Energy-saving pressure swing adsorption air conditioning intelligent oxygen supply system for plateau regions

Abstract

This invention relates to the field of air conditioning environmental control technology, specifically to an energy-saving pressure swing adsorption (PSA) air conditioning-type intelligent oxygen supply system for high-altitude regions. The system includes a data acquisition module for acquiring data; a suspected interference location analysis module, which filters suspected interference locations based on synchronous anomalies in oxygen concentration between monitoring locations and analyzes the probability of anomalies in oxygen concentration deviation; a ventilation interference analysis module, which obtains the probability of ventilation interference by observing the continuous distribution of suspected interference locations and the decreasing trend of anomaly probability, and measures the intensity of ventilation interference by combining the current distribution of ventilation interference locations with air pressure difference fluctuations; and an oxygen regulation module, which determines the weight of each location based on the probability and intensity of ventilation interference, and evaluates the overall oxygen concentration regulation. This invention improves the accuracy of oxygen supply and ensures the accuracy and reliability of indoor oxygen concentration control in high-altitude regions by analyzing the impact of anomalies and ventilation interference on multiple monitoring locations and adjusting the comprehensive monitoring results of oxygen concentration.

Description

Technical Field

[0001] This invention relates to the field of air conditioning and environmental control technology, specifically to an energy-saving pressure swing adsorption (PSA) air conditioning-type intelligent oxygen supply system for high-altitude regions. Background Technology

[0002] With economic development and tourism growth in plateau regions, the number of people entering high-altitude areas is increasing daily. At this time, the body needs to adapt to the low-oxygen environment, leading to a series of reactions, including rapid heart rate, shortness of breath, headache, nausea, and other discomfort. These symptoms may develop into acute altitude sickness, even endangering life; therefore, proper regulation of the oxygen supply system is essential.

[0003] In public spaces such as halls in high-altitude areas, oxygen concentration monitoring and control are affected by factors such as low air pressure and ventilation interference (e.g., fresh air from balconies or convection at doorways). Furthermore, the accuracy of oxygen sensors is susceptible to malfunctions and aging, which can also affect the detection results of localized oxygen concentrations at single points. This can lead to monitoring data that fails to reflect the overall oxygen concentration, resulting in significant errors in overall oxygen concentration monitoring. Consequently, the oxygen supply system may become inaccurate, leading to localized hypoxia or excessive oxygen supply and wasted energy. Summary of the Invention

[0004] To address the technical problems in the prior art, the present invention aims to provide an energy-saving pressure swing adsorption (PSA) air conditioning-type intelligent oxygen supply system for high-altitude regions. The specific technical solution adopted is as follows:

[0005] The first aspect of this application provides an energy-saving pressure swing adsorption (PSA) air conditioning-type intelligent oxygen supply system for high-altitude regions, the system comprising:

[0006] The data acquisition module is used to acquire oxygen concentration sequences at different monitoring locations indoors, as well as indoor and outdoor air pressure difference sequences.

[0007] The suspected interference location analysis module is used to filter out suspected interference locations at each time point based on the trend synchronization anomalies of the oxygen concentration sequence between monitoring locations at each time point; and to obtain the possible anomaly indicators of each suspected interference location based on the location distribution and oxygen concentration sequence deviation between each suspected interference location and other monitoring locations at each time point.

[0008] The ventilation interference analysis module is used to obtain the ventilation interference potential index and determine the ventilation interference location at the current moment for each suspected interference location based on the degree of continuous distribution of suspected interference locations in historical time series and the downward trend of abnormality probability index; and to obtain the ventilation interference intensity index at the current moment based on the proportion of ventilation interference locations at the current moment and the intensity of fluctuation in the air pressure difference sequence.

[0009] The oxygen regulation module is used to determine the characterization weight of each monitoring location based on the ventilation interference probability index and the ventilation interference intensity index; and to obtain the comprehensive oxygen concentration at the current moment through the characterization weight of the monitoring location and the oxygen concentration for regulation.

[0010] Furthermore, the method for obtaining the suspected interference location includes:

[0011] For any monitoring location at any given time, the slope of the oxygen concentration sequence at each time point is obtained as the trend at that time point.

[0012] In the preset preceding window at that moment, based on the differences in oxygen concentration and trend between the monitoring location and each other monitoring location at each moment, the trend synchronization degree between the monitoring location and each other monitoring location at that moment is obtained;

[0013] When the trend synchronization is less than the preset similarity threshold, other corresponding monitoring locations are recorded as deviation locations of the monitoring location; when the number of deviation locations is greater than the preset abnormality threshold, the monitoring location is regarded as a suspected interference location.

