Intensive care unit negative pressure self-adaptive adjusting system

Abstract

The application relates to the technical field of ICU environment regulation, and discloses a negative pressure self-adaptive regulation system for an ICU ward. The system comprises a regional pressure monitoring module, a pressure gradient analysis module, an abnormal fluctuation judgment module, a negative pressure demand generation module, a fan parameter calculation module and an execution control module. The regional pressure monitoring module obtains the pressure values of the ICU ward, a buffer room and a corridor in real time; the pressure gradient analysis module calculates the pressure difference values of adjacent regions, judges the gradient state and generates an abnormal signal; the abnormal fluctuation judgment module generates an abnormal grade signal according to the abnormal signal; the negative pressure demand generation module generates a negative pressure maintenance or enhancement instruction according to the grade signal; the fan parameter calculation module calculates the target fan rotating speed and the air valve opening value in combination with the real-time pressure value of the ward; and the execution control module controls the regulation mechanism of the exhaust system according to the target parameters. The system can dynamically regulate and control the negative pressure, ensures the stability of the negative pressure of the ward and reduces the risk of harmful microorganism diffusion.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ICU environment regulation, in particular to a negative pressure self-adaptive regulation system for ICU ward. BACKGROUND

[0002] In the daily operation of ICU ward, it is crucial to maintain a stable and reasonable negative pressure environment, which is directly related to the control of harmful microorganism diffusion in the ward, and further affects the health and safety of medical staff and the cleanliness of the diagnosis and treatment environment. Currently, most ICU wards use negative pressure regulation systems with fixed parameter control mode, that is, the fan speed and air valve opening degree are pre-set to maintain the negative pressure state in the ward. This mode is difficult to cope with pressure fluctuations caused by various factors in the actual diagnosis and treatment process.

[0003] For example, in the daily diagnosis and treatment operation of ICU ward, the frequent entry and exit of medical staff will cause the door to be opened many times, and each time the door is opened will break the original air flow balance in the ward, causing the pressure in the ward to change instantaneously. The traditional fixed parameter regulation system cannot sense this pressure change in real time, and often needs a long time to restore the negative pressure in the ward to the set range. During this period of unstable pressure, there is a risk of harmful microorganisms spreading outside the ward.

[0004] The running state of medical equipment in the ICU ward also affects the negative pressure environment. Some medical equipment will produce air flow disturbance or consume air in the ward during operation, which will cause fluctuations in the pressure in the ward. The traditional regulation system lacks real-time monitoring and dynamic response mechanism, and cannot adjust the fan and air valve parameters in time according to the pressure changes caused by equipment operation, so that the negative pressure in the ward is always in an unstable state.

[0005] The traditional negative pressure regulation system usually only monitors the pressure in the ICU ward, ignoring the pressure state of the buffer room and the corridor area. In fact, a reasonable pressure gradient needs to be formed between the ICU ward, the buffer room and the corridor to effectively prevent harmful microorganisms from spreading from the ward to the buffer room and then from the buffer room to the corridor. The traditional system lacks overall monitoring and gradient analysis of the pressure in these three areas, and cannot timely discover abnormal situations of pressure gradient, further increasing the risk of harmful microorganism diffusion.

[0006] With the continuous improvement of medical level, the requirements of ICU ward for environmental control are getting higher and higher, and the traditional fixed parameter type negative pressure regulation system cannot meet the actual diagnosis and treatment needs, and a negative pressure control system that can monitor in real time, dynamically analyze and self-adaptively regulate is needed to solve the problems of pressure response lag and pressure gradient cannot be guaranteed in the current system. SUMMARY

[0007] The purpose of the present application is to provide a negative pressure adaptive adjustment system for ICU ward to solve the problems raised in the background.

[0008] To achieve the above purpose, the present application provides a negative pressure adaptive adjustment system for ICU ward, which comprises:

[0009] A regional pressure monitoring module is configured to acquire real-time pressure values of the ICU ward region, the buffer room region and the corridor region by real-time acquisition of micro air pressure sensor data deployed in the regions.

[0010] A pressure gradient analysis module is configured to calculate real-time pressure difference values between adjacent regions based on the real-time pressure values of the ICU ward region, the buffer room region and the corridor region acquired by the regional pressure monitoring module, and to determine and analyze the pressure gradient state of the ICU ward region to generate a pressure gradient abnormal signal.

[0011] An abnormal fluctuation determination module is configured to generate an abnormal level signal based on the pressure gradient abnormal signal.

[0012] A negative pressure demand generation module is configured to receive the abnormal level signal and generate corresponding negative pressure maintenance instructions or negative pressure enhancement instructions according to the abnormal level signal.

[0013] A fan parameter calculation module is configured to receive the negative pressure maintenance instructions or negative pressure enhancement instructions, and to calculate target fan speed values and target air valve opening degree values in combination with the real-time pressure values of the ICU ward region acquired by the regional pressure monitoring module.

[0014] An execution control module is configured to control the fan speed adjustment mechanism and the air valve opening degree adjustment mechanism of the ICU ward exhaust system according to the target fan speed values and the target air valve opening degree values.

[0015] Preferably, the system further comprises:

[0016] A feedback calibration module is configured to acquire updated real-time pressure values of the ICU ward region from the regional pressure monitoring module after the execution control module completes the control operation, to calculate a pressure deviation value between the updated pressure values and a preset pressure threshold, and to generate a calibration compensation instruction.

[0017] A parameter correction module is configured to receive the calibration compensation instruction generated by the feedback calibration module, to adjust target fan speed correction coefficients and target air valve opening degree correction coefficients in the fan parameter calculation module in combination with the personnel entry and exit frequency parameters output in real time by the dynamic disturbance identification module.

[0018] The linkage response module is configured to trigger the dynamic interference identification module to monitor the start-stop state signal of the equipment in the adjacent ICU ward area in real time when the abnormal level signal output by the abnormal fluctuation determination module reaches the preset highest level, and input the signal into the fan parameter calculation module for cross-area collaborative parameter calculation.

[0019] Preferably, the abnormal level signal is generated based on the pressure gradient abnormal signal, including:

[0020] The personnel access frequency parameter and the equipment start-stop power parameter are extracted from the real-time personnel access state signal and the medical equipment start-stop state signal in the ICU ward area.

