Hot-pressing ventilation monitoring system based on loop network model

Abstract

The invention discloses a hot-pressing ventilation monitoring system based on a loop network model, and relates to the technical field of building environment engineering, and the system comprises a monitoring center which is connected with a network point collection module, an attribute processing module, a loop analysis module and an intelligent management and control module. Building comprehensive data is collected through the network point collection module; performing road end interception on the virtual loop space in an attribute processing module to obtain a virtual subunit, and performing heat balance extraction and balance restriction on the virtual subunit according to the building comprehensive data to obtain an isothermal restriction factor; the loop analysis module converts the isothermal constraint factor to obtain a constraint signal sequence, and sets a balance filtering coefficient to perform feature filtering on the isothermal constraint signal sequence to obtain a feature constraint coefficient; the intelligent management and control module performs virtual adjustment and safety comparison on the virtual subunits according to the feature restriction coefficient to obtain an abnormal alarm point; the operation effect of the ventilation system is accurately evaluated, and the accuracy and reliability of the monitoring system are improved.

Description

Technical Field

[0001] The invention relates to the technical field of building environment engineering, in particular to a heat pressure ventilation monitoring system based on a loop network model. Background Art

[0002] A loop network model refers to a mathematical model consisting of multiple interconnected loops, which can be used in different systems to describe and analyze the flow of information, energy or matter.

[0003] Thermal compression ventilation is a ventilation method that uses the air flow phenomenon caused by the difference in air density between indoor and outdoor temperatures. When the indoor air temperature is higher than the outdoor air temperature, the indoor hot air rises, and the outdoor cold air enters the room from the bottom of the building and is discharged from the top, achieving ventilation.

[0004] But at the same time, the effect of hot pressure ventilation is affected by factors such as outdoor climate conditions, building shape and surrounding environment, making it difficult to stably control the ventilation effect; if the ventilation system is to be monitored in real time, it may be necessary to invest in certain equipment and maintenance costs; the data of the ventilation system often involves complex physical processes, such as the dynamic changes of multiple variables such as temperature, humidity, and air pressure, which requires professional data analysis and processing capabilities; therefore, a system that can monitor the operating status of the hot pressure ventilation system in real time is needed in order to optimize and adjust the ventilation effect; for this purpose, a hot pressure ventilation monitoring system based on a loop network model is now provided. Summary of the invention

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A hot pressure ventilation monitoring system based on a loop network model includes a monitoring center, wherein the monitoring center is connected to a network point acquisition module, an attribute processing module, a loop analysis module, and an intelligent management and control module;

[0007] The network point acquisition module is used to construct a virtual loop space and collect comprehensive building data;

[0008] The process of collecting comprehensive building data includes:

[0009] Constructing a virtual loop space according to the target area, wherein the virtual loop space includes a tunnel subspace, a cave subspace, and an outdoor subspace;

[0010] Set a collection terminal according to the target area, collect comprehensive data of the target area through the collection terminal, and obtain comprehensive building data;

[0011] Upload the set acquisition end to the virtual loop space to obtain the virtual acquisition point;

[0012] The obtained virtual collection points are associated with the corresponding building comprehensive data.

[0013] The process of obtaining the isothermal constraint factor includes:

[0014] According to the obtained virtual collection points, the virtual loop space is intercepted at the road end to obtain a virtual subunit;

[0015] Extract heat balance of virtual subunits according to comprehensive building data to obtain thermal temperature unit data;

[0016] Perform thermal pressure balance on the virtual subunit according to the obtained thermal and temperature unit data to obtain the equilibrium resistance coefficient;

[0017] The virtual subunit is subjected to equilibrium constraints according to the thermal unit data and the equilibrium resistance coefficient to obtain the isothermal constraint factor.

[0018] The process of obtaining the intercept interval includes:

[0019] Performing signal conversion on the obtained isothermal constraint factor to obtain an isothermal constraint signal;

[0020] The isothermal control signals are balanced and sorted according to the obtained virtual subunits to obtain a control signal sequence;

[0021] The isothermal control signal is analyzed to obtain the control characteristics, the balance filtering coefficient is set according to the control characteristics, the balance filtering coefficient is stage-controlled to obtain the analysis parameters, and the balance filtering coefficient is intercepted and counted according to the analysis parameters to obtain the interception interval.