[0014] Furthermore, the method for obtaining the possible anomaly indicators includes:

[0015] For any suspected interference location at any given time, the ratio of the number of deviation locations of the suspected interference location to the total number of monitored locations is used as the deviation anomaly distribution index of the suspected interference location.

[0016] The distance between the suspected interference location and each deviation location is negatively correlated and mapped to serve as the position weight between the suspected interference location and each deviation location. The trend synchronization between the suspected interference location and all deviation locations is weighted and summed using the position weights, and then negatively correlated to obtain the abnormal deviation intensity index of the suspected interference location.

[0017] By combining the abnormal deviation distribution index and the abnormal deviation intensity index, the possible abnormal indicators of the suspected interference location are obtained.

[0018] Furthermore, the method for obtaining the ventilation interference potential indicators includes:

[0019] For any suspected interference location at the current moment, the time period when the suspected interference location is taken as a suspected interference location at consecutive moments in the historical time series is recorded as the abnormal fluctuation period of the suspected interference location; the time period from the start time of the first abnormal fluctuation period in the time series to the current moment is recorded as the critical period.

[0020] The duration of abnormal fluctuation periods during key periods is used as the fault trend degree of the suspected interference location; curve fitting is performed on the possible abnormal indicators during key periods, and the slope of the fitted curve is obtained; the number of negative slopes is used as the abnormal recovery trend degree of the suspected interference location.

[0021] The product of the fault trend degree of the suspected interference location after negative correlation mapping and the abnormal recovery trend degree is used as a possible indicator of ventilation interference at the suspected interference location.

[0022] Furthermore, the method for determining the location of the ventilation interference includes:

[0023] Locations suspected of being sources of ventilation interference, where the potential interference index exceeds a preset interference threshold, are designated as ventilation interference locations.

[0024] Furthermore, the method for obtaining the interference intensity index includes:

[0025] The standard deviation of the pressure difference before the current time in the pressure difference sequence is used as the pressure fluctuation index at the current time.

[0026] Both the ventilation interference location and the non-suspected interference location at the current moment are recorded as normal locations; the proportion of the ventilation interference location at the current moment to the normal location is used as the influence range index at the current moment; the product of the influence range index and the air pressure difference at the current moment is used as the air pressure flow index at the current moment.

[0027] By combining air pressure fluctuation indicators and air pressure flow indicators, the ventilation disturbance intensity index at the current moment is obtained.

[0028] Furthermore, the method for obtaining the representation weights includes:

[0029] The product of the ventilation disturbance intensity index and the ventilation disturbance potential index is negatively correlated and normalized, and used as the characterization weight for each ventilation disturbance location.

[0030] The preset maximum characterization weight is used as the characterization weight of the monitoring position for each non-suspected interference position; the preset minimum characterization weight is used as the characterization weight of the monitoring position for the non-ventilation interference position among the suspected interference positions; the preset minimum characterization weight is less than the preset maximum characterization weight.

[0031] Furthermore, the method for obtaining the overall oxygen concentration includes:

[0032] The current comprehensive oxygen concentration is obtained by weighting the current oxygen concentration data of all monitoring locations using the representation weight of each monitoring location as the weight.

[0033] Furthermore, the method for obtaining the trend synchronization degree includes:

[0034] Within a preset preceding window at that moment, calculate the difference in oxygen concentration and trend between this monitoring location and every other monitoring location at each moment;

[0035] After multiplying the differences in oxygen concentration and trend at each time point, the sum of the products at all times is negatively correlated to obtain the trend synchronization between the monitoring location and each other monitoring location at that time point.

[0036] Furthermore, the method of combining air pressure fluctuation indicators and air pressure flow indicators to obtain the ventilation disturbance intensity index at the current moment includes:

[0037] The product of the air pressure fluctuation index and the air pressure flow index is normalized to obtain the ventilation disturbance intensity index at the current moment.

[0038] Secondly, this application provides a computer device including a memory and a processor. The memory is used to store computer program code, and the processor is used to call and run the computer program code from the memory to perform the method as described in the first aspect of this application or any embodiment of the first aspect.

[0039] Thirdly, this application provides a computer program product comprising computer program code, which, when executed, performs the method as described in the first aspect of this application or any embodiment thereof.

