An intelligent ventilation regulation method and system for underground interchanges

Abstract

The application provides a kind of intelligent ventilation regulation method and system for underground intercommunication engineering, it is related to tunnel ventilation technical field, comprising: S1, constructs the ventilation network basic model of underground intercommunication engineering;S2, based on ventilation network basic model, underground intercommunication is divided into upstream tunnel section, downstream tunnel section and connecting tunnel section;And the ventilation flow rate corresponding to each tunnel section is obtained;S3, the first flow ratio is solved, and the air flow direction of each tunnel section is determined;S4, based on historical regulation data, a regulation scheme rule base is constructed;S5, based on the ventilation network basic model established in S1, an evaluation prediction model is constructed, and a target fan regulation scheme is selected;S6, based on the second flow ratio obtained, it is judged whether the ventilation network basic model parameters are modified, the intelligent perception, accurate prediction and dynamic optimization of underground intercommunication engineering ventilation are realized, the energy consumption is reduced, and the stability and adaptability of ventilation regulation are improved.

Description

Technical Field

[0001] This invention relates to the field of tunnel ventilation technology, and in particular to an intelligent ventilation control method and system for underground interchange projects. Background Technology

[0002] Currently, the common approach in engineering is to use a pre-configured fan setup based on fixed operating conditions. This method relies on numerical simulations and engineering experience during the design phase to pre-configure fan combinations for a limited number of typical operating conditions. However, this method still has limitations when applied to complex interconnected engineering projects.

[0003] First, the coupling of airflow in each tunnel section is not considered, and independent control of a single tunnel section will change the pressure balance of the entire network, leading to airflow turbulence. Second, the preset scheme cannot cover all possible complex situations. Third, it cannot achieve on-demand adjustment of air volume, which can easily lead to increased energy consumption and operating costs. Fourth, the system lacks data feedback and self-correction capabilities, and cannot cope with changes in operating conditions during long-term operation.

[0004] In summary, existing ventilation control technologies are significantly inadequate for handling the complex ventilation networks of underground interconnected projects. Therefore, there is an urgent need for an intelligent ventilation control method and system capable of real-time sensing of airflow conditions, intelligent prediction of fan control effects, and dynamic optimization of control strategies. Summary of the Invention

[0005] In view of this, the purpose of this invention is to overcome the shortcomings of existing ventilation control technology in underground interchange projects and to provide a precise, intelligent, efficient and adaptive ventilation control solution.

[0006] In a first aspect, embodiments of the present invention provide an intelligent ventilation control method for underground interchange projects, comprising: S1. Construct a basic model of the ventilation network for the underground interchange project; S2. Based on the basic model of the ventilation network, the underground interchange is divided into upstream tunnel segment, downstream tunnel segment and connecting tunnel segment; and the ventilation velocity corresponding to each tunnel segment is obtained; S3. Calculate the first confluence ratio based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and determine the airflow direction of each tunnel section based on the first confluence ratio; S4. Construct a control scheme rule base based on historical control data, and select at least one fan control scheme from the control scheme rule base based on the airflow direction index principle of the tunnel section. S5. Based on the ventilation network basic model established in S1, construct an evaluation and prediction model, input the at least one fan control scheme into the evaluation and prediction model to generate the predicted value of the confluence ratio and the predicted value of the mass flow rate corresponding to the at least one fan control scheme, so as to select the target fan control scheme. S6. Obtain the second confluence ratio, which is the actual value of the confluence ratio when the target fan control scheme is executed. Compare the second confluence ratio with the predicted value of the confluence ratio corresponding to the target fan control scheme to obtain the comparison result. Based on the comparison result, determine whether the adjustable parameters in the ventilation network basic model need to be adjusted.

[0007] In conjunction with the first aspect, the present invention provides a first possible implementation of the first aspect, wherein, in step S3, the first confluence ratio is calculated based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and the airflow direction of each tunnel section is determined based on the first confluence ratio. The calculation of the first confluence ratio is as follows: ; in, —The merging ratio corresponding to the downstream tunnel section and the connecting tunnel section; M—mass flow rate of ventilation flow; down—the downstream tunnel section; con — connects to the tunnel section; —Cross-sectional area of ​​the tunnel section; —Density of the ventilation flow; v con —Ventilation velocity connecting the tunnel section; v down —Ventilation velocity in the downstream tunnel section.

[0008] In conjunction with the first aspect, this embodiment of the invention provides a second possible implementation of the first aspect, wherein, in step S3, the first merging ratio is calculated based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and the airflow direction of each tunnel section is determined based on the first merging ratio, the airflow direction of the tunnel section is determined as follows: Define the positive direction for each tunnel segment; The airflow direction of the tunnel section is determined based on the first confluence ratio.