[0022] The process of obtaining the characteristic constraint coefficient includes:

[0023] The analysis series is obtained according to the obtained analysis parameters, interception intervals and constraint characteristics, and the balanced filtering coefficient is divided into intervals according to the obtained interception intervals to obtain the balanced coefficient segments;

[0024] The characteristic filtering is performed on the equal constraint signal sequence according to the obtained balance coefficient segment to obtain the characteristic constraint coefficient.

[0025] The process of obtaining the characteristic adjustment coefficient includes:

[0026] Generate a constraint coefficient spectrum diagram according to the characteristic constraint coefficient, mark the spectrum lines of the constraint coefficient spectrum diagram, obtain the characteristic coefficient spectrum lines, and upload the constraint coefficient spectrum diagram to the virtual loop space;

[0027] Set the safety threshold range, upload the safety threshold range to the constraint coefficient spectrum diagram, and obtain the safety threshold axis;

[0028] The monitoring center issues a pre-adjustment instruction to the virtual sub-unit, and the virtual sub-unit performs virtual adjustment according to the received pre-adjustment instruction to obtain a characteristic adjustment coefficient.

[0029] The process of virtual adjustment of the virtual subunit includes:

[0030] Performing thermal pressure balance on the obtained adjustment unit data to obtain the adjustment resistance coefficient;

[0031] Performing balance control on the virtual subunit according to the obtained adjustment unit data and adjustment resistance coefficient to obtain the adjustment control factor;

[0032] Performing signal conversion on the obtained regulatory constraint factor to obtain a regulatory constraint signal;

[0033] The characteristic adjustment coefficient is obtained by filtering the adjustment control signal according to the obtained balance coefficient segment.

[0034] The process of obtaining abnormal alarm points includes:

[0035] Uploading the obtained characteristic adjustment coefficient to the constraint coefficient spectrum diagram to obtain a virtual coefficient spectrum diagram;

[0036] Dynamically looping the obtained pre-adjustment instruction to obtain a loop adjustment instruction, virtually adjusting the virtual subunit according to the obtained loop adjustment instruction to obtain a characteristic adjustment coefficient, and uploading the obtained characteristic adjustment coefficient to a virtual coefficient spectrum diagram;

[0037] A safety comparison is performed on the virtual coefficient spectrum diagram according to the obtained safety threshold axis to obtain the abnormal alarm point.

[0038] Compared with the prior art, the invention has the following beneficial effects: the virtual loop space is intercepted at the road end to obtain a virtual subunit, the heat balance of the virtual subunit is extracted and balanced according to the comprehensive building data to obtain an isothermal constraint factor, the isothermal constraint factor is converted to obtain a constraint signal sequence, and a balance filtering coefficient is set to perform feature filtering on the isothermal constraint signal sequence to obtain a feature constraint coefficient; the heat pressure ventilation system of the underground building is converted into a virtual subunit in the virtual space for analysis, and the feature factor is extracted from the virtual subunit, which is beneficial to improving the analysis efficiency and monitoring accuracy;

[0039] The virtual sub-units are virtually adjusted and safety compared according to the characteristic constraint coefficients to obtain abnormal alarm points. By virtually adjusting different building areas in the virtual loop space, the scope of risk research is expanded, which is conducive to obtaining the optimal abnormal alarm points and facilitating the prediction of potential failures of the ventilation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0042] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] like Figure 1 As shown, a hot pressure ventilation monitoring system based on a loop network model includes a monitoring center, and the monitoring center is connected to a network point acquisition module, an attribute processing module, a loop analysis module, and an intelligent management and control module;

[0044] The network point collection module is used to collect comprehensive building data, and the specific process includes:

[0045] Constructing a virtual loop space according to the target area, wherein the virtual loop space includes a tunnel subspace, a cave subspace, and an outdoor subspace;

[0046] It should be further explained that, in the specific implementation process, the tunnel subspace is generated based on the deep buried tunnel in reality, the cavern subspace is generated based on the underground cavern in reality, and the outdoor subspace is generated based on the outdoor environment connected to the deep buried tunnel and the underground cavern in reality, which together constitute a virtual loop space. The linking method of the tunnel subspace, cavern subspace and outdoor subspace in the virtual loop space is exactly the same as the linking method of the deep buried tunnel, underground cavern and the connected outdoor environment in reality; in particular, the target area is represented as the area corresponding to the thermal pressure ventilation monitoring;

[0047] Several collection terminals are set according to the target area, and the collection terminals are set at data collection points in the target area, and the data collected by each collection terminal is all data information of the largest area that can be radiated by the collection terminal;

