Portable high-altitude pressurizing cabin and intelligent control system thereof

Abstract

The invention belongs to the technical field of pressure vessel leakage detection and safety control, and provides a portable high-altitude pressurized cabin and an intelligent control system thereof. The intelligent control system comprises a high-precision pressure sensing array, an intelligent flow sensing unit, a double-layer leakage diagnosis model and a brushless turbocharging module. By constructing the double-layer leakage diagnosis model, real-time online intelligent diagnosis of the sealing state of the pressure container is realized for the first time, and the control strategy is adaptively adjusted based on the diagnosis result and the environment pressure, so that the technical problem that the prior art cannot give consideration to light weight, rapid pressurization, stable pressure maintenance and high safety redundancy is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of pressure vessel leak detection and safety control technology, and more specifically, to a portable high-altitude pressurization chamber and its intelligent control system. Background Technology

[0002] Currently, pressure vessel systems for maintaining life support in high-altitude environments mainly have the following technical solutions and shortcomings:

[0003] Portable oxygen cylinders / oxygen concentrators can only provide short-term oxygen supplementation and cannot establish and maintain a stable absolute pressure environment; the improvement in the user's blood oxygen saturation (SpO2) is limited, and physiological indicators drop rapidly after use, failing to fundamentally solve the problem of high-altitude hypoxia.

[0004] Fixed hyperbaric oxygen chambers: Although they can provide a stable high-pressure environment, they are large in size, heavy in weight, and heavily dependent on fixed infrastructure (such as buildings and electricity), making them difficult to deploy and transport quickly in field emergency rescue scenarios.

[0005] Inflatable tents / positive pressure bags: While offering some portability, they generally suffer from the following systemic defects:

[0006] 1. Insufficient airtightness: High leakage rate at material joints, door seals, etc., making it difficult to maintain pressure.

[0007] 2. Large cabin pressure fluctuations: simple and crude control strategies (such as on / off control) result in poor comfort.

[0008] 3. Lack of intelligent safety redundancy: Usually only a single mechanical pressure relief valve is installed, which cannot cope with complex faults.

[0009] 4. Weak structural resistance to inflation: Poor structural stability after inflation, affecting safety and reliability.

[0010] 5. No leak diagnosis capability: It is completely impossible to perceive and assess the sealing health status of the compartment.

[0011] In summary, existing technologies lack a systematic solution that balances lightweight design, rapid pressurization, stable pressure maintenance, multiple safety redundancies, and efficient folding performance. Particularly noteworthy is the lack of real-time online diagnostics of cabin leakage during equipment operation. These solutions cannot distinguish between normal, slow material leakage and sudden, abnormal leaks, nor can they adaptively adjust control strategies based on real-time leakage conditions and changes in the external environment, posing safety risks. Summary of the Invention

[0012] To address the aforementioned technical problems, this invention provides a portable high-altitude pressurization chamber and its intelligent control system.

[0013] This invention provides an intelligent control system, comprising a high-precision pressure sensor array, an intelligent flow sensor unit, a dual-layer leak diagnosis model, and a brushless turbocharger module; wherein,

[0014] The high-precision pressure sensor array is configured to monitor the internal pressure of the pressure vessel;

[0015] The intelligent flow sensing unit is configured to monitor the gas replenishment flow rate of the gas being replenished into the pressure vessel.

[0016] The dual-layer leakage diagnosis model is configured to: calculate the background leakage rate of the pressure vessel based on the natural decay rate of the internal pressure monitored by the high-precision pressure sensor array during the pressure stabilization phase; and, calculate the dynamic leakage rate of the pressure vessel in real time based on the replenishment flow rate monitored by the intelligent flow sensor unit and the internal pressure rise rate monitored by the high-precision pressure sensor array during the replenishment phase; calculate the ratio of the dynamic leakage rate to the background leakage rate, and generate corresponding leakage status diagnosis signals and early warning signals according to the predetermined range of the ratio.

[0017] The brushless turbocharger module is configured to pressurize the pressure vessel in response to the warning signal.

[0018] As an example, the background leakage rate of the pressure vessel is calculated based on the natural decay rate of the internal pressure monitored by the high-precision pressure sensing array during the pressure stabilization phase, including:

[0019] During the pressure stabilization phase, the ratio of the internal pressure drop within a first preset time period to the first preset time period is obtained as the natural pressure decay rate.

[0020] The background leakage rate is calculated based on the natural pressure decay rate, the volume of the pressure vessel, the standard atmospheric pressure, and the first preset duration.

[0021] As an example, based on the replenishment flow rate monitored by the intelligent flow sensing unit during the replenishment phase and the internal pressure rise rate monitored by the high-precision pressure sensing array, the dynamic leakage rate of the pressure vessel is calculated in real time, including:

[0022] During the air replenishment phase, the ratio of the internal pressure rise within a second preset time period to the second preset time period is obtained as the pressure rise rate, and the average air replenishment flow rate monitored by the intelligent flow sensing unit within the second preset time period is obtained.

[0023] A dynamic equation is established based on the law of conservation of mass, and the dynamic leakage rate is calculated.

[0024] As an example, if the brushless turbocharger module includes an adaptive PID controller, then the pressurization operation of the pressure vessel in response to the warning signal includes:

[0025] The adaptive PID controller receives the dynamic leakage rate calculated in real time by the dual-layer leakage diagnosis model and the environmental pressure monitored by the high-precision pressure sensor array.