[0040] Fourthly, this application provides a computer-readable storage medium that stores computer program code, which, when executed, performs the method as described in the first aspect of this application or any embodiment thereof.

[0041] The present invention has the following beneficial effects:

[0042] This invention screens suspected interference locations based on the trend synchronization of oxygen concentration sequences at various monitoring locations, pinpointing locations where local ventilation causes abnormal oxygen concentrations. Locations exhibiting trend anomalies through trend synchronization analysis are identified as monitoring anomalies or ventilation disturbances. The degree of oxygen concentration deviation at suspected interference locations yields potential anomaly indicators, quantifying the severity of anomalies at suspected locations. Screening interference locations reduces the impact of some monitoring locations on overall oxygen concentration assessment and provides a basis for further differentiation between interference and anomalies. By analyzing the continuous distribution and decreasing trend of suspected ventilation interference locations over historical time series, and based on the continuous recovery characteristics of ventilation interference, potential ventilation interference indicators are obtained, and ventilation interference locations are determined. This distinguishes between ventilation interference and anomalies, and the confidence level of interference locations participating in overall oxygen concentration detection is adjusted through interference degree analysis. Combining the current proportion of ventilation interference locations with the intensity of air pressure difference fluctuations, the intensity of ventilation interference is measured, quantifying the current level of ventilation interference in the environment. Based on the potential and intensity indicators of ventilation interference, the representation weights of each monitoring location are determined to avoid biased adjustments caused by low-reliability data from interfering locations. The overall oxygen concentration is calculated and adjusted by combining these weights with the oxygen concentration, ensuring that the overall concentration closely reflects the true overall indoor oxygen concentration. This invention analyzes the impact of anomalies and ventilation interference at multiple monitoring locations, adjusts the overall monitoring results of indoor oxygen concentration, improves the accuracy of oxygen supply, ensures the accuracy and reliability of indoor oxygen concentration control in high-altitude areas, and reduces energy waste. Attached Figure Description

[0043] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a structural diagram of an energy-saving pressure swing adsorption air conditioning intelligent oxygen supply system based on a plateau region, provided in one embodiment of the present invention.

[0045] Figure 2 This is a schematic diagram of a computer device structure provided in one embodiment of the present invention. Detailed Implementation

[0046] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an energy-saving pressure swing adsorption (PSA) air conditioning-type intelligent oxygen supply system for plateau regions proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0048] The following description, in conjunction with the accompanying drawings, details a specific solution for an energy-saving pressure swing adsorption (PSA) air conditioning-type intelligent oxygen supply system for plateau regions provided by this invention.

[0049] Please see Figure 1 The diagram shows a structural diagram of an energy-saving pressure swing adsorption air conditioning intelligent oxygen supply system based on a plateau region, according to an embodiment of the present invention. The system includes: a data acquisition module 101, a suspected interference location analysis module 102, a ventilation interference analysis module 103, and an oxygen regulation module 104.

[0050] The data acquisition module 101 is used to acquire oxygen concentration sequences at different monitoring locations indoors, as well as the pressure difference between indoors and outdoors.

[0051] For indoor halls in high-altitude areas, the ventilation paths are more complex and interference is more concentrated. These halls typically connect multiple different spaces and exhibit multi-directional airflow, making monitoring and regulation more difficult. Therefore, optical oxygen sensors are used at different monitoring locations in different functional areas of the indoor space to collect oxygen concentration data for a preset historical time period, resulting in an oxygen concentration sequence. Since air pressure directly affects oxygen distribution and adsorption efficiency, air pressure sensors are used to collect indoor and outdoor air pressure and obtain the pressure difference.

[0052] It is understandable that the monitored data undergoes preprocessing, which may include data standardization and time-scale normalization to facilitate unified data analysis and remove the influence of units. It should be noted that data preprocessing is a technique well-known to those skilled in the art. The preset historical time period can be set to 1 hour, and the collection frequency to once per second. Specific collection settings can be adjusted by the implementer and will not be elaborated upon or limited here.

[0053] The suspected interference location analysis module 102 is used to filter out suspected interference locations at each time point based on the trend synchronization anomalies of the oxygen concentration sequence between monitoring locations at each time point; and to obtain the possible anomaly indicators of each suspected interference location based on the location distribution and oxygen concentration sequence deviation between each suspected interference location and other monitoring locations at each time point.