[0021] The pressure gradient abnormal signal generated by the pressure gradient analysis module is received, and an analysis instruction is triggered according to the signal; at the same time, the personnel access frequency parameter and the equipment start-stop power parameter output by the dynamic interference identification module are received, and the real-time pressure value of the ICU ward area obtained by the area pressure monitoring module is combined to calculate the pressure fluctuation intensity value; a pressure fluctuation intensity threshold value is set, and the abnormal level signal is output by comparing the pressure fluctuation intensity value with the pressure fluctuation intensity threshold value.

[0022] Preferably, the pressure gradient analysis module determines and analyzes the pressure gradient state of the ICU ward area, specifically including:

[0023] The real-time pressure value of the ICU ward area, the real-time pressure value of the buffer room area, and the real-time pressure value of the corridor area obtained by the area pressure monitoring module are extracted.

[0024] The first pressure difference value between the real-time pressure value of the ICU ward area and the real-time pressure value of the buffer room area is calculated.

[0025] The second pressure difference value between the real-time pressure value of the buffer room area and the real-time pressure value of the corridor area is calculated.

[0026] The first pressure difference threshold value and the second pressure difference threshold value are set, and the first pressure difference value is compared with the first pressure difference threshold value, and the second pressure difference value is compared with the second pressure difference threshold value at the same time.

[0027] When the first pressure difference value is less than the first pressure difference threshold value or the second pressure difference value is less than the second pressure difference threshold value, a pressure gradient abnormal signal is generated.

[0028] Preferably, the abnormal fluctuation determination module calculates the pressure fluctuation intensity value, specifically including:

[0029] The personnel access frequency parameter and the equipment start-stop power parameter output by the dynamic interference identification module are extracted.

[0030] The personnel access frequency parameter is converted into an access disturbance coefficient.

[0031] convert the device start-stop power parameter into a device disturbance coefficient;

[0032] extract the real-time pressure value of the ICU ward area obtained by the area pressure monitoring module, calculate the standard deviation of the pressure value in the current monitoring period to obtain a baseline fluctuation value;

[0033] According to the weighted calculation of the in-out disturbance coefficient, the device disturbance coefficient and the baseline fluctuation value, the pressure fluctuation intensity value is output.

[0034] Preferably, the negative pressure demand generation module generates a control instruction according to the abnormality level signal, specifically including:

[0035] set a first abnormality level threshold and a second abnormality level threshold;

[0036] When the abnormality level signal output by the abnormal fluctuation determination module is lower than the first abnormality level threshold, a negative pressure maintenance instruction is generated;

[0037] When the abnormality level signal output by the abnormal fluctuation determination module is higher than the first abnormality level threshold but lower than the second abnormality level threshold, a first-level negative pressure enhancement instruction is generated;

[0038] When the abnormality level signal output by the abnormal fluctuation determination module is higher than the second abnormality level threshold, a second-level negative pressure enhancement instruction is generated.

[0039] Preferably, when the fan parameter calculation module performs calculation, specifically including:

[0040] When receiving the negative pressure maintenance instruction, the real-time pressure value of the ICU ward area obtained by the area pressure monitoring module is extracted, the current deviation value of the real-time pressure value and the preset pressure threshold is calculated, and the target fan speed basic value and the target air valve opening basic value are obtained based on the current deviation value. Query the preset mapping table to get the target fan speed basic value and the target air valve opening basic value;

[0041] When receiving the first-level negative pressure enhancement instruction, the first enhancement coefficient is superimposed on the basis of the target fan speed basic value and the target air valve opening basic value;

[0042] When receiving the second-level negative pressure enhancement instruction, the second enhancement coefficient is superimposed on the basis of the target fan speed basic value and the target air valve opening basic value.

[0043] Preferably, the parameter correction module adjusts the target fan speed correction coefficient and the target air valve opening correction coefficient, specifically including:

[0044] Receive the pressure deviation value output by the feedback calibration module;

[0045] When the pressure deviation value exists in the preset direction for more than a set time, a positive correction coefficient or a negative correction coefficient is generated.

[0046] The positive or negative correction coefficient is superimposed on the target fan speed correction coefficient and the target valve opening correction coefficient used by the fan parameter calculation module.

[0047] Preferably, when the linkage response module performs cross-regional collaborative parameter calculation, it specifically includes:

[0048] Obtain the device start-stop state signal of the adjacent ICU ward area;

[0049] When a high-power device start signal is identified in the adjacent ICU ward area, generate a regional interference compensation amount;

[0050] Convert the regional interference compensation amount into an additional speed compensation value and an additional opening compensation value used by the fan parameter calculation module;

[0051] The linkage response module generates a regional interference compensation amount, specifically including:

[0052] Extract the rated power parameter of the high-power device in the adjacent ICU ward area;

[0053] Query the device interference intensity mapping table according to the rated power parameter to obtain a basic compensation amount;

[0054] According to the spatial distance parameter between the current ICU ward area and the adjacent ICU ward area, perform distance attenuation calculation on the basic compensation amount to output the regional interference compensation amount.

[0055] Preferably, the feedback calibration module generates a calibration compensation instruction, specifically including:

[0056] Within a set time window after the execution control module completes the control operation, continuously obtain the real-time pressure value of the ICU ward area updated by the regional pressure monitoring module;

[0057] Calculate the continuous deviation value of the updated pressure value and the preset pressure threshold value;

[0058] When the absolute value of the continuous deviation value is greater than the allowed deviation threshold value, generate a calibration compensation instruction;

[0059] The feedback calibration module calculates the continuous deviation value, specifically including:

[0060] Record the sampling sequence of all updated pressure values within the set time window;

[0061] Calculate the arithmetic mean of the sampling sequence to obtain the average updated pressure value;

[0062] Calculate the absolute value of the difference between the average updated pressure value and the preset pressure threshold value as the continuous deviation value.

[0063] Compared with the prior art, the present application has the following advantages:

[0064] The area pressure monitoring module of the system can simultaneously obtain real-time pressure values of the ICU ward area, the buffer room area and the corridor area, breaking the limitation of the traditional system that only monitors the pressure of a single area in the ward. Through synchronous monitoring of the pressure of the three areas, the pressure distribution of the entire ICU related area can be comprehensively mastered, pressure gradient cognitive bias caused by single area monitoring can be avoided, and comprehensive and accurate basic data for subsequent pressure gradient analysis and negative pressure adjustment can be provided, so that the entire negative pressure adjustment process is more in line with the actual environmental requirements.