[0026] The dynamic leakage rate and the environmental pressure are used as compensation parameters, and their proportional coefficient and integral coefficient are dynamically adjusted. The adjustment strategy is as follows: when the dynamic leakage rate increases or the environmental pressure decreases, the proportional coefficient is automatically increased and the integral coefficient is decreased.

[0027] A control signal is generated based on the adjusted proportional and integral coefficients to drive the brushless turbocharger module to maintain the internal pressure of the pressure vessel within the target range.

[0028] As an example, the dynamic leakage rate and the environmental pressure are used as compensation parameters, and their proportional coefficient and integral coefficient are dynamically adjusted, including:

[0029] The pre-constructed state-space prediction model, which includes dynamic leakage rate as a measurable disturbance term, is retrieved, along with an optimization objective function that targets the integral of the pressure tracking error over a finite future time domain and the output energy of the adaptive PID controller.

[0030] In each control cycle, based on the currently measured cabin pressure, the ambient pressure, and the dynamic leakage rate, and with the minimization of the optimization objective function as the criterion, a set of optimal proportional coefficients and integral coefficient sequences are obtained online.

[0031] The proportional and integral coefficients in the sequence are updated in real time to the adaptive PID controller to generate the control signal for the current control cycle.

[0032] As an example, in the process of obtaining a set of optimal proportional and integral coefficient sequences through online solution, the number of control cycles contained in the future finite time domain is dynamically adjustable, specifically:

[0033] When the rate of increase of the dynamic leakage rate exceeds the first set threshold, or the rate of change of the environmental pressure exceeds the second set threshold, the number of control cycles contained in the future finite time domain is automatically reduced.

[0034] When the dynamic leakage rate remains stable and its value is lower than the third set threshold, and the rate of change of the environmental pressure is lower than the fourth set threshold, the number of control cycles contained in the future finite time domain is automatically increased.

[0035] The present invention also provides a portable high-altitude pressurization chamber employing an intelligent control system as described in any of the preceding claims, comprising an outer layer, an inner layer, a carbon fiber keel, a constraint mesh, an air cushion, an air cushion inlet, a pressurization inlet, an outer layer door, a transition chamber, an inner layer door, and an observation window.

[0036] As an example, the portable high-altitude pressurization chamber also includes an air pump, a pressure sensor, and a flow sensor.

[0037] As an example, the portable high-altitude pressurization chamber also includes an MCU, a solenoid valve, a mechanical valve, an explosion-proof seam, and a display unit.

[0038] As an example, the portable high-altitude pressurization chamber also includes an oxygen concentration monitoring unit and a temperature sensing unit.

[0039] The beneficial technical effects of this invention are at least as follows: By constructing a dual-layer leakage diagnosis model, this invention achieves real-time online intelligent diagnosis of the sealing status of pressure vessels for the first time, and adaptively adjusts the control strategy based on the diagnosis results and environmental pressure, thereby effectively solving the technical problems of existing technologies that cannot simultaneously achieve lightweight, rapid pressurization, stable pressure maintenance and high safety redundancy. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the structure of an intelligent control system disclosed in an embodiment of the present invention;

[0041] Figure 2 This is a schematic diagram of the overall structure of the portable high-altitude pressurization chamber disclosed in an embodiment of the present invention;

[0042] Figure 3 This is an exploded view of the cabin material and frame of the portable high-altitude pressurized cabin disclosed in an embodiment of the present invention;

[0043] Figure 4 This is a schematic diagram of the dual-door structure of the portable high-altitude pressurized cabin disclosed in an embodiment of the present invention;

[0044] Figure 5 This is a constrained mesh routing diagram of the portable high-altitude pressurized chamber disclosed in an embodiment of the present invention;

[0045] Figure 6 This is a comparison diagram of the unfolded and folded states of the portable high-altitude pressurized cabin disclosed in an embodiment of the present invention.

[0046] Reference numerals: 1: Outer layer; 2: Inner layer; 3: Carbon fiber keel; 4: Constraint mesh; 5: Air cushion; 6: Air cushion port; 7: Pressurization port; 8: Outer door; 9: Transition chamber; 10: Inner door; 11: Observation window; 12: Air pump; 13: Pressure sensor; 14: MCU; 15: Solenoid valve; 16: Mechanical valve; 17: Explosion-proof seam; 18: Flow sensor; 19: Display unit; 100: Intelligent control system; 1001: High-precision pressure sensor array; 1002: Intelligent flow sensor unit; 1003: Dual-layer leakage diagnosis model; 1004: Brushless turbocharger module. Detailed Implementation

[0047] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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, 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.

[0049] To facilitate understanding of the embodiments of the present invention, further explanations and descriptions will be provided below with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0050] like Figure 1 As shown, this embodiment of the invention discloses an intelligent control system 100, which includes a high-precision pressure sensor array 1001, an intelligent flow sensor unit 1002, a dual-layer leak diagnosis model 1003, and a brushless turbocharger module 1004; wherein,

[0051] The high-precision pressure sensor array 1001 is configured to monitor the internal pressure of the pressure vessel;

[0052] In practice, this typically includes at least one internal absolute pressure sensor deployed inside the pressure vessel to continuously and accurately monitor the internal absolute pressure value (P). cabin Its accuracy can reach ±0.1 kPa. Preferably, the array may also include an external environmental pressure sensor for real-time monitoring of external environmental pressure (P). env This provides the system with altitude information, which serves as a key input for subsequent environmental adaptive control, and will be explained in detail later.