[0054] When monitoring an oxygen supply system, the indoor oxygen concentration is usually reflected by combining the monitoring results from multiple monitoring locations. However, ventilation interference can cause the oxygen concentration in some areas to deviate from the true level, leading to a misjudgment of oxygen scarcity. At the same time, the aging of oxygen sensors can also cause errors in concentration monitoring. Therefore, fluctuations in monitoring data can be used to initially screen out suspected interference locations with monitoring anomalies.

[0055] Due to the localized characteristics of interference monitoring, such as the possibility of cold air seeping in near windows causing local oxygen concentration fluctuations, while the central indoor area is minimally affected by these fluctuations, the oxygen concentration data at most monitoring locations are highly synchronized. Therefore, suspected interference locations are screened out based on the degree of synchronization anomaly.

[0056] Preferably, in this embodiment of the invention, the method for obtaining the suspected interference location includes:

[0057] For any given monitoring location at any given time, the slope of the oxygen concentration sequence at each time point is obtained as the trend degree, reflecting the changing trend of oxygen concentration. Within a preset preceding window at that time point, the trend synchronization degree between that monitoring location and each other monitoring location at that time point is obtained based on the differences in oxygen concentration and trend degree between that monitoring location and each other monitoring location. When the oxygen concentration deviation between two monitoring locations in a given time period is large and the difference in their changing trends is also high, it indicates that the synchronization similarity between the two monitoring locations is low. In this embodiment of the invention, the preset preceding window is set to the size of the window one minute prior to the time point. The specific value can be adjusted by the implementer according to the specific implementation situation and is not limited here.

[0058] In this embodiment of the invention, within a preset preceding window at a given moment, the differences in oxygen concentration and trend between the monitoring location and each other monitoring location at each moment are calculated. The oxygen concentration difference is the absolute value of the difference between the oxygen concentration sequences of the monitoring location and each other monitoring location at each moment, reflecting the numerical difference in oxygen concentration. Then, the differences in oxygen concentration and trend at each moment are multiplied, and the sum of the products at all moments is negatively correlated and normalized to obtain the trend synchronization degree between the monitoring location and each other monitoring location at that moment. The larger the difference, the higher the difference in the numerical value and trend of oxygen concentration between the two monitoring locations at that moment, and the lower the synchronization similarity.

[0059] In the embodiments of the present invention, normalization and negative correlation mapping are both well-known techniques to those skilled in the art, such as using inverse proportional values ​​or negative exponential forms. The choice of normalization can be linear normalization or standard normalization, etc. The specific methods are not limited or described in detail here.

[0060] When the trend synchronization is less than a preset similarity threshold, other corresponding monitoring locations are marked as deviation locations of this monitoring location. Low trend synchronization indicates low similarity and potential deviation anomalies. When the number of deviation locations exceeds a preset anomaly threshold, the monitoring location is designated as a suspected interference location. A higher number of marked deviation locations indicates lower similarity between the oxygen concentration of this monitoring location and most other areas, suggesting potential monitoring anomalies that require attention. In this embodiment, the preset similarity threshold can be set to 0.4, and the preset anomaly threshold can be set to 30% of the total number of monitoring locations. Implementers can adjust these values ​​themselves; no restrictions are imposed here.

[0061] For the initially screened suspected interference locations, the degree of deviation segregation is adjusted by monitoring the distribution of these locations, and the degree of abnormal oxygen concentration fluctuations at each suspected interference location is assessed. Preferably, in this embodiment of the invention, the method for obtaining the possible anomaly indicators includes:

[0062] For any suspected interference location at any given time, the ratio of the number of deviation locations of the suspected interference location to the total number of monitored locations is used as the deviation anomaly distribution index of the suspected interference location. The more deviation locations there are, the higher the difference between the suspected interference location and the oxygen concentration distribution in multiple local areas, and the greater the anomaly is likely.

[0063] Then, a negative correlation mapping is performed between the suspected interference location and each deviation location, which serves as the positional weight between the suspected interference location and each deviation location. For locations with greater distances, the deviation may inherently be higher, resulting in lower confidence levels during deviation analysis. Using the positional weights as weights, a weighted sum of the trend synchronization between the suspected interference location and all deviation locations is calculated, and then a negative correlation mapping is performed to obtain the abnormal deviation intensity index for the suspected interference location. Specifically, this involves calculating the product of the trend synchronization between the suspected interference location and each deviation location and the positional weight, and then performing a negative correlation mapping on the sum of all products to obtain the abnormal deviation intensity index. The smaller the trend synchronization under overall deviation, the greater the degree of abnormal fluctuation, and therefore, the larger the abnormal deviation intensity index.

