Thermal compression ventilation monitoring system based on loop network model

Abstract

The present invention discloses a heat-pressure ventilation monitoring system based on a loop network model, which relates to the field of building environment engineering technology. The monitoring center includes a monitoring center, which 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 collect comprehensive building data; the virtual loop space is intercepted at the road end in the attribute processing module to obtain a virtual sub-unit, and the thermal balance of the virtual sub-unit is extracted and balanced according to the comprehensive building data to obtain an isothermal constraint factor; the isothermal constraint factor is converted in the loop analysis module 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 virtual sub-unit is virtually adjusted and safety compared in the intelligent management and control module according to the feature constraint coefficient to obtain an abnormal alarm point; the operation effect of the ventilation system is accurately evaluated, thereby improving the accuracy and reliability of the monitoring system.

Description

Technical Field

[0001] The present 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 is a mathematical model consisting of multiple interconnected loops that can be used to describe and analyze the flow of information, energy, or matter in different systems.

[0003] Thermal compression ventilation utilizes the air flow 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 warm air rises, and the cool outdoor air enters the building from the bottom and is exhausted from the top, achieving ventilation.

[0004] However, the effectiveness of hot-pressed ventilation is affected by factors such as outdoor climate conditions, building shape, and the surrounding environment, making it difficult to stably control the ventilation effect. Real-time monitoring of the ventilation system may require investment in equipment and maintenance costs. Ventilation system data 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 is needed that can monitor the operating status of the hot-pressed ventilation system in real time in order to optimize and adjust the ventilation effect. To this end, a hot-pressed 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 heat compression ventilation monitoring system based on a loop network model includes a monitoring center 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 cavern subspace, and an outdoor subspace;

[0010] Set up 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 terminal 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 based on comprehensive building data to obtain thermal 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 control factor to obtain an isothermal control signal;

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

[0021] Signal analysis is performed on the isothermal control signal 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 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, intercept intervals and control characteristics, and the balance filter coefficient is divided into intervals according to the obtained intercept intervals to obtain the balance 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 line of the constraint coefficient spectrum diagram to obtain the characteristic coefficient spectrum line, 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 regulation unit data and regulation resistance coefficient to obtain the regulation 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 to obtain a virtual coefficient spectrum;

[0036] Dynamically looping the obtained pre-adjustment instruction to obtain a loop adjustment instruction, performing virtual adjustment on 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] The virtual coefficient spectrum is safely compared according to the obtained safety threshold axis to obtain the abnormal alarm point.

[0038] Compared with the prior art, the present invention has the following advantages: performing road-end interception on a virtual loop space to obtain a virtual subunit; extracting and balancing the thermal balance of the virtual subunit based on comprehensive building data to obtain an isothermal constraint factor; converting the isothermal constraint factor to obtain a constraint signal sequence; setting a balance filtering coefficient to perform feature filtering on the isothermal constraint signal sequence to obtain a feature constraint coefficient; converting the underground building's heat-pressure ventilation system into a virtual subunit in a virtual space for analysis; and extracting feature factors from the virtual subunit, thereby improving analysis efficiency and monitoring accuracy.

[0039] Virtual subunits are virtually adjusted and safety compared according to the characteristic constraint coefficients to obtain abnormal alarm points. By virtually adjusting different building areas separately 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 following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

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

[0042] The technical solutions of the present invention will be described clearly and completely below with reference to the embodiments. It is obvious that the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort are intended to fall within the scope of protection of the present invention.

[0043] like Figure 1 As shown, the heat compression ventilation monitoring system based on the loop network model includes a monitoring center, which 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 cavern subspace, and an outdoor subspace;

[0046] It should be further explained that, in the specific implementation process, the tunnel subspace is generated based on a real deep-buried tunnel, the cavern subspace is generated based on a real underground cavern, and the outdoor subspace is generated based on a real outdoor environment connected to the deep-buried tunnel and underground cavern, together forming a virtual loop space. The tunnel subspace, cavern subspace, and outdoor subspace in the virtual loop space are linked in exactly the same way as the deep-buried tunnel, underground cavern, and connected outdoor environment in reality. In particular, the target area is represented as the area corresponding to thermal pressure ventilation monitoring.