[0053] The intelligent flow sensing unit 1002 is configured to monitor the gas replenishment flow rate into the pressure vessel.

[0054] In practical implementation, this intelligent flow sensing unit can be integrated into the outlet pipeline of the brushless turbocharger module, enabling it to accurately measure the real-time volumetric flow rate or mass flow rate (Q) during the air injection process. in It is understandable that the intelligent flow sensing unit can also have a built-in signal processing chip, which has functions such as preprocessing, filtering and self-diagnosis of the raw flow signal to ensure that the data input to the dual-layer leakage diagnosis model is accurate and reliable.

[0055] The dual-layer leakage diagnosis model 1003 is configured to: calculate the background leakage rate of the pressure vessel based on the natural decay rate of the internal pressure monitored by the high-precision pressure sensor array during the pressure stabilization phase; and, calculate the dynamic leakage rate of the pressure vessel in real time based on the replenishment flow rate monitored by the intelligent flow sensor unit and the internal pressure rise rate monitored by the high-precision pressure sensor array during the replenishment phase; calculate the ratio of the dynamic leakage rate to the background leakage rate, and generate corresponding leakage status diagnosis signals and early warning signals according to the predetermined range of the ratio.

[0056] The two-layer leak diagnostic model is configured to perform the following two-layer diagnostic operations to achieve an accurate assessment of the leak status:

[0057] Background Leakage Rate Learning: At specific moments (such as initial use, after maintenance, or during periodic self-inspection), the pressure vessel is controlled to enter a pressure stabilization phase (i.e., gas supply is stopped, and a seal is maintained). At this time, the dual-layer leakage diagnostic model calculates and stores the background leakage rate (L) of the pressure vessel based on the natural decay rate of the internal pressure monitored by a high-precision pressure sensor array and the known volume of the pressure vessel. base Understandably, the background leakage rate is used to characterize the inherent, slow leakage characteristics of pressure vessels in terms of material penetration, process joints, etc., and serves as a baseline for the health of the vessel's seal.

[0058] Real-time dynamic leakage rate calculation: During the normal operation of the system and the injection phase of the brushless turbocharger module, the dual-layer leakage diagnosis model synchronously receives the injection flow rate (Q) from the intelligent flow sensing unit. in ) and the rate of increase of internal pressure (V) from the high-precision pressure sensor array rise Based on the law of conservation of mass, the dynamic leakage rate (L) under the current operating condition is calculated in real time by establishing and solving the dynamic equation. dynamic It is understandable that the dynamic leakage rate is used to characterize the total leakage of a pressure vessel in real time under the current internal pressure.

[0059] The dual-layer leakage diagnostic model calculates the dynamic leakage rate (L). dynamic ) and background leakage rate (L baseThe ratio K is used to intelligently diagnose leak conditions by comparing the K value with multiple preset threshold ranges. Specifically: if the K value is approximately equal to 1, it indicates that the leak condition is normal and consistent with the baseline; if the K value exceeds the first threshold (K1, for example, 1.5), a level one warning is triggered, generating a suggestive diagnostic signal and recommending that the operator check; if the K value exceeds a higher second threshold (K2, for example, 3.0), a level two alarm is triggered, generating the highest level warning signal, indicating that a sudden abnormal leak has occurred and immediate intervention is required.

[0060] The brushless turbocharger module 1004 is configured to pressurize the pressure vessel in response to the warning signal.

[0061] In practical implementation, the brushless turbocharger module is configured to pressurize the pressure vessel in response to a warning signal. Specifically, it receives control commands (typically PWM signals) from a dual-layer leak diagnostic model and precisely adjusts its speed and output according to the commands to compensate for the diagnosed leak, quickly and stably maintaining the chamber pressure within the design target range. It is understood that the brushless turbocharger module utilizes brushless turbine technology, featuring fast response, high efficiency, low noise, and long lifespan, making it particularly suitable for applications requiring rapid pressurization and long-term continuous operation.

[0062] This invention, by constructing a dual-layer leakage diagnosis model, achieves for the first time real-time online intelligent diagnosis of the sealing status of pressure vessels. Based on the diagnosis results and environmental pressure, it adaptively adjusts the control strategy, thereby effectively solving the technical challenges of existing technologies that cannot simultaneously achieve lightweight design, rapid pressurization, stable pressure maintenance, and high safety redundancy.

[0063] As an example, the background leakage rate of the pressure vessel is calculated based on the natural decay rate of the internal pressure monitored by the high-precision pressure sensing array during the pressure stabilization phase, including:

[0064] During the pressure stabilization phase, the ratio of the internal pressure drop within a first preset time period to the first preset time period is obtained as the natural pressure decay rate.

[0065] The background leakage rate is calculated based on the natural pressure decay rate, the volume of the pressure vessel, the standard atmospheric pressure, and the first preset duration.