[0048] The comprehensive data of the target area is collected through the collection end to obtain the comprehensive building data;

[0049] The comprehensive building data includes temperature data, air pressure data, wind speed data and sampling time;

[0050] Furthermore, the temperature data represents the temperature corresponding to the deep-buried tunnel, underground cavern and the connected outdoor environment, the air pressure data represents the corresponding air pressure at the collection end, and the wind speed data represents the indoor and outdoor wind speeds; the point collection time represents the time corresponding to the collection of the building comprehensive data;

[0051] Upload the set acquisition end to the virtual loop space to obtain the virtual acquisition point;

[0052] The obtained virtual collection points are associated with the corresponding building comprehensive data.

[0053] The attribute processing module is used to perform road-end interception on the virtual loop space to obtain virtual subunits, extract and balance the virtual subunits according to the comprehensive building data, and obtain isothermal constraint factors. The specific process includes:

[0054] According to the obtained virtual collection points, the virtual loop space is intercepted at the road end to obtain a virtual subunit;

[0055] It should be further explained that, in the specific implementation process, the road end interception means intercepting the tunnel subspace according to the virtual collection point in the virtual loop space, taking the virtual collection point as the dividing point, marking the space between two adjacent virtual collection points as a tunnel subunit, and similarly, marking the space between two adjacent virtual collection points in the cave subspace as a cave subunit, and marking the space between two adjacent virtual collection points in the outdoor subspace as an outdoor subunit;

[0056] Mark the obtained tunnel subunit, cave subunit and outdoor subunit as virtual subunits;

[0057] According to the obtained comprehensive building data, heat balance extraction is performed on the virtual sub-unit to obtain thermal temperature unit data;

[0058] Furthermore, the heat balance extraction means matching the virtual subunits according to the temperature data, pressure data and wind speed data in the comprehensive building data to obtain the temperature data, pressure data and wind speed data corresponding to the virtual subunits, that is, the thermal unit data;

[0059] Perform point-to-point linking according to the obtained virtual sub-units and virtual collection points to obtain a virtual ventilation loop;

[0060] Furthermore, the point-collection link represents a closed loop capable of ventilation in the virtual loop space, passing through the tunnel subspace, the cavern subspace and the outdoor subspace;

[0061] Perform thermal pressure balance on the virtual subunit according to the obtained thermal and temperature unit data to obtain the equilibrium resistance coefficient;

[0062] It should be further explained that, in the specific implementation process, for the virtual sub-unit, the balance resistance coefficient of its two virtual collection points can be established. According to the fact that the ventilation pipe network is composed of a closed loop, that is, the ventilation pipe network is composed of a virtual ventilation loop, the balance resistance coefficients of each virtual sub-unit are superimposed along the closed loop, and the total balance resistance coefficient of the virtual ventilation loop can be obtained;

[0063] Furthermore, the obtained equilibrium resistance coefficient is marked as P j ,in, j represents the number of the virtual subunit, j = 1, 2, 3, ..., v1, v1 is a positive integer, ρ0 is the ambient air density, t0 represents the ambient air temperature, t s,j is the starting air temperature of the jth virtual subunit, t e,j is the air temperature at the end of the jth virtual subunit, g represents the acceleration of gravity, and Δz represents the vertical height difference between the inlet and outlet of the virtual subunit;

[0064] According to the obtained thermal unit data and equilibrium resistance coefficient, the virtual subunit is subjected to equilibrium constraint to obtain the isothermal constraint factor;

[0065] It should be further explained that, in the specific implementation process, the heat balance relationship of each virtual subunit is obtained according to the heat transfer between the airflow and the internal heat source and the inner wall of the maintenance structure, which is the isothermal constraint factor;

[0066] Furthermore, the obtained isothermal constraint factor is marked as D j ,in, β1 and β2 are weight factors, and β1+β2=1, V j represents the volume of virtual subunit j, c p represents the specific heat of air, ρ j represents the air density in virtual subunit j, T rjn represents the air temperature at time n in the jth virtual subunit, T rj(n-1) represents the air temperature at time n-1 in the jth virtual subunit, and Δτ represents the time interval.