[0009] In conjunction with the first aspect, this embodiment of the invention provides a third possible implementation of the first aspect, wherein the step of defining the positive direction of each tunnel segment includes the following: The positive direction of the downstream tunnel section is from the confluence point to the exit of the downstream tunnel section; The positive direction of the upstream tunnel section is the direction from the entrance of the upstream tunnel section to the confluence point; The positive direction of the connecting tunnel section is the direction from the entrance of the connecting tunnel section to the merging point.

[0010] In conjunction with the first aspect, this embodiment of the invention provides a fourth possible implementation of the first aspect, wherein the step of determining the airflow direction of the tunnel section based on the first confluence ratio in S3 is as follows: When 0 < When the airflow is less than 1, the airflow direction in all tunnel sections is positive. when When the value is greater than 1, the airflow direction in the upstream tunnel section is reversed; when When the airflow is less than 0, the airflow direction in the connecting tunnel section is reversed.

[0011] In conjunction with the first aspect, this embodiment of the invention provides a fifth possible implementation of the first aspect, wherein, in step S5, an evaluation and prediction model is constructed based on the ventilation network basic model established in S1, and the at least one fan control scheme is input into the evaluation and prediction model to generate the predicted value of the confluence ratio and the predicted value of the mass flow rate for each of the at least one fan control scheme, in order to select the target fan control scheme, the formula for constructing the evaluation and prediction model is as follows: ; in, —Predicted merging ratio; —Pressure rise value of the jet fan in the downstream tunnel section; —Pressure rise value of the jet fan connecting the tunnel section; —Predicted mass flow rate of downstream tunnel section; —Tunnel flow resistance in the downstream tunnel section; —Tunnel flow resistance connecting tunnel sections.

[0012] In conjunction with the first aspect, this embodiment of the invention provides a sixth possible implementation of the first aspect, wherein, in step S5, an evaluation and prediction model is constructed based on the ventilation network basic model established in S1, and the at least one fan control scheme is input into the evaluation and prediction model to generate a combined flow ratio prediction value and a mass flow prediction value corresponding to each of the at least one fan control scheme, in order to select a target fan control scheme, the content of generating the corresponding combined flow ratio prediction value and mass flow prediction value is as follows: Generate corresponding updated fan pressure values ​​based on at least one fan control scheme described in S4; The updated wind turbine pressure value and the flow resistance of each tunnel are input into the evaluation and prediction model, and the predicted mass flow rate of the downstream tunnel section is output. ; Based on the predicted mass flow rate of the downstream tunnel section Calculate the predicted merging ratio ; Based on the predicted merging ratio Calculate the predicted mass flow rate of the connecting tunnel section ; Combined with the predicted mass flow rate of the downstream tunnel section The predicted mass flow rate of the connecting tunnel section Calculate the predicted mass flow rate of the upstream tunnel section. ; pass The symbol indicates whether the target scheme causes the airflow to reverse in the upstream tunnel section.

[0013] In conjunction with the first aspect, this embodiment of the invention provides a seventh possible implementation of the first aspect, wherein, in step S5, the updated value of the fan pressure and the flow resistance of each tunnel are input into the evaluation and prediction model to obtain the predicted mass flow rate of the downstream tunnel section. The content includes: Mass flow rate of downstream tunnel section obtained by numerical iteration method ; The process of the numerical iteration method is as follows: Based on the currently measured mass flow rate of the downstream tunnel section As the initial iteration value Initiate iterative calculation; Based on the downstream tunnel section mass flow rate obtained at iteration number k Calculate the square of the corresponding merging ratio ; Combination and Calculate the residual of the current solution's deviation from the pressure balance equation. ; If the absolute value of the residual If the value is less than the preset tolerance, the iteration is considered converged, and the current value is taken. As the final predicted value This continues until the convergence condition is met.

[0014] Secondly, embodiments of the present invention also provide an intelligent ventilation control system for underground interchange projects, used to execute the intelligent ventilation control method for underground interchange projects described in any of the above claims, the system comprising: The sensing and monitoring module is used to collect the ventilation velocity of the upstream tunnel section, downstream tunnel section and connecting tunnel section in real time; The fan status monitoring module is used to acquire the input voltage and speed parameters of the jet fan in real time. The central control and processing module is used to generate control commands for the jet fan and transmit the commands to the execution module. The execution module is used to execute the fan control commands transmitted from the central control and processing module, and control the frequency converter to adjust the frequency of the jet fan, including the jet fan and the frequency converter.

[0015] The embodiments of the present invention bring the following beneficial effects: By constructing a basic model of the ventilation network and dividing it into tunnel sections, and combining flow velocity calculation and confluence ratio analysis to determine the airflow direction, the system can accurately control the airflow state of the complex ventilation network in underground interchange projects. This solves the problem of airflow turbulence caused by the failure of existing technologies to consider the airflow coupling between different tunnel sections.