[0066] In this embodiment, after the system enters a specially controlled pressure stabilization phase (i.e., all gas supply and pressure relief operations are stopped, and the pressure vessel is in a static sealed state), a first preset duration (e.g., 5 minutes or 10 minutes) timing window is initiated. Within this timing window, a high-precision pressure sensor array continuously monitors the pressure changes inside the pressure vessel, records the internal pressure values ​​at the start and end of the timing window, and calculates the difference, i.e., the internal pressure drop (ΔP). leak This is because even if the container is well sealed, microscopic penetration of the material itself and extremely slow leakage at process seams can cause a slow drop in pressure.

[0067] The observed internal pressure drop (ΔP) leak Dividing this by the first preset time (Δt) during which the pressure decrease occurs yields an average natural rate of pressure decay (V). leak ), that is: V leak =ΔP leak / Δt. It is understandable that this natural pressure decay rate directly reflects how quickly the pressure in the pressure vessel is lost per unit time.

[0068] After obtaining the natural pressure decay rate, it is converted into the background leakage rate with standard physical meaning based on the following calculation formula: L base =(V leak *V chamber ) / (P atm *Δt). Wherein, V chamber The known fixed volume of the pressure vessel can be entered at the factory or during initialization; P atm The standard atmospheric pressure (usually taken as 101.325 kPa or 1 atm) is used as the basis for normalizing the leakage rate to standard atmospheric pressure conditions, thus making the calculated L... base It is a constant that is independent of environmental pressure and characterizes the inherent leakage characteristics of the container itself, enhancing the consistency and comparability of diagnostic results.

[0069] It is understandable that the physical essence of the above calculation formula is to convert the observed pressure change (V) into the actual pressure change. leak ), through the volume (V) of the container chamber The loss gas volume is converted into an equivalent volume of gas, then normalized to standard atmospheric pressure, and converted to a unit time to obtain a standardized background leakage rate in terms of volume / time (e.g., ml / min) or percentage / time (e.g., % / hour).

[0070] As an example, based on the replenishment flow rate monitored by the intelligent flow sensing unit during the replenishment phase and the internal pressure rise rate monitored by the high-precision pressure sensing array, the dynamic leakage rate of the pressure vessel is calculated in real time, including:

[0071] During the air replenishment phase, the ratio of the internal pressure rise within a second preset time period to the second preset time period is obtained as the pressure rise rate, and the average air replenishment flow rate monitored by the intelligent flow sensing unit within the second preset time period is obtained.

[0072] A dynamic equation is established based on the law of conservation of mass, and the dynamic leakage rate is calculated.

[0073] In this embodiment, when the system is in the normal air replenishment phase (i.e., the brushless turbocharger module is running to maintain or increase the cabin pressure), a second preset time window (e.g., 30 seconds or 1 minute) is initiated to periodically perform dynamic calculations. Within this time window, a high-precision pressure sensor array continuously monitors the pressure changes inside the pressure vessel, records the internal pressure values ​​at the start and end of the time window, and calculates the difference, i.e., the increase in internal pressure (ΔP). rise The increase in internal pressure (ΔP) rise Divide the average pressure rise rate (V) by the second preset time (Δt) during which this rise occurs, and obtain the average pressure rise rate (V) during that time period. rise ), that is, V rise =ΔP rise / Δt. Understandably, this rate of pressure increase reflects the net effect of the system's pressurization capacity.

[0074] Simultaneously, within this sliding time window, the intelligent flow sensing unit continuously monitors the instantaneous flow rate of the replenished gas, and averages all instantaneous flow rate samples within this time period to obtain the average replenished gas flow rate (Q) within this time window. in_avg Understandably, using average values ​​helps eliminate measurement noise caused by airflow pulsations and ensures the stability of the input data.

[0075] After obtaining the two key dynamic parameters mentioned above, according to the law of conservation of mass, during the gas replenishment stage, part of the gas mass (or the volumetric flow rate converted to a certain pressure) added to the pressure vessel is used to increase the gas density inside the vessel (manifested as a pressure increase), and the other part is used to compensate for the gas escaping through the leak point. Based on this, the following dynamic equation is established:

[0076] Q in_avg =K flow *V rise +L dynamic

[0077] Among them, Q in_avg K represents the average flow rate of gas actually supplied per unit time, which is the total supply of the system. flow *V riseThis represents the gas flow rate consumed to increase the internal pressure of the container, where K flow It is a system constant, which is related to the fixed volume V of the pressure vessel. chamber It relates to the physical properties of gases and can be obtained in advance through theoretical calculations or experimental calibration; L dynamic The dynamic leakage rate to be calculated represents the gas flow rate lost per unit time due to leakage from the container under the current internal pressure.

[0078] The measured Q in_avg and V rise and the known K flow Substituting into the above dynamic equation, the current dynamic leakage rate can be calculated in real time: L dynamic =Q in_avg -K flow *V rise .

[0079] As an example, if the brushless turbocharger module includes an adaptive PID controller, then the pressurization operation of the pressure vessel in response to the warning signal includes:

[0080] The adaptive PID controller receives the dynamic leakage rate calculated in real time by the dual-layer leakage diagnosis model and the environmental pressure monitored by the high-precision pressure sensor array.