[0047] Several collection terminals are set up according to the target area. The collection terminals are set up 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 covered by the collection terminal.

[0048] Collect comprehensive data of the target area through the collection terminal to obtain 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 connected outdoor environment; the air pressure data represents the air pressure corresponding to the collection end; the wind speed data represents the wind speed indoors and outdoors; and the point sampling time represents the time corresponding to the collection of the building comprehensive data;

[0051] Upload the set acquisition terminal 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 thermal balance of the virtual subunits based on the comprehensive building data, and obtain isothermal control 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 a specific implementation, the road-end interception means intercepting the tunnel subspace according to the virtual collection points in the virtual loop space, using the virtual collection points as the dividing points, and marking the space between two adjacent virtual collection points as a tunnel subunit. Similarly, the space between two adjacent virtual collection points in the cave subspace is marked as a cave subunit, and the space between two adjacent virtual collection points in the outdoor subspace is marked as an outdoor subunit.

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

[0057] Perform heat balance extraction on virtual subunits based on the obtained comprehensive building data 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, namely the thermal unit data;

[0059] Perform point-to-point linking based on the obtained virtual subunits and virtual collection points to obtain a virtual ventilation loop;

[0060] Furthermore, the point-to-point 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 a virtual sub-unit, a balanced resistance coefficient of its two virtual collection points can be established. Since the ventilation pipe network is composed of a closed loop, that is, the ventilation pipe network is composed of a virtual ventilation loop, the balanced resistance coefficients of each virtual sub-unit are superimposed along the closed loop to obtain the total balanced resistance coefficient of the virtual ventilation loop.

[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 external 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 control to obtain the isothermal control 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 a constraint signal sequence, set a balanced filtering coefficient to perform feature filtering on the isothermal constraint signal sequence, and obtain a feature constraint coefficient. The specific process includes:

[0068] performing signal conversion on the obtained isothermal control factor to obtain an isothermal control 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 control characteristics;

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

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

[0074] The balanced filtering coefficient is expressed in a functional form;

[0075] The obtained equilibrium filtration coefficient is controlled in stages 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] Perform intercept statistics on the equilibrium filtering coefficient according to the obtained analysis parameters to obtain the intercept 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 series is obtained according to the obtained analysis parameters, intercept interval and constraint characteristics, and the obtained analysis series 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, and H represents the number of interception intervals. 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 interval to obtain a balanced coefficient segment;

[0081] Furthermore, the interval division means that the balanced filtering coefficient is divided equally according to the number of interception 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 a specific implementation process, the feature filtering process includes:

[0084] Uploading the obtained balance coefficient segments to the constraint signal sequence according to the order of dividing the balance coefficients into intervals, and convolving the balance coefficient segments with corresponding positions of the constraint signal sequence to obtain 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 control signal sequence to obtain the isothermal equilibrium coefficient;

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

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

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

[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 mark 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 to obtain the characteristic constraint coefficient corresponding to the isothermal constraint factor corresponding to the virtual subunit, which is the node coefficient;

[0093] Uploading the obtained constraint coefficient spectrum graph 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] Furthermore, the upper threshold value and the lower threshold value are uploaded to the constraint coefficient spectrum graph to obtain an upper threshold value axis and a lower threshold value axis, wherein 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 graph;

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

[0098] It should be further explained that, in a specific implementation process, the pre-adjustment instruction indicates controlling the virtual sub-unit to perform data adjustment, that is, performing virtual adjustment on the building comprehensive data of the virtual sub-unit, for example, adjusting the indoor temperature of the j-th virtual sub-unit from y1 to y2;

[0099] According to the set instructions, the building comprehensive 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 regulation unit data and regulation resistance coefficient to obtain the regulation 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 to obtain a virtual coefficient spectrum;