[0016] A rule base for control schemes is built based on historical data. Target wind turbine control schemes are selected through evaluation and prediction models. Then, the model parameters are optimized by combining the actual confluence ratio feedback, forming a closed-loop intelligent control mechanism of "sensing-prediction-control-feedback" to achieve on-demand airflow adjustment and reduce energy consumption and operating costs.

[0017] It dynamically adapts to the complex working conditions of underground interchange projects, breaking through the limitations of preset schemes that only cover a limited number of typical working conditions. It also has self-correction capabilities, which can cope with changes in working conditions during long-term operation and improve the stability and reliability of ventilation control.

[0018] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1A flowchart of an intelligent ventilation control method for underground interchange projects provided by an embodiment of the present invention; Figure 2 This is a flowchart of the flow distribution prediction process in an intelligent ventilation control method according to an embodiment of the present invention; Figure 3 This is a schematic diagram of airflow and traffic direction in a certain type of underground interchange project provided by an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] This invention provides an intelligent ventilation control method and system for underground interchange projects.

[0024] To facilitate understanding of this embodiment, a detailed description of an intelligent ventilation control method for underground interchange engineering disclosed in this invention will be provided first, such as... Figure 1 As shown, the method includes: S1. Construct a basic model of the ventilation network for the underground interchange project; Specifically, the basic model of the ventilation network in the underground interchange project in S1 is used to provide the underlying framework support for the establishment of the subsequent dynamic prediction model of the ventilation network.

[0025] The basic model of the ventilation network in S1 includes the following three parts: One is the geometric model, which is based on the physical structure of real underground infrastructure. An abstract three-dimensional geometric model is established in the system. This model defines the length, cross-sectional area, hydraulic diameter of all tunnel sections, as well as the location of the jet fans and the airflow direction in each tunnel section.

[0026] Secondly, the model adheres strictly to the laws of physical conservation, including the laws of conservation of mass and energy: The law of conservation of mass states that at the confluence point, the total mass flow rate of the inflow and outflow is equal, i.e., it satisfies... = + The law of conservation of energy states that in any ventilation loop, the total pressure increase provided by all jet fans is equal to the total resistance loss caused by the airflow in all tunnel sections.

[0027] Thirdly, parameter settings are crucial. To achieve quantitative calculations for this model, key parameters need to be pre-established and initialized in the system: flow resistance consists of tunnel frictional resistance and local resistance, and its values ​​must be determined in conjunction with the actual engineering parameters of each tunnel section of the underground interchange project (such as tunnel length, hydraulic diameter, cross-sectional area, local loss coefficient, tunnel friction coefficient, etc.). The tunnel friction coefficient is selected appropriately based on the tunnel type (straight or curved) and actual engineering conditions. Simultaneously, a performance model for the jet fan is set within the system to enable control of the jet fan. The performance model of the jet fan is established using formulas... Establish.

[0028] Where L is the tunnel length (m); The hydraulic diameter of the tunnel (m); The coefficient for local loss is denoted by F; F is the thrust of the jet fan. and These are the outlet area (m2) and outlet velocity (m / s) of the jet fan, respectively; n represents the number of jet fans in a group; It is a coefficient.

[0029] S2, such as Figure 3 As shown, based on the basic model of the ventilation network, the underground interchange is divided into upstream tunnel sections, downstream tunnel sections, and connecting tunnel sections; and the ventilation velocity corresponding to each tunnel section is obtained. Specifically, S2 includes the following: After the basic ventilation network model is completed, the next step is real-time monitoring. Through sensor monitoring modules deployed at key sections of each tunnel segment, the ventilation velocity of the upstream, downstream, and connecting tunnel segments is collected in real time. Through the fan status monitoring module, the input voltage, current, and speed parameters of each jet fan unit are acquired in real time. This step provides the system with detailed and accurate parameters.

[0030] S3. Calculate the first confluence ratio based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and determine the airflow direction of each tunnel section based on the first confluence ratio; The merging point is where the upstream tunnel section, the downstream tunnel section, and the connecting tunnel section meet.

[0031] S4. Construct a control scheme rule base based on historical control data, and select at least one fan control scheme from the control scheme rule base based on the airflow direction index principle of the tunnel section. S5. Based on the ventilation network basic model established in S1, construct an evaluation and prediction model, input the at least one fan control scheme into the evaluation and prediction model to generate the combined flow ratio prediction value and mass flow prediction value corresponding to each fan control scheme in the at least one fan control scheme, so as to select the target fan control scheme. S6. Obtain the second confluence ratio, which is the actual value of the confluence ratio when the target fan control scheme is executed. Compare the second confluence ratio with the predicted value of the confluence ratio corresponding to the target fan control scheme to obtain the comparison result. Based on the comparison result, determine whether the adjustable parameters in the ventilation network basic model need to be adjusted.