[0081] The dynamic leakage rate and the environmental pressure are used as compensation parameters, and their proportional coefficient and integral coefficient are dynamically adjusted. The adjustment strategy is as follows: when the dynamic leakage rate increases or the environmental pressure decreases, the proportional coefficient is automatically increased and the integral coefficient is decreased.

[0082] A control signal is generated based on the adjusted proportional and integral coefficients to drive the brushless turbocharger module to maintain the internal pressure of the pressure vessel within the target range.

[0083] This invention embeds an adaptive PID controller into a brushless turbocharger module. Its input is no longer solely pressure deviation, but integrates multi-source key information, including: the dynamic leakage rate L calculated in real-time by a dual-layer leakage diagnosis model. dynamic This parameter precisely quantifies the intensity of the system's internal disturbances; the ambient pressure P is monitored by external sensors in a high-precision pressure sensing array. env This parameter directly reflects the external altitude conditions.

[0084] The parameters of the adaptive PID controller can dynamically self-tune based on the aforementioned multi-source key information. Its adjustment strategy involves using the dynamic leakage rate and environmental pressure as compensation parameters to dynamically adjust its proportional coefficient Kp and integral coefficient Ki. Specifically, when the dynamic leakage rate L... dynamicIncreased or environmental pressure P env When the input is reduced, the controller automatically increases the proportional coefficient Kp and decreases the integral coefficient Ki.

[0085] The physical and control principles underlying the above adjustment strategy are as follows:

[0086] Increasing the proportional gain Kp means that the adaptive PID controller will respond more rapidly and strongly to pressure deviations. When leakage worsens (increased disturbance) or at high altitudes (low ambient pressure, thin air, reduced system inertia), increasing Kp can enable the system to generate replenishment force more quickly, effectively suppressing rapid pressure drops and improving system rigidity.

[0087] Decreasing the integral coefficient Ki is equivalent to increasing the integral time, which aims to suppress integral saturation and slow down the cumulative correction rate of the system to steady-state deviations. Under large disturbances or changes in object characteristics, excessively strong integral action can easily lead to system overshoot or even oscillation. Appropriately weakening the integral action can create a good synergy with the enhanced proportional action, ensuring a rapid response to disturbances while guaranteeing a smooth return of pressure to the setpoint, avoiding large fluctuations, and thus meeting the high standard of comfort requirement of pressure fluctuation ≤ ±0.3 kPa.

[0088] Based on the real-time adjusted proportional and integral coefficients, the adaptive PID controller generates a corresponding control signal, which drives the brushless turbocharger module to operate at the optimal speed and power.

[0089] Through this closed-loop control that senses the environment, diagnoses the status, and adaptively adjusts, this implementation method can accurately compensate for gas losses caused by leakage and environmental changes, thereby quickly and stably maintaining the internal pressure of the pressure vessel within the target range.

[0090] As an example, the dynamic leakage rate and the environmental pressure are used as compensation parameters, and their proportional coefficient and integral coefficient are dynamically adjusted, including:

[0091] The pre-constructed state-space prediction model, which includes dynamic leakage rate as a measurable disturbance term, is retrieved, along with an optimization objective function that targets the integral of the pressure tracking error over a finite future time domain and the output energy of the adaptive PID controller.

[0092] In each control cycle, based on the currently measured cabin pressure, the ambient pressure, and the dynamic leakage rate, and with the minimization of the optimization objective function as the criterion, a set of optimal proportional coefficients and integral coefficient sequences are obtained online.

[0093] The proportional and integral coefficients in the sequence are updated in real time to the adaptive PID controller to generate the control signal for the current control cycle.

[0094] In this implementation, the predictive and optimization capabilities of MPC are applied to the parameter tuning process of the PID controller, thereby achieving more accurate, faster, and predictive intelligent parameter adaptation than traditional methods. Specifically:

[0095] First, the pre-built state-space prediction model and optimization objective function are retrieved. The state-space prediction model uses the dynamic leakage rate L... dynamic Incorporating it as a measurable disturbance term enables accurate prediction of the system pressure P under different control parameters, different leakage conditions, and different environmental pressures. cabin The future dynamic response.

[0096] The discrete-time state-space expression of the state-space prediction model is:

[0097] x(k+1)=A·x(k)+B·u(k)+D·L dynamic (k)

[0098] y(k)=C·x(k)

[0099] in, Let L be the system state vector, containing the cabin pressure and ambient pressure at time k; u(k) is the control input to the brushless turbocharger module at time k; dynamic (k) represents the dynamic leakage rate calculated in real time at time k, serving as the measurable disturbance input; y(k) = P cabin (k) represents the system output, i.e., the controlled variable; A, B, C, and D are the system matrix, input matrix, output matrix, and disturbance matrix, respectively.

[0100] The objective function is used to determine the optimal control parameters. It takes into account the cumulative performance over a finite period of time (optimization time domain). The standard form includes: an integral term for the pressure tracking error, which measures the accuracy of the system in tracking the pressure setpoint over a future period. Minimizing this term ensures control accuracy; and an output energy term for the adaptive PID controller, which measures the magnitude of the future control force. Minimizing this term achieves smooth control and reduces energy consumption.