[0065] The pressure gradient analysis module calculates the real-time pressure difference between adjacent areas according to the real-time pressure values of the three areas, and analyzes the pressure gradient state, so that abnormal conditions of the pressure gradient can be found in time. The traditional system often cannot detect pressure problems until harmful microorganisms may have begun to spread due to the lack of gradient analysis capability, while the system can generate an abnormal signal as soon as the pressure gradient is abnormal, which saves valuable time for subsequent adjustment and effectively reduces the possibility of harmful microorganism spread.

[0066] The abnormal fluctuation determination module generates an abnormal level signal based on the pressure gradient abnormal signal, so that the system can take different adjustment strategies according to the severity of the pressure abnormality. When the abnormality of the pressure gradient is relatively light, the system can generate a mild adjustment instruction to avoid excessive adjustment leading to frequent pressure fluctuations; when the abnormality is relatively severe, a higher intensity adjustment instruction is generated to ensure that the pressure is quickly restored to stability. This differentiated adjustment method not only ensures the effectiveness of the adjustment, but also improves the stability of the adjustment process, avoiding the problem of poor adjustment effect or resource waste caused by the traditional system using the same adjustment intensity regardless of the severity of the abnormality.

[0067] The negative pressure demand generation module generates a corresponding negative pressure maintenance instruction or negative pressure enhancement instruction according to the abnormal level signal, achieving precise matching between the adjustment instruction and the abnormal condition. When the pressure gradient is basically normal and only needs to maintain the current negative pressure state, a negative pressure maintenance instruction is generated to reduce unnecessary parameter adjustment and reduce device energy consumption; when the pressure gradient is abnormal and needs to enhance the negative pressure, a negative pressure enhancement instruction is generated to ensure that the direction and intensity of the negative pressure adjustment meet the actual requirements, further improving the pertinence and rationality of the system adjustment.

[0068] The fan parameter calculation module combines the real-time pressure value of the ICU ward area obtained by the area pressure monitoring module to calculate the target fan speed value and the target air valve opening value, so that the calculated parameters can accurately adapt to the current ward pressure condition. The traditional system uses fixed parameters, which cannot adjust the fan and air valve parameters according to the actual pressure change, while the system can ensure that the fan speed and air valve opening are always in the optimal state through the combination of real-time pressure data and adjustment instructions, which not only ensures the negative pressure adjustment effect, but also avoids the increase of energy consumption and equipment wear caused by long-term non-optimal operation of the equipment.

[0069] The execution control module controls the fan speed adjustment mechanism and the air valve opening adjustment mechanism of the exhaust system according to the target parameters, which realizes the rapid landing of the adjustment instruction. This module can respond to the calculated target parameters in time, quickly adjust the state of the fan and the air valve, effectively shorten the response time of pressure regulation, avoid the problem of long-term unstable pressure caused by the lag of traditional system adjustment, and ensure the continuous stability of the negative pressure environment of the ICU ward, creating a safer and more reliable diagnosis and treatment environment for medical staff and patients. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 The timing diagram of the negative pressure self-adaptive adjustment system of the ICU ward described in the present application;

[0071] Figure 2 The flowchart of feedback calibration and parameter correction;

[0072] Figure 3 The flowchart of abnormal level signal generation;

[0073] Figure 4 The flowchart of pressure fluctuation intensity value calculation;

[0074] Figure 5 The flowchart of cross-area collaborative parameter calculation. DETAILED DESCRIPTION

[0075] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0076] Please refer to Figure 1 The present application provides a negative pressure self-adaptive adjustment system for an ICU ward, which comprises an area pressure monitoring module, a pressure gradient analysis module, an abnormal fluctuation determination module, a negative pressure demand generation module, a fan parameter calculation module and an execution control module.

[0077] The regional pressure monitoring module collects air pressure data in real time by deploying micro air pressure sensors in the ICU ward area, buffer room area, and corridor area, and processes to obtain real-time pressure values of each area. The pressure gradient analysis module receives these real-time pressure values, calculates the real-time pressure difference between adjacent areas, including the first pressure difference between the ICU ward area and the buffer room area and the second pressure difference between the buffer room area and the corridor area, and determines the pressure gradient state by comparing these difference values with the preset pressure difference threshold. When any difference value is lower than the threshold, a pressure gradient abnormal signal is generated. The abnormal fluctuation determination module outputs an abnormal level signal based on the pressure gradient abnormal signal, combined with the dynamically identified personnel in and out state and medical equipment start and stop state. The negative pressure demand generation module generates a negative pressure maintenance instruction or a negative pressure enhancement instruction according to the abnormal level signal. The fan parameter calculation module receives the instruction and the real-time pressure value of the ICU ward area, calculates the target fan speed value and the target air valve opening value. The execution control module controls the fan speed adjustment mechanism and the air valve opening adjustment mechanism of the exhaust system according to the calculation result, realizing the adaptive adjustment of negative pressure.

[0078] Embodiment 1: refer to Figure 3 , relates to the determination and analysis of the pressure gradient state of the ICU ward by the system and the generation process of the abnormal level signal. The system realizes the fine management of the ward environment pressure through a series of continuous monitoring, analysis and decision steps. The regional pressure monitoring module is the basis of data collection, and high-precision micro air pressure sensors are deployed in the ICU ward area, buffer room area and corridor area. These sensors continuously measure the air pressure value of the area at a fixed sampling frequency (for example, once per second). The measurement data is transmitted to the central processing unit through wired or wireless means. The central processing unit filters and averages the original sensor data to eliminate transient noise interference, thereby obtaining the real-time pressure value of each area. These real-time pressure values are formatted into standard data packets, containing time stamp, area identification and pressure value, and continuously output to other modules of the system for use.

