Intelligent ventilation system in tunnel and control method thereof

Abstract

The present invention relates to an intelligent ventilation system in a tunnel and a control method thereof, and belongs to the technical field of tunnel ventilation. The intelligent ventilation system in a tunnel includes a data acquisition unit, a ventilation unit, a control unit, a data storage unit and a data analysis unit; wherein the data acquisition unit is installed in each detection section inside the tunnel, including a COVI detector, a wind speed and direction detector and a vehicle flow detection module; when the CO concentration and VI exceed the threshold, the ventilation unit is controlled to enter the corresponding working mode; the data analysis unit is used to generate an early warning model according to the data of the data storage unit, and the early warning model is used to obtain the CO concentration and VI data in the future time according to the wind speed and wind direction data, vehicle flow, vehicle type, fuel type data and CO concentration, VI changes. The ventilation system can intervene before the pollution concentration increases, effectively avoiding the period of insufficient ventilation, and ensuring that the tunnel always maintains good air quality.

Description

Technical Field

[0001] The present invention belongs to the technical field of tunnel ventilation, and in particular relates to an intelligent ventilation system in a tunnel and a control method thereof. Background Art

[0002] Vehicles passing through the tunnel emit exhaust gas. Since the tunnel is a semi-enclosed underground space, when the CO mass concentration is very high, it will endanger the human body; smoke and dust will deteriorate the field of vision and reduce the sight distance for safe driving of vehicles. In order to meet the requirements of pollutant concentration limits in the tunnel, ventilation system design has become an important consideration in tunnel engineering.

[0003] In the prior art, Chinese invention patent CN107288675B discloses a tunnel intelligent ventilation control method, which calculates the corresponding deviation and deviation change rate through the pollutant concentration, wind speed, and traffic volume parameters fed back by the on-site detector, and then adjusts the values ​​of the proportional coefficient Kp, integral action coefficient Ki, and differential action coefficient Kd according to the preset fuzzy control rules, obtains the control frequency of the frequency converter through PID operation, controls the variable frequency operation of the jet fan, quickly changes the ventilation environment in the speed regulator, cyclically feeds back the pollutant concentration and wind speed parameters, and continuously calculates and outputs the current control frequency to achieve ventilation on demand. However, this patent can only perform post-adjustment based on the data fed back by the on-site detector, and there will still be periods of insufficient ventilation in the tunnel.

[0004] Therefore, how to provide an intelligent ventilation system that can always maintain the air quality in the tunnel is a technical problem that urgently needs to be solved. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an intelligent ventilation system and a control method for a tunnel, which can intervene before the pollution concentration rises, effectively avoiding periods of insufficient ventilation and ensuring that good air quality is always maintained in the tunnel.

[0006] In one aspect, the present invention provides an intelligent ventilation system in a tunnel, comprising:

[0007] The data acquisition unit is installed in each detection section inside the tunnel, and includes a COVI detector, a wind speed and direction detector, and a vehicle flow detection module; wherein the COVI detector collects CO concentration and VI data in the tunnel; the wind speed and direction detector is used to collect wind speed and wind direction data in the tunnel; and the vehicle flow detection module is used to collect vehicle flow, vehicle type, and fuel type data in the tunnel;

[0008] The ventilation unit includes an axial flow fan arranged in the equipment room, a jet fan at the top of the tunnel and a roof fan at the top of the tunnel; wherein the axial flow fan is arranged in the equipment room, and the axial flow fan in each equipment room corresponds to adjusting one or more detection sections; the jet fan is distributed in each detection section of the entire tunnel, and the roof fan is arranged at the tunnel exit;

[0009] A control unit is respectively connected to the data acquisition unit and the ventilation unit for controlling the ventilation unit to enter a corresponding working mode when the CO concentration and the VI exceed a threshold value;

[0010] A data storage unit, which is communicatively connected to the data acquisition unit and is used to store all data acquired by the data acquisition unit;

[0011] The data analysis unit is connected to the data storage unit for generating an early warning model based on the data in the data storage unit. The early warning model is used to obtain future predictions based on wind speed and direction data, vehicle flow, vehicle type, fuel type data, and changes in CO concentration and VI. CO concentration and VI data over time.