[0101] The objective function to be optimized is:

[0102]

[0103] Where J is the objective function to be minimized; N p To predict the time domain length; P ref Pressure setpoint; P pre(l+i|k) is the predicted pressure value at time k+i based on the information at time k; Δu(k+i)=u(k+i)-u(k+i-1) is the rate of change of the control variable; ρ>0 is the weighting coefficient, used to balance the pressure tracking accuracy and control smoothness.

[0104] It should be noted that the above optimization problem needs to be solved in u min ≤u(k)≤u max and Δu min ≤Δu(k)≤Δu max Solving under equal constraints, the first control variable u in the optimal sequence is finally obtained. * (k) acts on the actuator.

[0105] Next, the optimal parameters are solved through online rolling optimization. Specifically, at the beginning of each control cycle, the system retrieves the latest measured value: the cabin pressure P. cabin Environmental pressure P env and dynamic leakage rate L dynamic .

[0106] Using the latest measurements as the initial state, an optimization problem is solved online, with the goal of minimizing the objective function. The decision variables in this problem are the future sequences of the proportional gain Kp and integral gain Ki of the PID controller. The optimizer seeks a set of trajectories for Kp and Ki such that, if the PID controller operates according to these parameters, the overall performance of the predicted system behavior (stress response) over a future period is optimal. The output of the optimization calculation is a set of optimal proportional gain and integral gain sequences for several future control cycles.

[0107] Next, real-time parameter updates and closed-loop control are implemented. Specifically, a rolling time-domain strategy is adopted, which does not execute the entire future parameter sequence, but only updates the instantaneous parameter values ​​corresponding to the current moment in the sequence to the adaptive PID controller. The PID controller, which has completed online parameter self-tuning, calculates and outputs the control signal for the current control cycle based on the updated and optimal Kp and Ki values ​​and the current pressure deviation, driving the brushless turbocharger module to perform precise boosting operations.

[0108] This implementation combines the long-term, multi-objective optimization capabilities of MPC with the simple structure of a PID controller. Instead of a fixed parameter adaptation rule, it achieves a high-level adaptive approach that determines the optimal parameters based on the system's future dynamic response at every moment. This allows the PID controller to anticipate upcoming environmental pressure changes and leakage disturbances, and adjust its parameters (Kp, Ki) in advance. Consequently, even in extremely complex high-altitude environments, it achieves high-quality pressure control with smaller overshoot, faster response, and stronger anti-interference capabilities.

[0109] As an example, in the process of obtaining a set of optimal proportional and integral coefficient sequences through online solution, the number of control cycles contained in the future finite time domain is dynamically adjustable, specifically:

[0110] When the rate of increase of the dynamic leakage rate exceeds the first set threshold, or the rate of change of the environmental pressure exceeds the second set threshold, the number of control cycles contained in the future finite time domain is automatically reduced.

[0111] When the dynamic leakage rate remains stable and its value is lower than the third set threshold, and the rate of change of the environmental pressure is lower than the fourth set threshold, the number of control cycles contained in the future finite time domain is automatically increased.

[0112] In this implementation, in complex scenarios such as high-altitude emergency rescue, the system's operating conditions may change abruptly from stable pressure maintenance to sudden leakage or rapid altitude changes (such as a vehicle rapidly ascending). Simultaneously, in model predictive control, the choice of the prediction time domain (i.e., the finite future time domain) directly affects the performance of the control system. A longer prediction time domain allows the optimizer to better anticipate future dynamic changes in the system, achieving more refined optimization control; while a shorter prediction time domain improves the optimizer's response speed, enabling it to respond to emergencies more quickly. To address these issues, this invention introduces a dynamic adjustment mechanism for the prediction time domain length, enabling the system to automatically select the optimal control strategy under different operating conditions.

[0113] Specifically, by continuously monitoring the changing trend of dynamic leakage rate and the rate of change of environmental pressure, the number of control cycles included in the prediction time domain is automatically adjusted:

[0114] (1) Rapid response mode under emergency conditions

[0115] When a sharp increase in the dynamic leakage rate is detected, exceeding the first set threshold, it indicates that a sudden leakage failure may have occurred in the system. At this time, the number of control cycles in the prediction time domain is automatically reduced. This adjustment allows the optimizer to focus its computational resources on near-term control effects, quickly generating powerful control commands to suppress pressure fluctuations and ensure that the system can stabilize the cabin pressure environment in a timely manner under emergency conditions.

[0116] Similarly, when the rate of change of environmental pressure exceeds the second set threshold, it indicates that the external altitude environment is undergoing drastic changes. In this case, the prediction time domain is also shortened, enabling the optimizer to quickly adapt to sudden changes in the external environment and maintain pressure stability.

[0117] (2) Fine optimization mode under stable operating conditions

[0118] When the system operation stabilizes, meaning the dynamic leakage rate remains low and changes gradually (below the third set threshold), and the environmental pressure changes only slightly (below the fourth set threshold), switch to fine optimization mode. At this point, appropriately increase the number of control cycles included in the prediction time domain, enabling the optimizer to perform longer-term and more comprehensive optimization calculations, and formulate an optimal control strategy that balances control accuracy, energy efficiency, and equipment lifespan.

[0119] By employing a condition-based predictive time-domain dynamic adjustment mechanism, this implementation enables the control system to autonomously adjust and optimize its field of view. In emergency situations, priority is given to ensuring the speed and stability of control; in stable situations, the focus is on the accuracy and economy of control. This intelligent adjustment mechanism ensures that the system maintains optimal control performance under different operating conditions, improving both the system's emergency response capability in the event of sudden failures and its overall control quality during stable operation.