[0079] The pressure gradient analysis module receives real-time pressure data packets from the area pressure monitoring module. The module first parses the data packets to extract the real-time pressure values of the three key areas: the ICU ward area, the buffer area, and the corridor area. Then, it performs difference calculations: subtracting the real-time pressure value of the buffer area from the real-time pressure value of the ICU ward area to obtain the first pressure difference value; subtracting the real-time pressure value of the corridor area from the real-time pressure value of the buffer area to obtain the second pressure difference value. The system has pre-set first pressure difference threshold and second pressure difference threshold, which are set according to the medical facility infection control standards and international negative pressure ward standards. The module compares the calculated first pressure difference value with the first pressure difference threshold, and at the same time compares the second pressure difference value with the second pressure difference threshold. The comparison logic is: if the first pressure difference value is less than the first pressure difference threshold, or the second pressure difference value is less than the second pressure difference threshold, it is judged that the pressure gradient is insufficient, and there is a risk of air reverse flow, at which time the module will generate a pressure gradient abnormal signal. The signal is a digital flag containing the time of abnormal occurrence, the type of abnormality (first gradient abnormality or second gradient abnormality), and the severity of the abnormality.

[0080] The work of the abnormal fluctuation determination module is triggered by the arrival of the pressure gradient abnormal signal. In addition to receiving the pressure gradient abnormal signal, the module also receives two parameters from the dynamic interference identification module in parallel: the personnel access frequency parameter and the device start-stop power parameter. The personnel access frequency parameter is the access frequency value per unit time obtained by counting the number of door opening events collected by the infrared sensor or door magnetic switch installed at the entrance of the ICU ward. The device start-stop power parameter is the device running power change value converted from the power consumption or running state signal of large medical equipment (such as ventilators, dialysis machines) in the ward.

[0081] The module inputs the personnel access frequency parameter into a pre-defined lookup table, which maps different frequency ranges to corresponding access disturbance coefficients. For example, lower access frequency corresponds to a smaller coefficient, while frequent access activity corresponds to a higher coefficient, indicating stronger interference on pressure stability. Similarly, the device start-stop power parameter is converted to a device disturbance coefficient through another lookup table, and the start or stop of high-power devices will produce a larger coefficient. At the same time, the module obtains the real-time pressure value sequence of the ICU ward area from the area pressure monitoring module. It selects all pressure sampling values in the latest complete monitoring period (e.g. 60 seconds) to calculate the standard deviation of these values. This standard deviation is called the baseline fluctuation value, which reflects the natural dispersion degree of pressure values in this time period, i.e. the background fluctuation level without specific interference.

[0082] The module performs a weighted calculation, which integrates the in-out disturbance coefficient, the equipment disturbance coefficient, and the reference fluctuation value according to a preset weight ratio, and finally outputs a quantitative index: the pressure fluctuation intensity value. This value comprehensively reflects the overall intensity of the current pressure fluctuation. The system presets a pressure fluctuation intensity threshold, which is set based on historical operation data and safety margin. By comparing the calculated pressure fluctuation intensity value with this threshold: if the fluctuation intensity value is below the threshold, a low-level abnormality level signal is output; if it is close to the threshold, a medium-level signal is output; if it significantly exceeds the threshold, a high-level signal is output. This abnormality level signal is a multi-level digital code, which provides a direct basis for subsequent modules to take control actions of what intensity.

[0083] Embodiment 2: refer to Figure 4 , which relates to the specific calculation process of the system for pressure fluctuation intensity and the mechanism for generating corresponding control instructions based on abnormality level. The system realizes accurate judgment and hierarchical response to negative pressure regulation demand by quantifying environmental interference factors and pressure fluctuation characteristics. The process of the abnormal fluctuation judgment module calculating the pressure fluctuation intensity value is a multi-source data fusion and analysis process. The module continuously receives real-time data streams from the dynamic disturbance identification module, which includes personnel in-out frequency parameters and equipment start-stop power parameters. The acquisition of personnel in-out frequency parameters relies on multiple sets of sensors installed at the entrance of the ICU ward. When personnel pass through the ward access control, infrared beam sensors record the number of passes, door magnetic sensors record the number of door leaf openings, and visual sensors assist in identifying personnel identity and flow direction. These raw event data are sent to a dedicated frequency calculation algorithm, which takes a sliding time window (e.g. five minutes) as a unit, counts the total number of passes in the window, and considers the time interval density of consecutive pass events, finally outputting a standardized personnel in-out frequency parameter value. This parameter value not only reflects the number of passes, but also embodies the concentration of passes.

[0084] The monitoring of equipment start-stop power parameters is realized through intelligent power meters installed in the power supply circuit of medical equipment or through direct communication with the equipment control system. For high-power equipment such as ventilators and hemodialysis machines, the system real-time collects the actual power consumption data of the equipment during operation, and records the state switching events. When the equipment switches from standby mode to full power operation, or from running state to shutdown, these state change events and their corresponding power change amplitudes are accurately recorded. The equipment start-stop power parameter is a weighted sum of all equipment power change amplitudes in a time window, where the weight coefficients are pre-set according to the type of equipment and its potential impact on air flow disturbance.

[0085] The personnel access frequency parameter is input into a preset mapping function that converts the frequency value into a dimensionless access disturbance coefficient. This mapping relationship is usually nonlinear, for example, low-frequency access activities have less impact, and the corresponding coefficient grows slowly; when the frequency exceeds a certain critical point, the coefficient will grow rapidly, reflecting the increasing destructive impact of frequent access on pressure stability. Similarly, the equipment start-stop power parameter is converted into an equipment disturbance coefficient by another mapping function. The sudden start-stop of high-power equipment will cause the instantaneous imbalance of the air supply and exhaust system, so when its power value is converted into a coefficient, it also has similar nonlinear characteristics, emphasizing the importance of high-power change events.

[0086] In calculating the reference fluctuation value, the module obtains all pressure sampling values of the ICU ward area in the current monitoring period from the area pressure monitoring module. It uses a standard statistical calculation method to first calculate the arithmetic mean of all pressure values in the sequence, then calculates the sum of the squared deviations of each sampling value from the mean, divides by the number of samples, and takes the square root to finally obtain the standard deviation of the pressure in the time period, i.e., the reference fluctuation value. This value purely reflects the dispersion of the pressure data itself and is an intrinsic measure of pressure stability.