[0032] If the difference between the second confluence ratio and the predicted confluence ratio corresponding to the target fan control scheme is less than the preset value, then there is no need to adjust the adjustable parameters in the basic ventilation network model. If the difference between the second merging ratio and the predicted merging ratio corresponding to the target fan control scheme is greater than the preset value, then the adjustable parameters in the basic ventilation network model are adjusted. In this embodiment, by constructing a basic model of the ventilation network and dividing the tunnel into sections, and combining flow velocity calculation and confluence ratio analysis to determine the airflow direction, the airflow state of the complex ventilation network of the underground interchange project can be accurately controlled, solving the problem of airflow turbulence caused by the failure of the existing technology to consider the airflow coupling of each tunnel section.

[0033] In this embodiment, a rule base for control schemes is built based on historical data. The target wind turbine control scheme is selected by evaluating and predicting the model. Then, the model parameters are optimized by combining the actual confluence ratio feedback, forming a closed-loop intelligent control mechanism of "sensing-prediction-control-feedback" to realize on-demand air volume adjustment and reduce energy consumption and operating costs.

[0034] This embodiment dynamically adapts to the complex working conditions of underground interchange projects, overcoming the limitation of the preset scheme that only covers a limited number of typical working conditions. It also has self-correction capabilities, which can cope with changes in working conditions during long-term operation and improve the stability and reliability of ventilation control.

[0035] In conjunction with the first aspect, the present invention provides a first possible implementation of the first aspect, wherein, in step S3, the first confluence ratio is calculated based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and the airflow direction of each tunnel section is determined based on the first confluence ratio. The calculation of the first confluence ratio is as follows: ; in, —The merging ratio corresponding to the downstream tunnel section and the connecting tunnel section; M—mass flow rate of ventilation flow; down—the downstream tunnel section; con — connects to the tunnel section; —Cross-sectional area of ​​the tunnel section; —Density of the ventilation flow; v con—Ventilation velocity connecting the tunnel section; v down —Ventilation velocity in the downstream tunnel section.

[0036] In this embodiment, key parameters such as mass flow rate, tunnel cross-sectional area, airflow density, and ventilation velocity are used to derive a quantitative basis for the accurate calculation of the confluence ratio, avoiding the subjectivity and error in the estimation of the confluence ratio, ensuring the accuracy of subsequent airflow direction determination, and laying a data foundation for the rational formulation of fan control schemes.

[0037] In conjunction with the first aspect, this embodiment of the invention provides a second possible implementation of the first aspect, wherein, in step S3, the first merging ratio is calculated based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and the airflow direction of each tunnel section is determined based on the first merging ratio, the airflow direction of the tunnel section is determined as follows: Define the positive direction for each tunnel segment; The airflow direction of the tunnel section is determined based on the first confluence ratio.

[0038] In this embodiment, a clear logical framework for determining airflow direction is established through a two-step method of "defining the positive direction of the tunnel section + judging based on the first confluence ratio". This standardizes and makes the airflow direction determination process more operable, solving the problem of difficulty in accurately determining airflow direction in complex interconnected tunnel networks and providing clear guidance for subsequent targeted selection of fan control schemes.

[0039] In conjunction with the first aspect, this embodiment of the invention provides a third possible implementation of the first aspect, wherein the step of defining the positive direction of each tunnel segment includes the following: The positive direction of the downstream tunnel section is from the confluence point to the exit of the downstream tunnel section; The positive direction of the upstream tunnel section is the direction from the entrance of the upstream tunnel section to the confluence point; The positive direction of the connecting tunnel section is the direction from the entrance of the connecting tunnel section to the merging point.

[0040] Because the airflows converge at the confluence point, in all cases, the downstream tunnel section M... down The mass flow rate will be greater than 0.

[0041] In this embodiment, the definition standards of the positive direction are clarified for the functional characteristics and positional relationship of the upstream, downstream and connecting tunnel sections, and the benchmark for determining the airflow direction is unified. This avoids confusion caused by the ambiguity of the positive direction definition, ensures the consistency and accuracy of the airflow direction determination in different tunnel sections, and provides a unified premise for the correlation analysis of the confluence ratio and airflow direction.

[0042] In conjunction with the first aspect, this embodiment of the invention provides a fourth possible implementation of the first aspect, wherein the step of determining the airflow direction of the tunnel section based on the first confluence ratio in S3 is as follows: When 0 < When the airflow is less than 1, the airflow direction in all tunnel sections is positive. when When the value is greater than 1, the airflow direction in the upstream tunnel section is reversed; when When the airflow is less than 0, the airflow direction in the connecting tunnel section is reversed.