[0120] This invention discloses a specific life support equipment—a portable high-altitude pressurization chamber—that integrates the aforementioned intelligent control systems. For example... Figure 2-6 As shown, the portable high-altitude pressurization chamber includes an outer layer 1, an inner layer 2, a carbon fiber keel 3, a constraint mesh 4, an air cushion 5, an air cushion port 6, a pressurization port 7, an outer door 8, a transition chamber 9, an inner door 10, and an observation window 11.

[0121] As an example, the portable high-altitude pressurization chamber also includes an air pump 12, a pressure sensor 13, and a flow sensor 18.

[0122] As an example, the portable high-altitude pressurization chamber also includes an MCU14, a solenoid valve 15, a mechanical valve 16, an explosion-proof seam 17, and a display unit 19.

[0123] The cabin adopts a double-layer composite structure of outer layer 1 and inner layer 2. The outer layer is made of high-strength 1680D nylon composite PVC, responsible for wear resistance and protection; the inner layer is made of medical-grade TPU membrane with excellent airtightness, ensuring a sealed environment under pressure. Carbon fiber keel 3 is embedded between the inner and outer layers, providing the necessary rigid support and shape retention for the entire inflatable cabin, preventing bulging and deformation; and constraint mesh 4 (such as...) A mesh of material, spaced at specific intervals (e.g., 200mm), covers the surface of the cabin, enhancing its ability to withstand internal pressure and ensuring structural safety and stability under high pressure differentials. The observation window 11 provides a physical view, alleviating the user's feeling of confinement.

[0124] The air cushion 5, as an independently inflatable bottom structure, is inflated and deflated through the air cushion port 6. This not only provides a comfortable layer isolating the occupants from the cold ground but also ensures the flatness and stability of the cabin. The pressurization port 7 is a dedicated interface for the intelligent control system to inject air into the cabin. The door system employs a double-layer airlock design consisting of an outer door 8, a transition chamber 9, and an inner door 10. Personnel enter and exit through the transition chamber, effectively preventing a sudden loss of cabin pressure caused by directly opening the inner door, thus maintaining a stable pressure environment.

[0125] Pressure sensor 13, the core of the high-precision pressure sensor array, is deployed both inside and outside the cabin to accurately monitor P_cabin (absolute cabin pressure) and P_env (ambient pressure), respectively. Flow sensor 18, the core of the intelligent flow sensing unit, is integrated into the pipeline from air pump 12 to pressurization port 7 to accurately monitor the make-up air flow rate Q_in. MCU 14 (Microcontroller Unit) runs a dual-layer leak diagnostic model and an adaptive PID control algorithm, serving as the brain of the entire system. Air pump 12 is the actuator of the brushless turbocharger module, receiving control signals from the MCU and responsible for providing a controllable and clean air source to the cabin.

[0126] In addition, the solenoid valve 15, mechanical valve 16, and explosion-proof seam 17 together constitute a three-stage pressure relief system, providing progressive safety redundancy to ensure that the cabin pressure will not exceed the safety limit under extreme circumstances. The three-stage pressure relief system specifically consists of: a first-stage solenoid valve (82 kPa), a second-stage mechanical valve (85 kPa), and a third-stage explosion-proof seam (90 kPa).

[0127] Display unit 19 serves as an intelligent interactive terminal, providing users with real-time visual displays of cabin pressure, equivalent altitude, oxygen concentration, leakage status, and system alarm information.

[0128] As an example, the portable high-altitude pressurization chamber also includes an oxygen concentration monitoring unit and a temperature sensing unit (not shown in the figure).

[0129] The oxygen concentration monitoring unit, based on electrochemical principles, monitors the CO2 concentration (range 0-30%) inside the cabin in real time, serving as a crucial input for safety decisions. The temperature sensing unit monitors the ambient temperature inside the cabin.

[0130] When this portable high-altitude pressurization chamber is deployed in high-altitude areas, its operating procedure is as follows:

[0131] Deployment and Self-Test: Deploy the cabin, inflate the air cushion 5 through air cushion port 6, and connect the power supply. After the system is powered on, MCU14 drives each sensor to perform a self-test.

[0132] Intelligent pressurization and pressure maintenance: The user sets the target pressure (or equivalent altitude) through the display unit 19. The MCU 14 starts the air pump 12 and, based on the feedback from the pressure sensor 13 and the flow sensor 18, runs an adaptive algorithm to precisely control the air pump and quickly increase the cabin pressure to the target value.

[0133] Online Monitoring and Safety Assurance: During operation, MCU14 continuously performs dual-layer leak diagnosis. Once an abnormal leak is detected (K value exceeding the limit), an alarm is immediately triggered via display unit 19, and the control strategy may be adaptively adjusted. If the pressure is abnormally high, the three-stage pressure relief system will be activated sequentially to absolutely ensure personal safety. Based on the life-saving priority mode of the above three-stage pressure relief system: In a compound fault mode, it actively executes: ① immediately stop the air pump; ② orderly depressurize to a safe intermediate pressure (e.g., 65 kPa); ③ issue the highest-level alarm. The core of this strategy is to prioritize preventing oxygen deficiency in extreme situations, rather than blindly maintaining pressure.