[0012] This technical solution effectively avoids periods of insufficient ventilation by intervening before pollution concentrations rise, ensuring that good air quality is always maintained in the tunnel.

[0013] In some embodiments, the data analysis unit is further used to calculate the average speed of vehicles in the tunnel; time Calculate according to formula (1), the expression of formula (1) is:

[0014] (1);

[0015] In formula (1), is the tunnel length, is the average speed of vehicles in the tunnel; the average speed of vehicles in the tunnel Obtained through the Data Analysis Unit.

[0016] This technical solution can improve the accuracy of prediction by adjusting the prediction time through the average speed of vehicles passing through the tunnel.

[0017] In some embodiments, the intelligent ventilation system in the tunnel further includes an early warning unit, which is in communication with the data analysis unit. When the CO concentration and VI within a certain period of time exceed the threshold, the early warning unit will sound an alarm.

[0018] This technical solution can remind relevant personnel to take measures in advance to prevent the air quality in the tunnel from deteriorating by setting up an early warning unit.

[0019] In some embodiments, the control unit is also in communication with the data analysis unit. When the CO concentration and VI within a certain period of time exceed the threshold, the ventilation unit is controlled to start working in advance.

[0020] This technical solution can intervene before the pollution level rises by starting the ventilation mechanism in advance, ensuring that the air quality in the tunnel always remains within a safe range.

[0021] In some of the embodiments, the intelligent ventilation system in the tunnel also includes an automatic inspection unit, which is communicated with the early warning unit. The automatic inspection unit is used to establish a digital twin model of the intelligent ventilation system in the tunnel and perform automatic inspections on the equipment of the ventilation system. When the real-time operating status of the equipment is abnormal, the early warning unit issues an alarm.

[0022] This technical solution can detect and handle equipment failures in a timely manner through the setting of automatic inspection units, ensuring stable operation and efficient management of the system.

[0023] On the other hand, based on the above-mentioned intelligent ventilation system in a tunnel, the present invention further provides a control method for the intelligent ventilation system in a tunnel, which is applied to the above-mentioned intelligent ventilation system in a tunnel, and comprises the following steps:

[0024] Divide the detection sections: Divide the two lines and ramps of the tunnel into several detection sections, and set up COVI detectors in each detection section. At the same time, set up wind speed and direction detectors and vehicle flow detection modules in the tunnel according to the design plan;

[0025] Fan setting: Axial flow fans are arranged in the equipment room. The axial flow fans in each equipment room are corresponding to one or more detection sections. Jet fans are distributed in the detection sections of the entire tunnel, and roof fans are arranged at the tunnel exit.

[0026] Data collection: The COVI detector collects the CO concentration and VI in the tunnel in real time, and the wind speed and direction detector collects the wind speed and direction in the tunnel in real time; the vehicle flow detection module collects the vehicle flow, vehicle type, and fuel type in the tunnel in real time;

[0027] Data storage: Store CO concentration and VI, wind speed and direction, vehicle flow, vehicle type, and fuel type data in the database;

[0028] Data analysis: Generate early warning models based on wind speed and direction data, vehicle flow, vehicle model, fuel type data, and CO concentration and VI changes, and obtain future CO concentration and VI data over time;

[0029] Ventilation: When CO concentration and VI exceed the threshold, each fan is controlled to enter the corresponding working mode; When the CO concentration and VI data within a certain period of time exceed the threshold, each fan is controlled to start working in advance.

[0030] This technical solution can systematically divide the detection sections, scientifically arrange the fans, collect and store data in real time, and then conduct accurate analysis and prediction based on these data to achieve ventilation on demand.

[0031] In some of the embodiments, when the CO concentration and VI exceed the threshold value, the specific method of controlling each fan to enter the corresponding working mode is:

[0032] When the CO concentration detected by the COVI detector in a certain detection section exceeds 80ppm or the VI exceeds 5.2x10 -3 m -1 When the axial flow fan of the detection section is turned on, the axial flow fan of the detection section is controlled;

[0033] When the CO concentration in a detection section exceeds 90 ppm or the VI exceeds 5.85 x10 -3 m -1 When the detection section is under test, the axial flow fan and jet fan of the detection section shall be controlled to be turned on; for the detection section with roof fan, the roof fan of the detection section shall be turned on at the same time.