[0043] The determination method is as follows: (1) When 0 < When the value is less than 1, it indicates that the airflow direction of both the connecting tunnel section and the upstream tunnel section is consistent with the specified positive direction, and the system is in normal operation. At this time, the downstream mass flow rate is... upstream mass flow Mass flow rate of connecting tunnels The sum of these satisfy the law of conservation of mass. (2) When >1: Indicates the mass flow rate of the connecting tunnel section. It is already greater than the mass flow rate of the downstream tunnel section. ,Right now > >0, which does not conform to the mass conservation principle under forward airflow conditions. = + Therefore, the mass flow rate of the upstream tunnel section can be derived. It must be a negative value (i.e.) <0), at this time, = - .therefore, >1 is a necessary and sufficient condition for airflow to reverse in the upstream tunnel section.

[0044] (3) When <0: Due to downstream mass flow The condition that the mass flow rate is always positive directly indicates the mass flow rate of the connecting tunnel section. It is a negative value. Therefore, <0 indicates that the airflow reverses within the connecting tunnel section itself.

[0045] In this embodiment, by quantifying the correspondence between the numerical range of the first confluence ratio and the airflow direction, a clear determination rule is given (0 < <1、 >1. <0 corresponds to different airflow directions, making the airflow direction determination results intuitive and quantifiable, eliminating the need to rely on experience-based judgment, improving the objectivity and reliability of the determination results, and providing a direct basis for quickly selecting suitable fan control solutions.

[0046] In conjunction with the first aspect, this embodiment of the invention provides a fifth possible implementation of the first aspect, wherein, in S5, an evaluation and prediction model is constructed based on the ventilation network basic model established in S1, and the at least one fan control scheme is input into the evaluation and prediction model to generate the predicted value of the confluence ratio and the predicted value of the mass flow rate corresponding to each of the at least one fan control scheme, such as... Figure 2 As shown, in the steps of selecting a target wind turbine control scheme, the formula for constructing the evaluation and prediction model is as follows: The physical basis of this evaluation and prediction model is the law of conservation of energy in the ventilation network, which is specifically expressed as a set of pressure balance equations: ; ; Where R is the flow resistance of the tunnel cross section ( ); p is the pressure rise value (Pa) of the jet fan.

[0047] ; To solve the above set of equations, it is necessary to determine the pressure rise (p) of each fan, the tunnel resistance (R), and the mass flow rate (M).

[0048] Therefore, the merging ratio is introduced. .

[0049] The core equations used for prediction calculations can be obtained as follows: ; in Defined as: ; The minus sign does not represent a negative value, but rather the direction of the ventilation airflow.

[0050] Further, the squared value of the predicted merging ratio is obtained. : ; in, —Predicted merging ratio; —Pressure rise value of the jet fan in the downstream tunnel section; —Pressure rise value of the jet fan connecting the tunnel section; —Predicted mass flow rate of downstream tunnel section; —Tunnel flow resistance in the downstream tunnel section; —Tunnel flow resistance connecting tunnel sections.

[0051] The specific process of generating at least one wind turbine control scheme in S5 is as follows: Assuming the merging ratio obtained in S3 >1. According to criterion S5, the airflow in the upstream tunnel section reverses at this point. The control algorithm in the central control and processing module activates its preset rule base, which contains a series of "IF-THEN" logic statements. Based on this, the algorithm generates a specific thrust adjustment scheme A. Simultaneously, to find a better or alternative solution, the algorithm applies other rules in parallel, thereby generating scheme B, and even a comprehensive scheme C.

[0052] In this embodiment, by constructing an evaluation and prediction model based on a ventilation network basic model, key parameters such as the predicted values ​​of fan pressure rise, flow resistance, and mass flow rate in the downstream and connecting tunnel sections are integrated to establish a quantitative calculation method for the predicted value of the confluence ratio, thereby achieving accurate prediction of the effect of the fan control scheme and providing a scientific and quantitative evaluation standard for selecting the optimal target scheme from multiple candidate schemes.

[0053] In conjunction with the first aspect, this embodiment of the invention provides a sixth possible implementation of the first aspect, wherein, in step S5, an evaluation and prediction model is constructed based on the ventilation network basic model established in S1, and the at least one fan control scheme is input into the evaluation and prediction model to generate a combined flow ratio prediction value and a mass flow prediction value corresponding to each of the at least one fan control scheme, in order to select a target fan control scheme, the content of generating the corresponding combined flow ratio prediction value and mass flow prediction value is as follows: Generate corresponding updated fan pressure values ​​based on at least one fan control scheme described in S4; The updated wind turbine pressure value and the flow resistance of each tunnel are input into the evaluation and prediction model, and the predicted mass flow rate of the downstream tunnel section is output. ; Based on the predicted mass flow rate of the downstream tunnel section Calculate the predicted merging ratio ; Based on the predicted merging ratio Calculate the predicted mass flow rate of the connecting tunnel section ; Combined with the predicted mass flow rate of the downstream tunnel section The predicted mass flow rate of the connecting tunnel section Calculate the predicted mass flow rate of the upstream tunnel section. ; pass The symbol indicates whether the target scheme causes the airflow to reverse in the upstream tunnel section.