[0064] Finally, by combining the abnormal deviation distribution index and the abnormal deviation intensity index, an abnormality probability index is obtained. In this embodiment of the invention, the product of the abnormal deviation distribution index and the abnormal deviation intensity index is used as the abnormality probability index of the suspected interference location. The larger the abnormal deviation distribution index and the abnormal deviation intensity index are, the stronger the deviation between the suspected interference location and other locations, and the higher the probability of being affected by an anomaly.

[0065] The ventilation interference analysis module 103 is used to obtain the ventilation interference potential index and determine the ventilation interference location at the current moment for each suspected interference location based on the degree of continuous distribution of suspected interference locations in historical time series and the downward trend of abnormality probability index; and to obtain the ventilation interference intensity index at the current moment based on the proportion of ventilation interference locations at the current moment and the intensity of air pressure difference fluctuation.

[0066] In high-altitude environments, indoor ventilation can cause localized oxygen concentrations to deviate from the actual indoor levels. This deviation is usually temporary and has low persistence. Simultaneously, the drastic fluctuations in air pressure and temperature accelerate sensor aging. This type of malfunction can cause the collected oxygen concentration to deviate from the actual value, exhibiting a high degree of anomaly. If the anomaly in oxygen concentration at a suspected location is caused by sensor malfunction, this anomaly will typically persist and will not change with variations in environmental conditions.

[0067] Therefore, different abnormal situations should be assessed separately. Locations that are truly likely to be faulty or abnormal may not be included in the comprehensive analysis, while the attention given to ventilation locations with temporary impacts can be dynamically adjusted according to the degree of impact. By analyzing the duration and recoverability of ventilation deviations, the likelihood of suspected interference locations being ventilation disturbances can be determined.

[0068] Preferably, in this embodiment of the invention, the method for obtaining possible indicators of ventilation interference includes:

[0069] For any suspected disturbance location at the current moment, since the building structure will not change, the abnormalities in ventilation and other disturbances will have a phased impact over historical periods. Therefore, the time periods when the suspected disturbance location is located consecutively in the historical time series are recorded as the abnormal fluctuation periods of that suspected disturbance location. The period from the start time of the first abnormal fluctuation period in the time series to the current moment is recorded as the critical period. Considering the persistence of the fault after its occurrence, the analysis focuses on the period after the anomaly begins to appear.

[0070] The proportion of abnormal fluctuation periods during key time periods is used as the fault trend degree of the suspected interference location. A larger proportion of abnormal fluctuation periods, i.e., a higher fault trend degree, indicates a more significant anomaly and a higher probability of monitoring equipment failure. Curve fitting is performed on the possible anomaly indicators during key time periods, and the slope of the fitted curve is obtained. The number of negative slopes is used as the anomaly recovery trend degree of the suspected interference location. The more times the slope is negative, the more concentration recovery trends exist at that location, and the more likely it is a ventilation interference location with temporary fluctuations caused by ventilation. It should be noted that curve fitting is a technique well-known to those skilled in the art and will not be elaborated upon here.

[0071] Finally, the product of the fault trend degree of the suspected interference location after negative correlation mapping and the abnormal recovery trend degree is used as a possible indicator of ventilation interference at the suspected interference location. The smaller the fault trend degree and the larger the abnormal recovery trend degree, the higher the probability that the location is affected by ventilation interference.

[0072] Therefore, in this embodiment of the invention, the suspected interference location where the ventilation interference index is greater than the preset interference threshold is taken as the ventilation interference location, wherein the preset interference threshold is set to 0.5, and the specific value can be adjusted by the implementer and is not limited here.

[0073] Ventilation is essentially the flow of air caused by pressure differences. In high-altitude areas, air pressure is generally low, and there is a significant difference between indoor and outdoor air pressure. Intelligent oxygen supply systems need to generate high-concentration oxygen through pressure swing adsorption (PSA) technology and deliver it indoors. This process slightly alters the indoor air pressure; for example, an increase in indoor oxygen concentration can lead to slightly higher indoor air pressure than outdoors. Additionally, strong winds at high altitudes can cause fluctuations in outdoor air pressure, creating an indoor-outdoor pressure difference. This pressure difference directly determines the intensity of the driving force behind the airflow, thus determining the extent of ventilation interference and the degree of impact on local oxygen concentration.