[0067] The loop analysis module is used to convert the isothermal constraint factor to obtain the constraint signal sequence, set the balance filtering coefficient to perform feature filtering on the isothermal constraint signal sequence, and obtain the feature constraint coefficient. The specific process includes:

[0068] Performing signal conversion on the obtained isothermal constraint factor to obtain an isothermal constraint signal;

[0069] The isothermal control signals are balanced and sorted according to the obtained virtual subunits to obtain a control signal sequence;

[0070] Furthermore, the balanced sorting means sorting the isothermal control signals in the virtual loop space according to the distribution of the virtual subunits and the order of the virtual acquisition points to obtain a control signal sequence;

[0071] Performing signal analysis on the obtained isothermal control signal to obtain the control characteristics;

[0072] The constraint characteristics include frequency range, noise level and signal period;

[0073] Setting a balanced filtering coefficient according to the obtained constraint characteristics;

[0074] The balanced filtering coefficient is expressed in the form of a function;

[0075] The obtained equilibrium filtration coefficient is stage-controlled to obtain analysis parameters;

[0076] Furthermore, the stage control means performing scaling and translation transformation on the balanced filtering coefficient in the time dimension and the frequency dimension, and performing statistics on the parameters of the scaling and translation transformation to obtain analysis parameters;

[0077] According to the obtained analysis parameters, interception statistics are performed on the equilibrium filtering coefficient to obtain the interception interval;

[0078] Furthermore, the intercept statistics represent performing statistics on the distance between two adjacent analysis parameters to obtain an intercept interval;

[0079] The analysis order is obtained according to the obtained analysis parameters, interception interval and constraint characteristics, and the obtained analysis order is marked as F, where: L represents the sequence signal length of the equal constraint signal sequence, a represents the number of interception intervals, Δb represents the interception interval, c represents the analysis parameter, H max Indicates the maximum frequency in the frequency range of the constraint characteristic, H min Indicates the minimum frequency value in the frequency range of the constraint characteristic, T 周 Indicates the signal period;

[0080] The balanced filtering coefficient is divided into intervals according to the obtained interception intervals to obtain balanced coefficient segments;

[0081] Furthermore, the interval division means that the balanced filtering coefficient is equally divided according to the number of intercepted intervals to obtain balanced coefficient segments of equal length;

[0082] Performing feature filtering on the equal constraint signal sequence according to the obtained balance coefficient segment to obtain a feature constraint coefficient;

[0083] It should be further explained that, in the specific implementation process, the feature filtering process includes:

[0084] According to the order of dividing the balance coefficient into intervals, the obtained balance coefficient segments are uploaded to the constraint signal sequence, and the balance coefficient segments are convolved with the corresponding positions of the constraint signal sequence to obtain the convolved balance coefficient segments;

[0085] Performing exponential transformation on the obtained convolution balance coefficient segment to obtain an exponential balance coefficient segment;

[0086] The exponential equilibrium coefficient segments are sequentially combined according to the obtained constraint signal sequence to obtain the isothermal equilibrium coefficient;

[0087] The obtained isothermal equilibrium coefficients are subjected to inverse discrete cosine transformation to obtain characteristic constraint coefficients.

[0088] The intelligent control module is used to perform virtual adjustment and safety comparison on the virtual subunit according to the characteristic constraint coefficient to obtain abnormal alarm points. The specific process includes:

[0089] Generate a constraint coefficient spectrum diagram according to the obtained characteristic constraint coefficient;

[0090] Marking the spectrum lines of the obtained constraint coefficient spectrum diagram to obtain characteristic coefficient spectrum lines;

[0091] Mark nodes on the constraint coefficient spectrum diagram according to the obtained virtual subunits to obtain node coefficients;

[0092] Furthermore, the node marking indicates uploading the obtained virtual subunit to the horizontal axis of the constraint coefficient spectrum diagram, and corresponding the nodes of the horizontal axis to the characteristic coefficient spectrum lines, and obtaining the characteristic constraint coefficient corresponding to the isothermal constraint factor corresponding to the virtual subunit, that is, the node coefficient;

[0093] Uploading the obtained constraint coefficient spectrum diagram to the virtual loop space;

[0094] Setting a safety threshold range, wherein the safety threshold range includes an upper threshold limit and a lower threshold limit;

[0095] The obtained safety threshold range is uploaded to the constraint coefficient spectrum diagram to obtain the safety threshold axis;

[0096] Further, the upper threshold value and the lower threshold value are uploaded to the constraint coefficient spectrum diagram to obtain the upper threshold value axis and the lower threshold value axis, and the obtained upper threshold value axis and the lower threshold value axis are two parallel line segments parallel to the horizontal axis of the constraint coefficient spectrum diagram;