[0054] Specifically, the generation of the corresponding merging ratio prediction value and mass flow rate prediction value includes: Based on the evaluation and prediction model, simulation calculations and effect assessments were performed on each scheme generated by S4; the predicted merging ratio was obtained through numerical calculations. and predicted flow distribution ( , , ).

[0055] Next, the system evaluates the prediction results. First, it eliminates all schemes that would cause airflow reversal in any tunnel section. Then, it calculates and compares the performance indicators (such as ventilation efficiency) of the remaining schemes. Finally, it selects the best overall fan control scheme.

[0056] The selected optimal fan control scheme is converted into specific fan control commands. The system transmits the detailed control commands to the variable frequency drive in the execution module. After receiving the commands, the variable frequency drive precisely adjusts the frequency of the jet fan, thereby adjusting the fan's outlet speed and ultimately changing the fan's thrust, achieving precise control of the airflow distribution within the underground interchange project.

[0057] After the control command is executed, the system continues to collect new ventilation velocities and calculate the merging ratio through the sensor monitoring module, comparing the measured and predicted values ​​of the merging ratio. If a significant deviation is found between the measured and predicted values ​​of the merging ratio, it indicates a problem with the set prediction model parameters. At this time, the system will automatically execute the prediction model calibration procedure, adjusting key parameters in the prediction model (such as the flow resistance of each tunnel section) through appropriate mathematical optimization methods, so that the model's prediction results match the measured results more closely, thereby ensuring the accuracy of the system's predictions.

[0058] First, the system generates a set of fan pressure change parameters based on the contents of each scheme in S4: for fans that are clearly to be adjusted in the scheme, the updated fan pressure value is used; for fans not mentioned in the scheme, the current real-time monitoring value is used.

[0059] Based on these fan parameters and the inherent flow resistance of the tunnel ( , Calculate the squared value of the predicted merging ratio. .

[0060] Finally, based on the predicted mass flow rate of the downstream tunnel section... Calculate the predicted merging ratio According to the definition of merging ratio The predicted mass flow rate of the connecting tunnel section was calculated. .

[0061] Then, based on the law of conservation of mass = + The predicted mass flow rate of the upstream tunnel section was calculated. .

[0062] Here, the system will verify The sign of the variable is used; if it is negative, it indicates that the proposed solution will cause the airflow in the upstream tunnel section to reverse. Thus, through this series of rigorous calculations, the system achieves accurate quantitative prediction of the consequences of implementing any proposed solution, providing a reliable basis for subsequent decision-making.

[0063] In this embodiment, by refining the application process of the evaluation and prediction model, clarifying the input of the fan pressure update value, the calculation logic of the mass flow prediction value of each tunnel section, and the airflow reversal judgment method, a complete prediction and analysis chain is formed to ensure that the prediction results are comprehensive and detailed, and can accurately assess the impact of the control scheme on the airflow state of each tunnel section.

[0064] By determining whether the airflow is reversed by using the sign of the predicted mass flow rate value of the upstream tunnel section, the risk of airflow turbulence caused by improper control schemes can be avoided in advance, thereby improving the safety and rationality of ventilation control and solving the drawbacks of existing control schemes that may cause unknown airflow problems.

[0065] In conjunction with the first aspect, this embodiment of the invention provides a seventh possible implementation of the first aspect, wherein, in step S5, the updated value of the fan pressure and the flow resistance of each tunnel are input into the evaluation and prediction model to obtain the predicted mass flow rate of the downstream tunnel section. The content includes: In the new equilibrium state It is also an unknown quantity to be determined, constructing a concept about The system employs a nonlinear equation. To solve this equation, a numerical iteration method is required.

[0066] Mass flow rate of downstream tunnel section obtained by numerical iteration method ; The process of the numerical iteration method is as follows: Based on the currently measured mass flow rate of the downstream tunnel section As the initial iteration value Initiate iterative calculation; Based on the downstream tunnel section mass flow rate obtained at iteration number k Calculate the square of the corresponding merging ratio ; Combination and Calculate the residual of the current solution's deviation from the pressure balance equation. ; If the absolute value of the residual If the value is less than the preset tolerance, the iteration is considered converged, and the current value is taken. As the final predicted value This continues until the convergence condition is met.