[0087] The final pressure fluctuation intensity value is generated by a weighted fusion algorithm, in which the access disturbance coefficient, the equipment disturbance coefficient, and the reference fluctuation value are input into a weighted summation unit. The system assigns configurable weight coefficients to these three input quantities. These weight coefficients are determined based on a large amount of historical operation data analysis and expert experience during system debugging, aiming to balance the contribution of different types of disturbances to overall pressure instability. The result of the weighted calculation is the pressure fluctuation intensity value, which is a comprehensive quantitative indicator representing the overall pressure disturbance level currently faced by the ICU ward.

[0088] The negative pressure demand generation module generates control instructions based on the received abnormality level signal. The module has two key threshold values preset inside: the first abnormality level threshold and the second abnormality level threshold, where the second threshold is higher than the first threshold. These two thresholds divide the severity of abnormality into three intervals. The abnormality level signal is a continuous or multi-level numerical signal.

[0089] The module continuously monitors the input abnormality level signal. When the value of the signal is below the first abnormality level threshold, the module determines that the current pressure fluctuation is within an acceptable range, and the system does not need to strengthen the negative pressure, but only needs to maintain the existing state to save energy and reduce equipment wear and tear. At this time, the module generates and outputs a negative pressure maintenance instruction. This instruction is a digital command that instructs subsequent modules to maintain the existing fan and damper parameters.

[0090] When the value of the abnormality level signal rises above the first abnormality level threshold but has not yet reached the second abnormality level threshold, it indicates that the pressure fluctuation has intensified, there is a risk of gradient instability, but the situation is not yet serious. The module generates a first-level negative pressure enhancement instruction accordingly. This instruction is an escalation command, instructing subsequent modules to appropriately increase the exhaust capacity to offset the increased disturbance and return the pressure gradient to the stable range. When the value of the abnormality level signal further rises and exceeds the second abnormality level threshold, it indicates that a strong disturbance event has occurred, and the pressure gradient faces a high risk of being destroyed, which may endanger the isolation safety of the ward. The module immediately generates and outputs a second-level negative pressure enhancement instruction. This is the highest level of response command, requiring subsequent modules to maximize the exhaust capacity to quickly and forcefully restore and maintain the required negative pressure environment.

[0091] The entire implementation process embodies the technical path from multi-dimensional sensor data acquisition, to parameter conversion and fusion calculation, to logical judgment and hierarchical instruction generation based on explicit thresholds. The calculation of pressure fluctuation intensity value comprehensively considers human factors, equipment factors, and the change characteristics of pressure itself, making the evaluation result more comprehensive and objective. The generation mechanism of the three-level instruction realizes the precise matching of system response and abnormality severity, avoiding insufficient adjustment or over-response, and embodies the core idea of adaptive control.

[0092] Embodiment 3: relates to the specific process of the fan parameter calculation module calculating the target fan speed value and the target air valve opening value according to the received different instruction types. The core function of this module is to convert the abstract control instructions generated by the upstream module into specific and quantitative parameter values to drive the actuator. Its calculation logic has the characteristics of conditional branching and superimposed enhancement. The fan parameter calculation module continuously listens to the instruction output from the negative pressure demand generation module. These instructions are divided into three types: negative pressure maintenance instruction, first-level negative pressure enhancement instruction, and second-level negative pressure enhancement instruction. The module internally presets a mapping relationship table between the pressure deviation value and the fan air valve basic parameters. This mapping table is the core result of the system design and debugging phase, and it is constructed based on fluid mechanics principles, fan characteristic curves, and a large amount of field test data. Each corresponding relationship in the mapping table aims to achieve: for a given real-time pressure and target pressure deviation value, it can query a set of optimal fan speed and air valve opening combination that can theoretically return the pressure to the target value.

[0093] When the module receives a negative pressure maintenance instruction, its calculation process starts. The module first accesses the data interface of the regional pressure monitoring module to obtain the latest ICU ward real-time pressure value, denoted as At the same time, the module reads the system preset pressure threshold from the internal memory, which is the target negative pressure value expected to be maintained, denoted as Subsequently, the module calculates the current deviation value :

[0094]

[0095] wherein: represents the latest real-time pressure value of the ICU ward area acquired from the area pressure monitoring module, represents the target negative pressure threshold value preset by the system and expected to be maintained, represents the algebraic difference value between the real-time pressure value and the target pressure threshold value, whose sign and magnitude directly reflect the deviation direction and degree of the current pressure.

[0096] After calculation, the module queries the preset mapping table with it as the index key. The mapping table is essentially an optimized lookup table, whose row index is the discretized value interval, and the column output is the corresponding target fan speed base value and target air valve opening base value . For example, when is a small negative value (indicating that the current negative pressure is slightly higher than the target, i.e., the absolute value of the pressure is smaller), the queried and will be reduced accordingly to reduce the exhaust intensity; conversely, when is a positive value (indicating that the current negative pressure is insufficient or even positive), the queried and will be significantly increased to improve the exhaust capacity and quickly restore the negative pressure. This query process ensures that the system response is closely related to the current actual pressure state.

[0097] When the module receives a first-level negative pressure enhancement instruction, it indicates that there is a disturbance beyond the normal range upstream, and a stronger adjustment action than the basic response is needed. The module will first perform the same steps as processing the negative pressure maintenance instruction: acquiring , reading , calculating , and obtaining and through the mapping table query. After that, instead of directly outputting these base values, the module performs enhancement processing. The module internally stores a first enhancement coefficient ( ). This coefficient is a multiplier factor greater than 1, and its specific value is determined through system simulation and debugging, aiming to provide a moderately enhanced adjustment intensity. The module multiplies the base values by the enhancement coefficient to obtain the final enhanced parameters: target fan speed value , target air valve opening value This multiplication superposition means that on the basis of the basic adjustment amount, the fan speed and the damper opening are increased in proportion, so as to output stronger exhaust air volume to cope with the enhanced disturbance.

[0098] When the module receives the highest level of secondary negative pressure enhancement instruction, it indicates that the system is facing serious disturbance, and the pressure gradient is at risk of collapse, and the greatest intervention is needed. Its calculation process is similar to that of handling the first level instruction, but a larger second enhancement coefficient is used in the enhancement link ). The module performs calculation: target fan speed value , target damper opening value . The setting of the second enhancement coefficient provides the maximum degree of adjustment capability that the system can exert, aiming to suppress extreme disturbance in the fastest and strongest way and to rebuild the effective negative pressure gradient.