[0134] Although the invention has been specifically shown and described with reference to preferred embodiments, those skilled in the art will understand that various modifications in form and detail may be made without departing from the spirit and scope of the invention. Accordingly, the disclosed invention should be considered merely illustrative and limited only by the scope specified in the appended claims.

Claims

1. An intelligent control system, characterized by, The system comprises a high-precision pressure sensor array, an intelligent flow sensor unit, a double-layer leakage diagnosis model and a brushless turbocharging module. The high-precision pressure sensor array is configured to monitor the internal pressure of the pressure container. The intelligent flow sensor unit is configured to monitor the gas supplement flow into the pressure container. The double-layer leakage diagnosis model is configured to calculate the background leakage rate of the pressure container based on the natural decay rate of the internal pressure monitored by the high-precision pressure sensor array during the pressure stabilizing stage, and to calculate the dynamic leakage rate of the pressure container in real time based on the gas supplement flow monitored by the intelligent flow sensor unit and the rising rate of the internal pressure monitored by the high-precision pressure sensor array during the gas supplement stage. The brushless turbocharging module is configured to perform pressure boosting operation on the pressure container in response to the early warning signal.

2. The intelligent control system of claim 1, wherein: The background leakage rate of the pressure container is calculated based on the natural decay rate of the internal pressure monitored by the high-precision pressure sensor array during the pressure stabilizing stage, which comprises: During the pressure stabilizing stage, the ratio of the internal pressure drop within a first preset time period to the first preset time period is obtained as the pressure natural decay rate. The background leakage rate is calculated according to the pressure natural decay rate, the volume of the pressure container, the standard atmospheric pressure and the first preset time period.

3. The intelligent control system of claim 1, wherein: The dynamic leakage rate of the pressure container is calculated in real time based on the gas supplement flow monitored by the intelligent flow sensor unit and the rising rate of the internal pressure monitored by the high-precision pressure sensor array during the gas supplement stage, which comprises: During the gas supplement stage, the ratio of the internal pressure rise within a second preset time period to the second preset time period is obtained as the pressure rising rate, and the average gas supplement flow monitored by the intelligent flow sensor unit within the second preset time period is obtained. The dynamic equation is established according to the law of conservation of mass, and the dynamic leakage rate is calculated.

4. The intelligent control system of claim 1, wherein: The brushless turbocharging module comprises an adaptive PID controller, and the pressure boosting operation on the pressure container in response to the early warning signal comprises: The adaptive PID controller receives the dynamic leakage rate calculated in real time by the double-layer leakage diagnosis model and the ambient pressure monitored by the high-precision pressure sensor array. The dynamic leakage rate and the ambient pressure are used as compensation parameters to dynamically adjust their proportional coefficient and integral coefficient, wherein the adjustment strategy is to automatically increase the proportional coefficient and decrease the integral coefficient when the dynamic leakage rate increases or the ambient pressure decreases. The control signal is generated according to the adjusted proportional coefficient and integral coefficient to drive the brushless turbocharging module to operate, so as to maintain the internal pressure of the pressure container within the target range.

5. The intelligent control system of claim 4, wherein: The dynamic leakage rate and the ambient pressure are used as compensation parameters to dynamically adjust their proportional coefficient and integral coefficient, which comprises: retrieve a pre-constructed state space prediction model containing dynamic leakage rate as a measurable perturbation term, and an optimization objective function targeting the integral of pressure tracking error and the output energy of the adaptive PID controller within a future finite time horizon; at each control cycle, based on the current measured cabin pressure, the ambient pressure and the dynamic leakage rate, solve a set of optimal proportional and integral coefficient sequences online with the optimization objective function minimized as a criterion; update the instant proportional and integral coefficients in the sequence to the adaptive PID controller for generating the control signal of the current control cycle.

6. The intelligent control system of claim 5, wherein: in the process of solving a set of optimal proportional and integral coefficient sequences online, the number of control cycles contained in the future finite time horizon is dynamically adjustable, specifically: when the increasing rate of the dynamic leakage rate exceeds a first set threshold, or the changing rate of the ambient pressure exceeds a second set threshold, automatically reduce the number of control cycles contained in the future finite time horizon; when the dynamic leakage rate remains stable and its value is lower than a third set threshold, and the changing rate of the ambient pressure is lower than a fourth set threshold, automatically increase the number of control cycles contained in the future finite time horizon.

7. A portable hyperbaric chamber employing the intelligent control system according to any one of claims 1-6, characterized in that: the portable high-altitude hyperbaric chamber comprises an outer layer, an inner layer, a carbon fiber keel, a constraint grid, an air cushion, an air cushion port, a hyperbaric port, an outer layer door, a transition chamber, an inner layer door, an observation window.

8. The portable high altitude pressurized chamber of claim 7, wherein: It also includes an air pump, a pressure sensor, a flow sensor.

9. The portable high altitude pressurized chamber according to claim 7 or 8, characterized in that: It also includes an MCU, a solenoid valve, a mechanical valve, an explosion-proof joint, a display unit.

10. The portable high altitude pressurized chamber of claim 9, wherein: It also includes an oxygen concentration monitoring unit, a temperature sensing unit.

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