[0067] If convergence is not achieved, the algorithm will then rely on the residuals. A new estimate is automatically calculated. Repeat the above calculation steps until the convergence condition is met.

[0068] In this embodiment, a numerical iterative method is used to obtain the predicted mass flow rate of the downstream tunnel section. Through the process of setting initial iteration values, calculating residuals, and determining convergence, the accuracy of the predicted values ​​is ensured to meet the preset requirements, avoiding excessive errors caused by direct calculation. At the same time, the iterative process has a clear termination condition (the absolute value of the residual is less than the preset tolerance), making the calculation process controllable and the results reliable, providing high-precision data support for merging ratio prediction and subsequent scheme selection.

[0069] Secondly, embodiments of the present invention also provide an intelligent ventilation control system for underground interchange projects, used to execute the intelligent ventilation control method for underground interchange projects described in any of the above claims, the system comprising: The sensing and monitoring module is used to collect the ventilation velocity of the upstream tunnel section, downstream tunnel section and connecting tunnel section in real time; The fan status monitoring module is used to acquire the input voltage and speed parameters of the jet fan in real time. The central control and processing module is used to generate control commands for the jet fan and transmit the commands to the execution module. The execution module is used to execute the fan control commands transmitted from the central control and processing module, and control the frequency converter to adjust the frequency of the jet fan, including the jet fan and the frequency converter.

[0070] In this embodiment, the sensor monitoring module collects ventilation flow rate data in real time, and the fan status monitoring module acquires key fan parameters, providing a real-time and accurate data source for ventilation status analysis and control scheme formulation, ensuring the timeliness and pertinence of control decisions.

[0071] The central control and processing module coordinates data processing, scheme generation, and instruction issuance, while the execution module precisely implements control instructions. Through the coordinated operation of these modules, the ventilation control is automated and intelligent, eliminating the need for manual intervention, improving control efficiency, avoiding human error, ensuring the accurate implementation of control schemes, and effectively supporting the efficient execution of the aforementioned intelligent ventilation control methods.

[0072] The device provided in this application embodiment has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0073] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0074] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0075] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0076] The aforementioned computer-readable storage medium may be any combination of one or more computer-readable media. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or flash memory, optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium that contains or stores a program that may be used by or in connection with an instruction execution system, apparatus, or device.

[0077] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0078] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0079] Computer program code for performing the operations of the embodiments of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0080] The foregoing has described specific embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0081] In the description of the embodiments of this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments of this application. In the embodiments of this application, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in the embodiments of this application, as well as the features of different embodiments or examples.

[0082] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of embodiments of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0083] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order according to the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0084] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0085] It should be noted that the terminals involved in the embodiments of this application may include, but are not limited to, personal computers (PCs), personal digital assistants (PDAs), wireless handheld devices, tablet computers, mobile phones, MP3 players, MP4 players, etc.

[0086] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0087] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0088] The integrated units implemented as software functional units described above can be stored in a computer-readable storage medium. These software functional units, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute some steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0089] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present application should be included within the scope of protection of the present application.

Claims

1. A smart ventilation control method for underground interchange projects, characterized in that, include: S1. Construct a basic model of the ventilation network for the underground interchange project; S2. Based on the basic model of the ventilation network, the underground interchange is divided into upstream tunnel segment, downstream tunnel segment and connecting tunnel segment; and the ventilation velocity corresponding to each tunnel segment is obtained; S3. Calculate the first confluence ratio based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and determine the airflow direction of each tunnel section based on the first confluence ratio; S4. Construct a control scheme rule base based on historical control data, and select at least one fan control scheme from the control scheme rule base based on the airflow direction index principle of the tunnel section. S5. Based on the ventilation network basic model established in S1, construct an evaluation and prediction model, input the at least one fan control scheme into the evaluation and prediction model to generate the predicted value of the confluence ratio and the predicted value of the mass flow rate corresponding to the at least one fan control scheme, so as to select the target fan control scheme. S6. Obtain the second confluence ratio, which is the actual value of the confluence ratio when the target fan control scheme is executed. Compare the second confluence ratio with the predicted value of the confluence ratio corresponding to the target fan control scheme to obtain the comparison result. Based on the comparison result, determine whether the adjustable parameters in the ventilation network basic model need to be adjusted.

2. The intelligent ventilation control method for underground interchange projects according to claim 1, characterized in that, In step S3, the first confluence ratio is calculated based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and the airflow direction of each tunnel section is determined based on the first confluence ratio. The calculation of the first confluence ratio is as follows: ； in, —The merging ratio corresponding to the downstream tunnel section and the connecting tunnel section; M—mass flow rate of ventilation flow; down—the downstream tunnel section; con — connects to the tunnel section; —Cross-sectional area of ​​the tunnel section; —Density of the ventilation flow; v con —Ventilation velocity connecting the tunnel section; v down —Ventilation velocity in the downstream tunnel section.