[0074] Therefore, combining the air pressure difference and the determined location of the ventilation disturbance, the intensity index of the ventilation disturbance affected at the current moment is analyzed. In this embodiment of the invention, the method for obtaining the disturbance intensity index includes:

[0075] Using the standard deviation of the air pressure difference before the current moment in the air pressure difference sequence as the air pressure fluctuation index at the current moment, when the indoor and outdoor air pressure difference changes significantly, the air flow dynamics are strong and the ventilation speed is fast, which will quickly dilute or accumulate in local areas. At this time, the intensity of the interference of the external environment on the indoor oxygen supply environment will be greater, and the oxygen concentration data obtained will be less reliable.

[0076] Both the location of the ventilation disturbance and the location not suspected of being disturbed are recorded as normal locations at the current moment. The proportion of the location of the ventilation disturbance to the normal locations at the current moment is used as the influence range indicator. The more ventilation disturbance locations there are, the larger the area affected by ventilation. Then, the product of the influence range indicator and the air pressure difference at the current moment is used as the air pressure flow indicator. The larger the air pressure flow indicator, the larger the area affected by the current air pressure difference and the higher the disturbance intensity.

[0077] Finally, by combining the air pressure fluctuation index and the air pressure flow index, the ventilation interference intensity index at the current moment is obtained. In this embodiment of the invention, the product of the air pressure fluctuation index and the air pressure flow index is normalized to obtain the ventilation interference intensity index at the current moment. When the ventilation interference intensity index is larger, it indicates that the degree of interference is higher and the reliability of the oxygen concentration is lower.

[0078] The oxygen regulation module 104 is used to determine the characterization weight of each monitoring location based on the ventilation interference probability index and the ventilation interference intensity index; and to obtain the comprehensive oxygen concentration at the current moment through the characterization weight of the monitoring location and the oxygen concentration for regulation.

[0079] Indoor oxygen concentration monitoring points can be affected by ventilation interference, leading to discrepancies in oxygen concentration data at different locations. Even if the sensor itself is not faulty, ventilation interference can still cause localized areas to deviate from the true indoor average oxygen concentration. Therefore, analyzing and assessing the intensity of ventilation interference at monitoring locations can adjust the overall oxygen concentration assessment results, improve the confidence level of monitoring at locations without ventilation interference, and reduce the impact of results from interfering and abnormal locations.

[0080] In this embodiment of the invention, the method for obtaining the characterization weight includes:

[0081] The product of the ventilation interference intensity index and the ventilation interference probability index is negatively correlated and normalized, and used as the representation weight for each ventilation interference location. For ventilation interference locations, the higher the probability of receiving ventilation interference and the stronger the degree of interference, the lower the confidence level for participating in the comprehensive assessment.

[0082] Furthermore, a preset maximum representation weight is used as the representation weight for the monitoring position of each non-suspected interference location. Normal locations among the non-suspected interference locations are assigned the highest confidence level for comprehensive evaluation. A preset minimum representation weight is used as the representation weight for the monitoring position of the non-ventilation interference location among the suspected interference locations. Other abnormal locations are assigned the lowest confidence level for comprehensive evaluation. In this embodiment of the invention, the preset minimum representation weight is less than the preset maximum representation weight. The preset minimum representation weight is set to 0, meaning abnormal locations do not participate in the evaluation; the preset maximum representation weight is set to 1, meaning the participation confidence level of normal locations is not reduced.

[0083] In this embodiment of the invention, the current oxygen concentration data of all monitoring locations are weighted and averaged using the representation weight of each monitoring location as the weight to obtain the current comprehensive oxygen concentration. That is, the comprehensive oxygen concentration is obtained by multiplying the representation weight of each monitoring location by the oxygen concentration data and calculating the average of all products.

[0084] By using weighted averaging, the large fluctuations in oxygen concentration caused by local ventilation at individual locations can be reduced, and the impact of measurement errors or equipment failures at single monitoring points can be mitigated, thereby improving the accuracy of comprehensive oxygen concentration data for the overall oxygen concentration status of the oxygen supply environment.

[0085] After determining the overall oxygen concentration, the data is input into the PID controller. Based on the proportional, integral, and derivative terms of the PID algorithm, the controller calculates the control quantity, i.e., the output signal. According to the output signal, the PID controller sends adjustment commands to the oxygen supply system to adjust the oxygen concentration, such as increasing or decreasing the oxygen flow rate. It should be noted that the control methods used are well-known to those skilled in the art and will not be elaborated upon here.