[0097] The monitoring center issues a pre-adjustment instruction to the virtual sub-unit, and the virtual sub-unit performs virtual adjustment according to the received pre-adjustment instruction to obtain a characteristic adjustment coefficient;

[0098] It should be further explained that, in the specific implementation process, the pre-adjustment instruction indicates controlling the virtual subunit to adjust the data, that is, to virtually adjust the comprehensive building data of the virtual subunit, for example, adjusting the indoor temperature of the jth virtual subunit from y1 to y2;

[0099] According to the set instructions, the comprehensive building data in the virtual sub-unit is adjusted to the corresponding value to obtain the adjusted unit data;

[0100] The virtual adjustment process includes:

[0101] Performing thermal pressure balance on the obtained adjustment unit data to obtain the adjustment resistance coefficient;

[0102] Performing balance control on the virtual subunit according to the obtained adjustment unit data and adjustment resistance coefficient to obtain the adjustment control factor;

[0103] Performing signal conversion on the obtained regulatory constraint factor to obtain a regulatory constraint signal;

[0104] Perform feature filtering on the regulation control signal according to the obtained balance coefficient segment to obtain a feature regulation coefficient;

[0105] Uploading the obtained characteristic adjustment coefficient to the constraint coefficient spectrum diagram to obtain a virtual coefficient spectrum diagram;

[0106] Dynamically looping the obtained pre-adjustment instruction to obtain a loop adjustment instruction, virtually adjusting the virtual subunit according to the obtained loop adjustment instruction to obtain a characteristic adjustment coefficient, and uploading the obtained characteristic adjustment coefficient to a virtual coefficient spectrum diagram;

[0107] Furthermore, the dynamic cycle means changing the set pre-adjustment instruction and changing the adjusted value, so that the virtual subunit can satisfy all possible value ranges in the virtual loop space to the maximum extent, thereby increasing the universality of hot pressure ventilation monitoring;

[0108] Perform a safety comparison on the virtual coefficient spectrum diagram according to the obtained safety threshold axis to obtain an abnormal alarm point;

[0109] It should be further explained that, in the specific implementation process, the safety comparison means that in the virtual coefficient spectrum diagram, the characteristic adjustment index greater than the upper threshold axis and less than the lower threshold axis is marked as an abnormal ventilation point, indicating that the characteristic adjustment coefficient of the virtual subunit after virtual adjustment through the cyclic adjustment instruction in the virtual loop space exceeds the safety range, that is, the hot pressure ventilation condition of the virtual subunit is unqualified and normal ventilation cannot be performed;

[0110] The characteristic adjustment index greater than or equal to the lower threshold axis and less than or equal to the upper threshold axis is marked as a safe ventilation point, indicating that the characteristic adjustment coefficient after the virtual subunit is virtually adjusted through the cyclic adjustment instruction in the virtual loop space is within the safe range and does not affect the normal operation of the underground building thermal pressure ventilation;

[0111] Obtain the circulation adjustment instruction corresponding to the abnormal ventilation point and record it as the abnormal alarm point;

[0112] The control center issues an abnormal warning to the abnormal alarm point. When the abnormal alarm point is detected in the virtual loop space, an early warning instruction is issued to inspect and repair the hot pressure ventilation system of the underground building until the abnormal warning is eliminated.

[0113] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A hot pressure ventilation monitoring system based on a loop network model, including a monitoring center, characterized in that: The monitoring center is connected to a network point acquisition module, an attribute processing module, a loop analysis module and an intelligent management and control module; The network point acquisition module is used to construct a virtual loop space and collect comprehensive building data; The attribute processing module is used to perform road-end interception on the virtual loop space to obtain virtual subunits, extract and balance the virtual subunits according to the comprehensive building data, and obtain isothermal constraint factors; The loop analysis module is used to perform signal conversion and balance sorting on the isothermal constraint factors to obtain a constraint signal sequence, set a balance filtering coefficient and perform interception statistics to obtain an interception interval, and perform feature filtering on the isothermal constraint signal sequence through the interception interval, analysis parameters and constraint characteristics to obtain a feature constraint coefficient; The intelligent management and control module is used to generate a constraint coefficient spectrum diagram according to the characteristic constraint coefficient, perform virtual adjustment on the virtual sub-unit to obtain the characteristic adjustment coefficient, upload the characteristic adjustment coefficient to the constraint coefficient spectrum diagram to obtain the virtual coefficient spectrum diagram, perform safety comparison on the virtual coefficient spectrum diagram according to the safety threshold axis, and obtain the abnormal alarm point.