[0034] This technical solution achieves accurate response to different pollution levels and ensures the air quality in the tunnel.

[0035] In some of these embodiments, when the future When the CO concentration and VI data within a certain period of time exceed the threshold, the method of controlling each fan to start working in advance includes:

[0036] When a detection section is in the future The CO concentration exceeds 80ppm or the VI exceeds 5.2x10 -3 m -1 When the alarm is sounded, the axial flow fan in the detection section is controlled to be turned on in advance;

[0037] When a detection section is in the future The CO concentration exceeds 90 ppm or the VI exceeds 5.85 x10 -3 m -1 When the detection section is in danger, an alarm is sounded and the axial flow fan and jet fan of the detection section are turned on in advance. For the detection section with roof fans, the roof fans of the detection section should be turned on in advance at the same time.

[0038] This technical solution can intervene before the pollution level rises, ensuring the continuity of air quality and driving safety in the tunnel.

[0039] In some of the embodiments, the control method of the intelligent ventilation system in the tunnel also includes an automatic inspection step, which includes: establishing a digital twin model of the intelligent ventilation system in the tunnel, performing automatic inspections on the equipment of the ventilation system, and when the real-time operating status of the equipment is abnormal, issuing an alarm to notify the operation and maintenance personnel to enter the site for maintenance.

[0040] This technical solution establishes a digital twin model of the intelligent ventilation system in the tunnel. When the equipment operating status is abnormal, an alarm is promptly issued and the operation and maintenance personnel are notified to carry out maintenance, which effectively improves the maintenance efficiency and reliability of the system.

[0041] In some embodiments, the future The alarm when the CO concentration and VI data within a certain period exceed the threshold value is different from the alarm when the real-time operating status of the equipment is abnormal. The alarm is classified by the C4.5 decision tree algorithm before it is issued.

[0042] This technical solution can more accurately identify and handle different types of abnormal situations, ensuring the accuracy and efficiency of system response.

[0043] Based on the above scheme, the intelligent ventilation system in the tunnel in the embodiment of the present invention monitors the CO concentration, VI (visibility) data, wind speed, wind direction, traffic flow and other data in the tunnel in real time through the data acquisition unit, which can timely reflect the air quality and traffic conditions in the tunnel. When it is detected that the pollutant concentration exceeds the threshold, the control unit quickly starts the ventilation unit to effectively improve the air quality; the data analysis unit uses the stored data to generate an early warning model to predict the CO concentration and VI data in the future T time. If the predicted value exceeds the threshold, the system can start the ventilation unit in advance, so as to intervene before the pollution concentration increases, effectively avoiding the period of insufficient ventilation and ensuring that the tunnel always maintains good air quality. The intelligent ventilation system significantly improves the level of air quality management in the tunnel by comprehensively applying technical means such as real-time monitoring, prediction and early warning, multiple ventilation means and intelligent control, and provides an efficient, reliable and energy-saving solution with important application value and promotion prospects. The control method of the intelligent ventilation system in the tunnel can systematically divide the detection section, scientifically arrange the fan, collect and store data in real time, and then accurately analyze and predict based on these data to achieve ventilation on demand. This method effectively ensures the continuous improvement of the air quality in the tunnel. Not only can ventilation measures be taken in a timely manner when the pollutant concentration exceeds the threshold, but ventilation equipment can also be started in advance when it is predicted that the pollutant concentration will exceed the standard in the future, thereby maximizing the air quality and driving safety in the tunnel, while improving the efficiency and energy-saving effects of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0045] Figure 1 It is a structural block diagram of an intelligent ventilation system in a tunnel according to an embodiment of the present invention;