[0086] In summary, this invention screens suspected ventilation interference locations based on the trend synchronization of oxygen concentration sequences at various monitoring locations, pinpointing locations where local ventilation causes abnormal oxygen concentrations. Locations exhibiting trend anomalies through trend synchronization analysis are identified as monitoring anomalies or ventilation disturbances. The degree of oxygen concentration deviation at suspected interference locations yields potential anomaly indicators, quantifying the severity of anomalies at suspected locations. Screening interference locations reduces the impact of some monitoring locations on overall oxygen concentration assessment and provides a basis for further differentiation between interference and anomalies. By analyzing the continuous distribution of suspected ventilation interference locations and the decreasing trend of anomaly severity over historical time series, and based on the continuous recovery characteristics of ventilation interference, potential ventilation interference indicators are obtained, and ventilation interference locations are determined. This distinguishes between ventilation interference and anomalies, and the confidence level of interference locations participating in overall oxygen concentration detection is adjusted through interference severity analysis. Finally, by combining the current proportion of ventilation interference locations with the intensity of air pressure difference fluctuations, the intensity of ventilation interference is measured, quantifying the current level of ventilation interference in the environment. Based on the potential and intensity indicators of ventilation interference, the representation weights of each monitoring location are determined to avoid biased adjustments caused by low-reliability data from interfering locations. The overall oxygen concentration is calculated and adjusted by combining these weights with the oxygen concentration, ensuring that the overall concentration closely reflects the true overall indoor oxygen concentration. This invention analyzes the impact of anomalies and ventilation interference at multiple monitoring locations, adjusts the overall monitoring results of indoor oxygen concentration, improves the accuracy of oxygen supply, ensures the accuracy and reliability of indoor oxygen concentration control in high-altitude areas, and reduces energy waste.

[0087] This application also provides a computer device; please refer to [link / reference]. Figure 2 The diagram illustrates a computer device structure according to an embodiment of the present invention. The computer device includes a memory 301, a processor 302, and a computer program 303 stored in the memory 301 and running on the processor 302. When the processor 302 executes the computer program 303, the computer device can perform the steps of any of the aforementioned energy-saving pressure swing adsorption air conditioning intelligent oxygen supply systems based on plateau regions.

[0088] This application also provides a computer program product that, when run on a computer device, enables the computer device to execute any of the steps of the aforementioned energy-saving pressure swing adsorption air conditioning intelligent oxygen supply system based on plateau regions.

[0089] This application also provides a computer-readable storage medium storing computer program code. When the computer program code is run on a computer device, the computer device can execute the steps of any of the aforementioned energy-saving pressure swing adsorption air conditioning intelligent oxygen supply systems based on plateau regions.

[0090] In the embodiments provided in this application, it should be understood that the computer device, computer program product and computer-readable storage medium provided are all used to perform the corresponding methods provided above, and therefore the beneficial effects they can achieve can be referred to the beneficial effects of the methods provided above, which will not be repeated here.