[0099] Throughout the calculation process, the module also contains necessary logic checks, such as checking whether the final parameter values calculated exceed the physical working range of the fan and damper actuator. If it exceeds, the parameter will be limited to the maximum or minimum value allowed, preventing the issuance of instructions that are not executable or may damage the equipment. Finally, the target fan speed value and the target damper opening value calculated are packaged into data packets and output to the execution control module.

[0100] Example 4: refer to Figure 2 ​, involves the feedback calibration mechanism of the system after the initial control is completed, the dynamic correction of parameters, and the cross-regional collaborative response function in high-risk situations. This implementation improves the accuracy and robustness of system regulation through closed-loop feedback and collaborative computing. The feedback calibration module enters an active state after the system performs control operations. Instead of making a judgment immediately, the module waits for a preset time window (e.g., 30 seconds) for the effects of the exhaust system's adjustment actions to fully manifest in the pressure environment of the ward. Within this time window, the module continuously acquires updated real-time pressure values from the regional pressure monitoring module at a certain sampling interval (e.g., once every second), forming a sequence of pressure values. The module stores the preset pressure threshold that the system needs to maintain. The core task of the module is to evaluate the effectiveness of the adjustment action, i.e., to determine whether the pressure has stabilized and returned to the target range after control. Its calculation logic is not based on a single instantaneous pressure value, but on statistical results to avoid false judgments caused by accidental fluctuations. The module calculates the arithmetic mean of the collected pressure value sequence to obtain the average updated pressure value. Then, the absolute value of the difference between the average value and the preset pressure threshold is calculated, which is defined as the continuous deviation value, quantifying the stable gap between the current pressure and the target pressure. The module has an allowed deviation threshold set internally, which is a small fault tolerance range. The feedback calibration module compares the calculated continuous deviation value with the allowed deviation threshold: if the absolute value of the continuous deviation value is greater than the allowed deviation threshold, it means that the current pressure is still continuously deviating from the target value, and the control effect has not fully met the expectations, so the module generates a calibration compensation instruction. This instruction is a digital signal containing deviation direction and magnitude information, which is sent to the parameter correction module.

[0101] The parameter correction module receives the calibration compensation instruction from the feedback calibration module, which not only contains a Boolean value (indicating whether calibration is needed), but also contains the specific pressure deviation value and its direction (positive deviation indicates negative pressure deficiency, negative deviation indicates excessive negative pressure). The correction logic of the module is based on the persistent deviation trend. The module has a timer or state machine internally to determine whether a certain deviation state has persisted for more than a set duration (e.g., two consecutive monitoring periods). If the pressure deviation value is continuously positive and exceeds the set duration, the module determines that there is a persistent negative pressure deficiency in the system, and the exhaust intensity needs to be increased, so a positive correction coefficient is generated. Conversely, if it is continuously negative, a negative correction coefficient is generated. These correction coefficients are small incremental or decremental values, and their specific values are determined based on historical data and learning algorithms, aiming to make fine and progressive adjustments to avoid system oscillation caused by excessive correction, as shown in Table 1.

[0102] Table 1: Mapping relationship between pressure deviation persistence state and correction coefficient.

[0103]

[0104] The parameter correction module does not operate in isolation. It also receives the personnel access frequency parameter output in real time from the dynamic disturbance identification module. This parameter reflects the level of personnel activity in the ward and is an important feedforward disturbance signal. The module uses the received personnel access frequency parameter as a modulation factor to fine-tune the correction coefficient based on feedback described above. For example, during a high frequency of personnel access, even if the feedback deviation is the same, a slightly larger correction coefficient can be applied to pre-compensate for the disturbance that can be caused. Finally, the correction coefficient obtained through comprehensive calculation is sent to the fan parameter calculation module. When calculating the target fan speed value and the target air valve opening value, the fan parameter calculation module uses the correction coefficient as a multiplier and adds it to its original calculation logic, thereby achieving dynamic optimization and adaptive adjustment of the parameters.

[0105] The linkage response module is an extension function of the system to deal with high-risk situations. This module continuously monitors the abnormal level signal output by the abnormal fluctuation judgment module. When the strength of this signal reaches the highest level preset by the system, the linkage response module is triggered. This means that the current ICU ward is experiencing extremely severe pressure fluctuations, which can be caused by major disturbance events in the room or adjacent areas. At this time, the module sends a trigger signal to the dynamic disturbance identification module, instructing it to expand the monitoring range and collect the device start-stop state signals in the adjacent ICU ward area in real time. These signals are obtained through network communication links between the wards. The dynamic disturbance identification module packages the collected device state information (such as the start-stop of large image devices or environmental control devices) in adjacent areas and sends it back to the linkage response module. The linkage response module analyzes this signal and identifies possible device start events with high power characteristics. Once such a cross-area disturbance event is identified, the module determines that it may have an adverse effect on the pressure stability of the current ward through shared ventilation ducts or building structures. The module then generates a regional disturbance compensation amount, which is a quantitative value reflecting the estimated disturbance intensity. This compensation amount is transmitted to the fan parameter calculation module simultaneously. During its calculation process, the fan parameter calculation module converts the regional disturbance compensation amount into an additional speed compensation value and an additional opening compensation value, which are directly added to the target fan speed value and the target air valve opening value calculated finally. This enables the exhaust system of the current ward to actively and proactively resist potential disturbances from adjacent areas, achieving preliminary coordination between the exhaust systems of different ward units and improving the overall stability and stability of pressure management in the entire ICU ward area.

[0106] Example 5: see Figure 5, the specific operation process of the system in cross-regional collaborative calculation and feedback calibration is described, and the focus is on how the linkage response module identifies and compensates for the interference of adjacent areas, and how the feedback calibration module ensures control accuracy through continuous monitoring.

[0107] The execution of the linkage response module depends on its close data interaction with other modules in the system. The module continuously monitors the abnormal level signal stream from the abnormal fluctuation judgment module. When the value of this signal continues to rise and finally reaches the preset highest level threshold, the linkage response module determines that the current ward is at risk of extreme pressure instability. At this time, the module automatically activates its cross-regional monitoring function. It sends a high-priority instruction to the dynamic interference identification module, requiring it to immediately expand the data collection range and temporarily extend the monitoring focus from the current ward to the adjacent ICU ward area. The dynamic interference identification module responds to this instruction by requesting or subscribing to real-time status information of its medical devices from the monitoring system of the adjacent ward through the pre-deployed ward data communication link. These information usually include device identifiers, running status (such as standby, start, run, shutdown), current power level or load rate, etc. The system of the adjacent ward transmits these device start-stop state signals back in real time.