[0046] Figure 2 The figure is a flow chart of a method for controlling an intelligent ventilation system in a tunnel according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0048] In the description of the present invention, it should be understood that the terms "center", "lateral", "longitudinal", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0049] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0050] like Figure 1As shown, in one embodiment of the intelligent ventilation system in a tunnel and the control method thereof of the present invention, the intelligent ventilation system in the tunnel includes a data acquisition unit, a ventilation unit, a control unit, a data storage unit and a data analysis unit; wherein the data acquisition unit is installed in each detection section inside the tunnel, including a COVI detector, a wind speed and direction detector and a vehicle flow detection module; wherein the COVI detector collects CO concentration and VI data in the tunnel; the wind speed and direction detector is used to collect wind speed and wind direction data in the tunnel; the vehicle flow detection module is used to collect vehicle flow, vehicle type, and fuel type data in the tunnel; the ventilation unit includes an axial flow fan arranged in the equipment room, a jet fan at the top of the tunnel and a roof fan at the top of the tunnel; wherein The axial flow fans are arranged in the equipment room, and the axial flow fans in each equipment room are corresponding to one or more detection sections; the jet fans are distributed in the detection sections of the whole tunnel, and the roof fans are arranged at the tunnel exit; the control unit is communicated with the data acquisition unit and the ventilation unit respectively, and when the CO concentration and VI exceed the threshold value, the ventilation unit is controlled to enter the corresponding working mode; the data storage unit is communicated with the data acquisition unit for storing all the data obtained by the data acquisition unit; the data analysis unit is communicated with the data storage unit for generating an early warning model according to the data of the data storage unit, and the early warning model is used to obtain the future according to the wind speed and direction data, the traffic volume, the vehicle type, the fuel type data and the CO concentration and VI changes. CO concentration and VI data over time.

[0051] In the above-mentioned exemplary embodiment, the intelligent ventilation system in the tunnel monitors the CO concentration, VI (visibility) data, wind speed, wind direction, traffic flow and other data in the tunnel in real time through the data acquisition unit, which can timely reflect the air quality and traffic conditions in the tunnel. When it is detected that the pollutant concentration exceeds the threshold, the control unit quickly starts the ventilation unit to effectively improve the air quality; the data analysis unit uses the stored data to generate an early warning model to predict the CO concentration and VI data in the future T time. If the predicted value exceeds the threshold, the system can start the ventilation unit in advance, so as to intervene before the pollution concentration increases, effectively avoiding the period of insufficient ventilation and ensuring that the tunnel always maintains good air quality. The intelligent ventilation system significantly improves the level of air quality management in the tunnel through the comprehensive application of real-time monitoring, prediction and early warning, multiple ventilation means and intelligent control and other technical means, providing an efficient, reliable and energy-saving solution with important application value and promotion prospects.

[0052] In some embodiments, the data analysis unit is further used to calculate the average speed of vehicles in the tunnel; time According to formula (1), the expression of formula (1) is:

[0053] (1);

[0054] In formula (1), is the tunnel length, is the average speed of vehicles in the tunnel; the average speed of vehicles in the tunnel Obtained through the Data Analysis Unit.

[0055] In the above exemplary embodiment, by adjusting the prediction time by the average speed of vehicles passing through the tunnel, the accuracy of the prediction can be improved, further ensuring that the air quality in the tunnel is always kept within a safe range.

[0056] In some embodiments, Figure 1 As shown, the intelligent ventilation system in the tunnel also includes an early warning unit, which is connected to the data analysis unit in communication. When the CO concentration and VI exceed the threshold within a certain period of time, the early warning unit will sound an alarm. Through the setting of the early warning unit, relevant personnel can be reminded in advance to take measures to prevent the deterioration of air quality in the tunnel and ensure driving safety and personnel health.

[0057] In some embodiments, the control unit is also in communication with the data analysis unit. When the CO concentration and VI exceed the threshold within a certain period of time, the ventilation unit is controlled to start working in advance. By starting the ventilation mechanism in advance, it is possible to intervene before the pollution level rises, ensuring that the air quality in the tunnel is always kept within a safe range.

[0058] In some embodiments, Figure 1 As shown, the intelligent ventilation system in the tunnel also includes an automatic inspection unit, which is connected to the early warning unit in communication. The automatic inspection unit is used to establish a digital twin model of the intelligent ventilation system in the tunnel and automatically inspect the equipment of the ventilation system. When the real-time operating status of the equipment is abnormal, the early warning unit will sound an alarm. Through the setting of the automatic inspection unit, equipment failures can be discovered and handled in a timely manner to ensure stable operation and efficient management of the system.