3. The intelligent ventilation control method for underground interchange projects according to claim 2, characterized in that, In step S3, the first confluence ratio is calculated based on the ventilation velocity corresponding to the downstream tunnel section and the connecting tunnel section, and the airflow direction of each tunnel section is determined based on the first confluence ratio. The determination of the airflow direction of each tunnel section is as follows: Define the positive direction for each tunnel segment; The airflow direction of the tunnel section is determined based on the first confluence ratio.

4. The intelligent ventilation control method for underground interchange projects according to claim 3, characterized in that, The steps for defining the positive direction of each tunnel segment are as follows: The positive direction of the downstream tunnel section is from the confluence point to the exit of the downstream tunnel section; The positive direction of the upstream tunnel section is the direction from the entrance of the upstream tunnel section to the confluence point; The positive direction of the connecting tunnel section is the direction from the entrance of the connecting tunnel section to the merging point.

5. The intelligent ventilation control method for underground interchange projects according to claim 3, characterized in that, The step in S3, which determines the airflow direction of the tunnel section based on the first confluence ratio, includes the following: When 0 < When the airflow is less than 1, the airflow direction in all tunnel sections is positive. when When the value is greater than 1, the airflow direction in the upstream tunnel section is reversed; when When the airflow is less than 0, the airflow direction in the connecting tunnel section is reversed.

6. The intelligent ventilation control method for underground interchange projects according to claim 4, characterized in that, In step S5, an evaluation and prediction model is constructed based on the ventilation network basic model established in S1. The at least one fan control scheme is input into the evaluation and prediction model to generate the predicted confluence ratio and mass flow rate for each of the at least one fan control scheme. The formula for constructing the evaluation and prediction model in the step of selecting the target fan control scheme is as follows: ； in, —Predicted merging ratio; —Pressure rise value of the jet fan in the downstream tunnel section; —Pressure rise value of the jet fan connecting the tunnel section; —Predicted mass flow rate of downstream tunnel section; —Tunnel flow resistance in the downstream tunnel section; —Tunnel flow resistance connecting tunnel sections.

7. The intelligent ventilation control method for underground interchange projects according to claim 4, characterized in that, In step S5, an evaluation and prediction model is constructed based on the ventilation network basic model established in S1. The at least one fan control scheme is input into the evaluation and prediction model to generate the predicted confluence ratio and mass flow rate for each of the at least one fan control scheme. In the step of selecting a target fan control scheme, the generated predicted confluence ratio and mass flow rate are as follows: Generate corresponding updated fan pressure values ​​based on at least one fan control scheme described in S4; The updated wind turbine pressure value and the flow resistance of each tunnel are input into the evaluation and prediction model, and the predicted mass flow rate of the downstream tunnel section is output. ; Based on the predicted mass flow rate of the downstream tunnel section Calculate the predicted merging ratio ; Based on the predicted merging ratio Calculate the predicted mass flow rate of the connecting tunnel section ; Combined with the predicted mass flow rate of the downstream tunnel section The predicted mass flow rate of the connecting tunnel section Calculate the predicted mass flow rate of the upstream tunnel section. ; pass The symbol indicates whether the target scheme causes the airflow to reverse in the upstream tunnel section.

8. The intelligent ventilation control method for underground interchange projects according to claim 7, characterized in that, In step S5, the updated wind turbine pressure value and the flow resistance of each tunnel are input into the evaluation and prediction model to obtain the predicted mass flow rate of the downstream tunnel section. The content includes: Mass flow rate of downstream tunnel section obtained by numerical iteration method ; The process of the numerical iteration method is as follows: Based on the currently measured mass flow rate of the downstream tunnel section As the initial iteration value Initiate iterative calculation; Based on the downstream tunnel section mass flow rate obtained at iteration number k Calculate the square of the corresponding merging ratio ; Combination and Calculate the residual of the current solution's deviation from the pressure balance equation. ; If the absolute value of the residual If the value is less than the preset tolerance, the iteration is considered converged, and the current value is taken. As the final predicted value This continues until the convergence condition is met.

9. An intelligent ventilation control system for underground interchange projects, used to execute the intelligent ventilation control method for underground interchange projects according to any one of claims 1-8, characterized in that, The system includes: The sensing and monitoring module is used to collect the ventilation velocity of the upstream tunnel section, downstream tunnel section and connecting tunnel section in real time; The fan status monitoring module is used to acquire the input voltage and speed parameters of the jet fan in real time. The central control and processing module is used to generate control commands for the jet fan and transmit the commands to the execution module. The execution module is used to execute the fan control commands transmitted from the central control and processing module, and control the frequency converter to adjust the frequency of the jet fan, including the jet fan and the frequency converter.

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