[0106] Dynamically looping the obtained pre-adjustment instruction to obtain a loop adjustment instruction, performing virtual adjustment on 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 loop means changing the pre-adjustment instructions set, changing the adjustment value, so that the virtual subunit can meet all possible value ranges in the virtual loop space to the maximum extent, thereby increasing the universality of heat 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 a specific implementation process, the safety comparison is represented by marking the characteristic adjustment index greater than the upper threshold axis and less than the lower threshold axis in the virtual coefficient spectrum as an abnormal ventilation point, indicating that the characteristic adjustment coefficient of the virtual sub-unit 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 sub-unit 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 sub-unit 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 thermal pressure ventilation of the underground building;

[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 for 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 intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A heat-pressure ventilation monitoring system based on a loop network model, including a monitoring center, is 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. 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 cavern subspace, and an outdoor subspace; Set up 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 terminal to the virtual loop space to obtain the virtual acquisition point; Associating the obtained virtual collection points with corresponding 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 thermal balance of the virtual subunits according to the comprehensive building data, and obtain isothermal control factors; The loop analysis module is used to perform signal conversion and balance sorting on the isothermal control factors to obtain a control signal sequence, set a balance filtering coefficient and perform interception statistics to obtain an interception interval, and perform feature filtering on the isothermal control signal sequence using the interception interval, analysis parameters and control characteristics to obtain a feature control coefficient; The intelligent control module is used to generate a constraint coefficient spectrum diagram according to the characteristic constraint coefficient and perform virtual adjustment on the virtual subunit. The process of obtaining the characteristic adjustment coefficient includes: Generate a constraint coefficient spectrum diagram according to the characteristic constraint coefficient, mark the spectrum line of the constraint coefficient spectrum diagram to obtain the characteristic coefficient spectrum line, 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. The process 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 regulation unit data and regulation resistance coefficient to obtain the regulation control factor; performing signal conversion on the obtained regulatory constraint factor to obtain a regulatory constraint signal; Perform feature filtering on the regulation control signal according to the obtained balance coefficient segment to obtain a feature regulation coefficient; The characteristic adjustment coefficient is uploaded to the constraint coefficient spectrum to obtain a virtual coefficient spectrum. The virtual coefficient spectrum is then compared with the safety threshold axis to obtain the abnormal alarm point. The process includes: Uploading the obtained characteristic adjustment coefficient to the constraint coefficient spectrum to obtain a virtual coefficient spectrum; Dynamically looping the obtained pre-adjustment instruction to obtain a loop adjustment instruction, performing virtual adjustment on 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; The virtual coefficient spectrum is safely compared according to the obtained safety threshold axis to obtain the abnormal alarm point.

2. The heat-pressure ventilation monitoring system based on the loop network model according to claim 1 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 based on comprehensive building data to obtain thermal unit data; Perform thermal-pressure balance on the virtual subunit according to the obtained thermal-temperature unit data to obtain the equilibrium resistance coefficient; The virtual sub-unit is subjected to equilibrium constraints according to the thermal unit data and the equilibrium resistance coefficient to obtain the isothermal constraint factor.

3. The heat-pressure ventilation monitoring system based on the loop network model according to claim 2 is characterized in that: The process of obtaining the intercept interval includes: performing signal conversion on the obtained isothermal control factor to obtain an isothermal control signal; The isothermal control signals are balanced and sorted according to the obtained virtual subunits to obtain a control signal sequence; Signal analysis is performed on the isothermal control signal 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 analysis parameters, and the balance filtering coefficient is intercepted and counted according to the analysis parameters to obtain the interception interval.

4. The heat-pressure ventilation monitoring system based on the loop network model according to claim 3 is characterized in that: The process of obtaining the characteristic constraint coefficient includes: The analysis series is obtained according to the obtained analysis parameters, intercept intervals and control characteristics, and the balance filter coefficient is divided into intervals according to the obtained intercept 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.

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