[0108] After receiving these data streams, the linkage response module does not simply forward them, but performs an analysis and screening process. The module stores a list of known high-power medical devices and their characteristic parameters, such as MRI cooling units, large groups of breathing machines, or high-frequency ventilation equipment. The module compares the incoming device status signals with this list and filters out those that belong to the high-power category and whose status has just changed to start or high-speed operation. After identifying such events, the module starts the generation logic of the regional interference compensation amount. The generation process is not a simple mapping, but a multi-factor comprehensive estimation. The module first extracts the rated power parameter of the device from the device signal, which is a basic physical quantity representing its energy consumption and potential air flow disturbance intensity. Based on this rated power value, the module queries an internally pre-stored device interference intensity mapping table. This mapping table is constructed during the system integration phase by analyzing the actual impact of different types of devices on the ward pressure environment when they start and stop. It maps the power value to an initial basic compensation amount.

[0109] The module introduces a spatial factor for correction, which reads the spatial distance parameter between the current ward and the adjacent ward that sends the interference signal from the system configuration database. The distance is not simply the straight-line distance, but the effective conduction path length estimated according to the ward layout and the ventilation duct path. The module uses a decay calculation model to handle the basic compensation amount, which considers that the interference intensity decreases with the increase of the effective distance. Therefore, for high-power equipment interference from the adjacent ward far away, the calculated regional interference compensation amount will be correspondingly reduced; while for the same kind of interference from the adjacent ward next to it, the compensation amount will be greater. The final generated regional interference compensation amount is a quantitative value that integrates the intensity of the interference source and the spatial decay effect. This compensation amount is transmitted to the fan parameter calculation module in real time. The algorithm embedded in the fan parameter calculation module will convert this compensation amount into specific additional speed compensation value and additional opening compensation value, which will be directly added to the basic parameters calculated according to the state of the current ward, so that the exhaust system of the current ward can prospectively resist the pressure disturbance from the outside, and realize a certain degree of regional collaborative control.

[0110] The work of the feedback calibration module constitutes another key link of the system control closed loop. The activity cycle of the module begins after the execution control module completes the adjustment operation of the fan and the air valve. Instead of making a single sampling judgment immediately, the module enters a monitoring time window of a preset length. Within this time window, the module continuously obtains the latest ICU ward regional real-time pressure value from the regional pressure monitoring module at a fixed sampling frequency, and caches these sampling values in a data sequence in chronological order. This is done to avoid making a false judgment based on instantaneous fluctuations, so as to obtain the stable trend of the pressure state in a period of time.

[0111] After the time window ends, the module performs arithmetic average calculation on all the cached pressure sampling values to obtain the average updated pressure value in this time period. This average value effectively filters short-term and random pressure pulsations, and better represents the steady-state pressure level after the adjustment action is implemented. The module then calculates the absolute value of the difference between this average updated pressure value and the system preset pressure threshold value, which is defined as the sustained deviation value, which objectively reflects the size of the sustained gap between the current pressure and the ideal target.

[0112] The module is internally configured with an allowable deviation threshold, which is a small tolerance band determined according to the clinical environment control requirements and technical feasibility. The feedback calibration module compares the calculated sustained deviation value with the allowable deviation threshold. If the absolute value of the sustained deviation value is greater than the allowable deviation threshold, it indicates that although the control operation has been performed, the pressure has not been steadily maintained within the desired range, and there is a steady-state error in the control process. At this time, the module generates a calibration compensation instruction. The key information contained in the instruction includes the existence of the deviation, the direction of the deviation (whether it is a positive deviation or a negative deviation), and the amplitude of the deviation. The instruction is sent to the parameter correction module, triggering its fine tuning of the control parameters, thereby starting a new round of fine adjustment cycle, gradually reducing until the elimination of this persistent control deviation. The whole process embodies the complete closed-loop control idea from execution to monitoring to calibration.

[0113] It should be noted that the relational terms herein such as first and second and the like are used solely to distinguish one entity or action from another, without necessarily requiring or implying any such actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0114] Although embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, alternatives, and variations can be made in the embodiments without departing from the spirit and scope of the present application as defined by the appended claims and their equivalents.

Claims

1. A negative pressure adaptive adjustment system for an ICU ward, characterized in that, include: The regional pressure monitoring module is used to acquire real-time pressure data from miniature pressure sensors deployed in the ICU ward area, buffer room area, and corridor area, and obtain the real-time pressure value of each area. The pressure gradient analysis module is used to calculate the real-time pressure difference between adjacent areas based on the real-time pressure values ​​of the ICU ward area, buffer room area and corridor area obtained by the regional pressure monitoring module, thereby determining and analyzing the pressure gradient status of the ICU ward area and generating pressure gradient abnormality signals. The abnormal fluctuation determination module generates an abnormality level signal based on the pressure gradient abnormality signal; The negative pressure demand generation module is used to receive the abnormality level signal and generate a corresponding negative pressure maintenance command or negative pressure enhancement command based on the abnormality level signal. The fan parameter calculation module is used to receive the negative pressure maintenance command or negative pressure enhancement command, and calculate the target fan speed value and the target air valve opening value by combining the real-time pressure value of the ICU ward area obtained by the area pressure monitoring module. The execution control module is used to control the fan speed adjustment mechanism and the damper opening adjustment mechanism of the ICU ward exhaust system according to the target fan speed value and the target damper opening value. The feedback calibration module is used to obtain the real-time pressure value of the ICU ward area updated by the area pressure monitoring module after the execution control module completes the control operation, calculate the pressure deviation value between the updated pressure value and the preset pressure threshold, and generate a calibration compensation instruction. The parameter correction module is used to receive the calibration compensation command generated by the feedback calibration module, and adjust the target fan speed correction coefficient and the target air valve opening correction coefficient in the fan parameter calculation module in combination with the personnel entry and exit frequency parameters output in real time by the dynamic interference identification module. The linkage response module is used to trigger the dynamic interference identification module to monitor the equipment start-up and shutdown status signals of adjacent ICU ward areas in real time when the abnormal level signal output by the abnormal fluctuation judgment module reaches the preset highest level, and synchronously input the signal into the fan parameter calculation module for cross-regional collaborative parameter calculation. The generation of anomaly level signals based on the pressure gradient anomaly signal includes: Real-time identification of personnel entry and exit status signals and medical equipment start and stop status signals in the ICU ward area, and extraction of personnel entry and exit frequency parameters and equipment start and stop power parameters; The system receives the pressure gradient anomaly signal generated by the pressure gradient analysis module and triggers an analysis command based on the signal; it also receives the personnel entry and exit frequency parameters and equipment start-up and shutdown power parameters output by the dynamic interference identification module, and calculates the pressure fluctuation intensity value by combining it with the real-time pressure value of the ICU ward area obtained by the regional pressure monitoring module; it sets the pressure fluctuation intensity threshold, and outputs an anomaly level signal by comparing the pressure fluctuation intensity value with the pressure fluctuation intensity threshold.