[0091] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0092] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A high-altitude region-based energy-saving pressure swing adsorption air-conditioning type intelligent oxygen supply system, characterized in that, The system comprises: a data acquisition module for acquiring oxygen concentration sequences of different monitoring positions in a room and a pressure difference sequence between the inside and outside of the room; a suspected interference position analysis module for screening suspected interference positions at each moment according to trend synchronization abnormalities of the oxygen concentration sequences between the monitoring positions at each moment, and obtaining abnormal possibility indexes of each suspected interference position according to the position distribution and oxygen concentration sequence deviation degree between each suspected interference position and other monitoring positions at each moment; a ventilation interference analysis module for obtaining ventilation interference possibility indexes and determining ventilation interference positions at the current moment according to the continuous distribution degree of the suspected interference positions and the downward trend of the abnormal possibility indexes in the historical time sequence at each suspected interference position at the current moment, and obtaining ventilation interference intensity indexes at the current moment according to the proportion of the ventilation interference positions at the current moment and the fluctuation intensity of the pressure difference sequence; an oxygen regulation module for determining representation weights of each monitoring position based on the ventilation interference possibility indexes and the ventilation interference intensity indexes, and regulating the comprehensive oxygen concentration at the current moment obtained by the representation weights of the monitoring positions and the oxygen concentration; The method for obtaining the suspected interference position comprises: For any monitoring position at any moment, the slope of the oxygen concentration sequence at each moment is obtained as the trend degree at each moment at the monitoring position; in a preset previous window at the moment, the trend synchronization degrees between the monitoring position and each other monitoring position at the moment are obtained according to the differences between the monitoring position and each other monitoring position in oxygen concentration and trend degree at each moment; When the trend synchronization degree is less than a preset similarity threshold, the corresponding other monitoring positions are recorded as deviated positions of the monitoring position; when the number of the deviated positions is greater than a preset abnormal threshold, the monitoring position is taken as a suspected interference position; The method for obtaining the abnormal possibility index comprises: For any suspected interference position at any moment, the ratio of the number of deviated positions of the suspected interference position to the total number of monitoring positions is taken as the deviated abnormal distribution index of the suspected interference position; The distances between the suspected interference position and each deviated position are negatively correlated and mapped as the position weights between the suspected interference position and each deviated position; the trend synchronization degrees between the suspected interference position and all deviated positions are weighted and summed with the position weights as weights, and negatively correlated and mapped to obtain the abnormal deviated intensity index of the suspected interference position; The abnormal possibility index of the suspected interference position is obtained by combining the deviated abnormal distribution index and the abnormal deviated intensity index; The method for obtaining the ventilation interference possibility index comprises: For any suspected interference position at the current moment, the period when the suspected interference position is continuously taken as a suspected interference position in the historical time sequence is recorded as an abnormal fluctuation period of the suspected interference position; the period from the starting moment of the first abnormal fluctuation period to the current moment is recorded as a key period. The length proportion of the abnormal fluctuation period on the key period is taken as a fault trend degree of the suspected interference position; the abnormal possible indicators on the key period are curve fitted, and a slope on the fitted curve is obtained; the number of negative slopes is taken as an abnormal recovery trend degree of the suspected interference position; The product of the fault trend degree of the suspected interference position after negative correlation mapping and the abnormal recovery trend degree is taken as a ventilation interference possible indicator of the suspected interference position; The determination method of the ventilation interference position comprises: The suspected interference position with the ventilation interference possible indicator greater than a preset interference threshold is taken as the ventilation interference position. The acquisition method of the ventilation interference intensity indicator comprises: The pressure difference standard deviation before the current moment in the pressure difference sequence is taken as a pressure fluctuation indicator of the current moment; The ventilation interference position and the non-suspected interference position at the current moment are both taken as normal positions; the proportion of the ventilation interference position in the normal positions at the current moment is taken as an influence range indicator of the current moment; the product of the influence range indicator and the pressure difference of the current moment is taken as a pressure flow indicator of the current moment; The ventilation interference intensity indicator of the current moment is obtained in combination with the pressure fluctuation indicator and the pressure flow indicator.

2. The energy-saving pressure swing adsorption air-conditioning type intelligent oxygen supply system based on highland region according to claim 1, characterized in that, The acquisition method of the representation weight comprises: The product of the ventilation interference intensity indicator and the ventilation interference possible indicator is negatively correlated and normalized to obtain the representation weight of each ventilation interference position; A preset maximum representation weight is taken as the representation weight of each non-suspected interference position; a preset minimum representation weight is taken as the representation weight of the monitoring position in the non-ventilation interference position in the suspected interference position; the preset minimum representation weight is less than the preset maximum representation weight.

3. The energy-saving pressure swing adsorption air-conditioning type intelligent oxygen supply system based on highland region according to claim 1, characterized in that, The acquisition method of the comprehensive oxygen concentration comprises: The representation weight of each monitoring position is taken as a weight to obtain the current comprehensive oxygen concentration by weighted averaging of the current oxygen concentration data of all monitoring positions.

4. The energy-saving pressure swing adsorption air-conditioning type intelligent oxygen supply system based on highland region according to claim 1, characterized in that, The acquisition method of the trend synchronization degree comprises: In the preset presequence window at the moment, the oxygen concentration difference and the trend degree difference between the monitoring position and each other monitoring position at each moment are calculated; The product of the oxygen concentration difference and the trend degree difference at each moment is multiplied, and the sum of the products of all moments is negatively correlated to obtain the trend synchronization degree between the monitoring position and each other monitoring position at the moment.

5. The energy-saving pressure swing adsorption air-conditioning type intelligent oxygen supply system based on highland region according to claim 1, characterized in that, The ventilation interference intensity indicator of the current moment is obtained in combination with the pressure fluctuation indicator and the pressure flow indicator, comprising: The product of the pressure fluctuation indicator and the pressure flow indicator is normalized to obtain the ventilation interference intensity indicator of the current moment.

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