2. The hot pressure ventilation monitoring system based on the loop network model according to claim 1 is characterized in that: The process of collecting comprehensive building data includes: Constructing a virtual loop space according to the target area, wherein the virtual loop space includes a tunnel subspace, a cave subspace, and an outdoor subspace; Set a collection terminal according to the target area, collect comprehensive data of the target area through the collection terminal, and obtain comprehensive building data; Upload the set acquisition end to the virtual loop space to obtain the virtual acquisition point; The obtained virtual collection points are associated with the corresponding building comprehensive data.

3. The hot pressure ventilation monitoring system based on the loop network model according to claim 2 is characterized in that: The process of obtaining the isothermal constraint factor includes: According to the obtained virtual collection points, the virtual loop space is intercepted at the road end to obtain a virtual subunit; Extract heat balance of virtual subunits according to comprehensive building data to obtain thermal temperature unit data; Perform thermal pressure balance on the virtual subunit according to the obtained thermal and temperature unit data to obtain the equilibrium resistance coefficient; The virtual subunit is subjected to equilibrium constraints according to the thermal unit data and the equilibrium resistance coefficient to obtain the isothermal constraint factor.

4. The hot pressure ventilation monitoring system based on the loop network model according to claim 3 is characterized in that: The process of obtaining the intercept interval includes: Performing signal conversion on the obtained isothermal constraint factor to obtain an isothermal constraint signal; The isothermal control signals are balanced and sorted according to the obtained virtual subunits to obtain a control signal sequence; The isothermal control signal is analyzed to obtain the control characteristics, the balance filtering coefficient is set according to the control characteristics, the balance filtering coefficient is stage-controlled to obtain the analysis parameters, and the balance filtering coefficient is intercepted and counted according to the analysis parameters to obtain the interception interval.

5. The heat pressure ventilation monitoring system based on the loop network model according to claim 4 is characterized in that: The process of obtaining the characteristic constraint coefficient includes: The analysis series is obtained according to the obtained analysis parameters, interception intervals and constraint characteristics, and the balance filter coefficient is divided into intervals according to the obtained interception intervals to obtain the balance coefficient segments; The characteristic filtering is performed on the equal constraint signal sequence according to the obtained balance coefficient segment to obtain the characteristic constraint coefficient.

6. The heat-pressure ventilation monitoring system based on the loop network model according to claim 5 is characterized in that: The process of obtaining the characteristic adjustment coefficient includes: Generate a constraint coefficient spectrum diagram according to the characteristic constraint coefficient, mark the spectrum lines of the constraint coefficient spectrum diagram, obtain the characteristic coefficient spectrum lines, and upload the constraint coefficient spectrum diagram to the virtual loop space; Set the safety threshold range, upload the safety threshold range to the constraint coefficient spectrum diagram, and obtain the safety threshold axis; The monitoring center issues a pre-adjustment instruction to the virtual sub-unit, and the virtual sub-unit performs virtual adjustment according to the received pre-adjustment instruction to obtain a characteristic adjustment coefficient.

7. The hot pressure ventilation monitoring system based on the loop network model according to claim 6 is characterized in that: The process of virtual adjustment of the virtual subunit includes: Performing thermal pressure balance on the obtained adjustment unit data to obtain the adjustment resistance coefficient; Performing balance control on the virtual subunit according to the obtained adjustment unit data and adjustment resistance coefficient to obtain the adjustment control factor; Performing signal conversion on the obtained regulatory constraint factor to obtain a regulatory constraint signal; The characteristic adjustment coefficient is obtained by filtering the adjustment control signal according to the obtained balance coefficient segment.

8. The hot pressure ventilation monitoring system based on the loop network model according to claim 7 is characterized in that: The process of obtaining abnormal alarm points includes: Uploading the obtained characteristic adjustment coefficient to the constraint coefficient spectrum diagram to obtain a virtual coefficient spectrum diagram; Dynamically looping the obtained pre-adjustment instruction to obtain a loop adjustment instruction, virtually adjusting the virtual subunit according to the obtained loop adjustment instruction to obtain a characteristic adjustment coefficient, and uploading the obtained characteristic adjustment coefficient to a virtual coefficient spectrum diagram; A safety comparison is performed on the virtual coefficient spectrum diagram according to the obtained safety threshold axis to obtain the abnormal alarm point.

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