen concentration, and secondarily, adjust the oxygen flow rate.

6. Medical oxygen generator multi-source information fusion monitoring and evaluation system, characterized in that, Adopt the multi-source information fusion monitoring and evaluation method for a medical oxygen generator as described in any one of claims 1-5, including: A data acquisition module, configured to collect the device operation parameters and environmental parameters of the medical oxygen generator in real time, and obtain the physiological demand data of the patient; A state feature construction module, configured to construct a coupling feature for characterizing the operation state of the oxygen generator according to the device operation parameters and environmental parameters; An environmental impact modeling module, configured to establish an environmental quantitative impact model of environmental parameters on oxygen generation efficiency according to the correlation between environmental parameters and oxygen generation efficiency; A dynamic oxygen supply regulation module, configured to perform coupling analysis according to the patient physiological demand parameters, coupling features, and environmental quantitative impact model to determine a dynamic oxygen supply regulation strategy; A monitoring and early warning module, configured to monitor the operation state of the oxygen generator in real time according to the coupling features, environmental quantitative impact model, and dynamic oxygen supply regulation strategy, and trigger a hierarchical early warning when an abnormality occurs.

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