2. The negative pressure adaptive adjustment system for an ICU ward according to claim 1, characterized in that, The pressure gradient analysis module determines and analyzes the pressure gradient status in the ICU ward area, specifically including: Extract the real-time pressure values ​​of the ICU ward area, the buffer room area, and the corridor area obtained by the area pressure monitoring module. Calculate the first pressure difference between the real-time pressure value of the ICU ward area and the real-time pressure value of the buffer room area; Calculate the second pressure difference between the real-time pressure value of the buffer zone area and the real-time pressure value of the corridor area; Set a first pressure difference threshold and a second pressure difference threshold, compare the first pressure difference value with the first pressure difference threshold, and at the same time compare the second pressure difference value with the second pressure difference threshold. A pressure gradient anomaly signal is generated when the first pressure difference is less than the first pressure difference threshold or the second pressure difference is less than the second pressure difference threshold.

3. The negative pressure adaptive adjustment system for an ICU ward according to claim 1, characterized in that, The abnormal fluctuation determination module calculates the pressure fluctuation intensity value, specifically including: Extract the personnel entry / exit frequency parameters and equipment start / stop power parameters output by the dynamic interference identification module; Convert personnel entry and exit frequency parameters into entry and exit disturbance coefficients; Convert the equipment start-up and shutdown power parameters into equipment disturbance coefficients; Extract the real-time pressure value of the ICU ward area obtained by the regional pressure monitoring module, calculate the standard deviation of the pressure value within the current monitoring period, and obtain the baseline fluctuation value; The pressure fluctuation intensity value is calculated by weighting the inlet / outlet disturbance coefficient, the equipment disturbance coefficient, and the reference fluctuation value.

4. The negative pressure adaptive adjustment system for an ICU ward according to claim 1, characterized in that, The negative pressure demand generation module generates control commands based on the abnormality level signal, specifically including: Set a first anomaly level threshold and a second anomaly level threshold; When the abnormal level signal output by the abnormal fluctuation determination module is lower than the first abnormal level threshold, a negative pressure maintenance command is generated. When the abnormal level signal output by the abnormal fluctuation determination module is higher than the first abnormal level threshold but lower than the second abnormal level threshold, a first-level negative pressure enhancement command is generated. When the abnormal level signal output by the abnormal fluctuation determination module is higher than the second abnormal level threshold, a second-level negative pressure enhancement command is generated.

5. The negative pressure adaptive adjustment system for an ICU ward according to claim 4, characterized in that, When the wind turbine parameter calculation module performs calculations, it specifically includes: When a negative pressure maintenance command is received, the real-time pressure value of the ICU ward area obtained by the area pressure monitoring module is extracted, the current deviation value between the real-time pressure value and the preset pressure threshold is calculated, and the target fan speed base value and the target air valve opening base value are obtained by querying the preset mapping table based on the current deviation value. When a first-level negative pressure enhancement command is received, a first enhancement coefficient is superimposed on the base value of the target fan speed and the base value of the target damper opening. When a secondary negative pressure enhancement command is received, a second enhancement coefficient is superimposed on the base values ​​of the target fan speed and the target damper opening.

6. The negative pressure adaptive adjustment system for an ICU ward according to claim 1, characterized in that, The parameter correction module adjusts the target fan speed correction coefficient and the target valve opening correction coefficient, specifically including: Receive the pressure deviation value output by the feedback calibration module; When the pressure deviation value persists in the preset direction for more than a set time, a positive correction coefficient or a negative correction coefficient is generated; The positive or negative correction coefficient is superimposed on the target fan speed correction coefficient and the target damper opening correction coefficient used by the fan parameter calculation module.

7. The negative pressure adaptive adjustment system for an ICU ward according to claim 1, characterized in that, When the linkage response module performs cross-regional collaborative parameter calculation, it specifically includes: Obtain the start / stop status signals of the equipment in the adjacent ICU ward area; When a high-power device start-up signal is detected in an adjacent ICU ward area, an area interference compensation amount is generated. The regional interference compensation amount is converted into additional speed compensation value and additional opening compensation value used by the wind turbine parameter calculation module; The linkage response module generates regional interference compensation amounts, specifically including: Extract the rated power parameters of high-power devices in adjacent ICU ward areas; The basic compensation amount is obtained by consulting the equipment interference intensity mapping table based on the rated power parameters; Based on the spatial distance parameters between the current ICU ward area and the adjacent ICU ward area, the distance attenuation of the basic compensation amount is calculated, and the regional interference compensation amount is output.

8. The negative pressure adaptive adjustment system for an ICU ward according to claim 1, characterized in that, The feedback calibration module generates calibration compensation instructions, specifically including: Within a set time window after the execution control module completes the control operation, the real-time pressure value of the ICU ward area updated by the area pressure monitoring module is continuously acquired. Calculate the continuous deviation between the updated pressure value and the preset pressure threshold; When the absolute value of the persistent deviation exceeds the allowable deviation threshold, a calibration compensation command is generated. The feedback calibration module calculates the persistent deviation value, specifically including: Record the sampling sequence of all updated pressure values ​​within the set time window; Calculate the arithmetic mean of the sampled sequences to obtain the average update pressure value; Calculate the absolute value of the difference between the average update pressure value and the preset pressure threshold, and use it as the continuous deviation value.

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