[0059] Based on the above-mentioned intelligent ventilation system in the tunnel, Figure 2As shown, the present invention also provides a control method for an intelligent ventilation system in a tunnel, which is applied to the above-mentioned intelligent ventilation system in a tunnel, including the steps of dividing detection sections, fan setting, data acquisition, data storage, data analysis and ventilation; wherein the step of dividing the detection sections includes dividing the two lines and ramps of the tunnel into a number of detection sections, and setting a COVI detector in each detection section, and at the same time setting a wind speed and direction detector and a vehicle flow detection module in the tunnel according to the design scheme; the fan setting step includes configuring an axial flow fan in an equipment room, and the axial flow fan in each equipment room corresponds to adjusting one or more detection sections; dividing the jet fan into The detection sections of the entire tunnel are arranged, and the roof fan is set at the tunnel exit; the data collection step includes the COVI detector collecting the CO concentration and VI in the tunnel in real time, and the wind speed and direction detector collecting the wind speed and direction in the tunnel in real time; the vehicle flow detection module collects the vehicle flow, vehicle model, and fuel type in the tunnel in real time; the data storage step includes storing the CO concentration and VI, wind speed and wind direction, and vehicle flow, vehicle model, and fuel type data in the database; the data analysis step includes generating an early warning model based on the wind speed and wind direction data, vehicle flow, vehicle model, fuel type data, and CO concentration and VI changes, and obtaining future The CO concentration and VI data within a certain period of time; the ventilation steps include controlling each fan to enter the corresponding working mode when the CO concentration and VI exceed the threshold; When the CO concentration and VI data within a certain period of time exceed the threshold, each fan is controlled to start working in advance.

[0060] In the above exemplary embodiment, the control method of the intelligent ventilation system in the tunnel can systematically divide the detection section, scientifically arrange the fans, collect and store data in real time, and then accurately analyze and predict based on these data to achieve ventilation on demand. This method effectively ensures the continuous improvement of the air quality in the tunnel. It can not only take ventilation measures in time when the pollutant concentration exceeds the threshold, but also start the ventilation equipment in advance when it is predicted that the pollutant concentration will exceed the standard in the future, thereby maximizing the air quality and driving safety in the tunnel, while improving the efficiency and energy saving effect of the system.

[0061] In some embodiments, when the CO concentration and VI exceed the threshold, the specific method of controlling each fan to enter the corresponding working mode is as follows: when the CO concentration detected by the COVI detector in a certain detection section in real time exceeds 80ppm or the VI exceeds 5.2x10 -3 m -1 When the CO concentration in a detection section exceeds 90 ppm or the VI exceeds 5.85x10 -3 m -1When the CO concentration or VI concentration in the detection section exceeds the corresponding threshold, each fan is automatically controlled to enter the corresponding working mode. This method achieves accurate response to different pollution levels and ensures the air quality in the tunnel.

[0062] In some embodiments, when the future When the CO concentration and VI data within a certain period of time exceed the threshold, the method of controlling each fan to start working in advance includes: The CO concentration exceeds 80ppm or the VI exceeds 5.2x10 -3 m -1 When a detection section is in the future, an alarm is sounded and the axial flow fan of the detection section is controlled to be turned on in advance; The CO concentration exceeds 90 ppm or the VI exceeds 5.85 x10 -3 m -1 When the CO concentration or VI concentration is predicted to exceed the threshold within T time in the future, the relevant fans are started in advance. This preventive measure can intervene before the pollution level rises, ensuring the continuity of air quality and driving safety in the tunnel.

[0063] In some embodiments, Figure 2 As shown, the control method of the intelligent ventilation system in the tunnel also includes an automatic inspection step, which includes: establishing a digital twin model of the intelligent ventilation system in the tunnel, automatically inspecting the equipment of the ventilation system, and when the real-time operating status of the equipment is abnormal, an alarm is issued to notify the operation and maintenance personnel to enter the site for maintenance. By establishing a digital twin model of the intelligent ventilation system in the tunnel, the equipment of the ventilation system is automatically inspected; when the operating status of the equipment is abnormal, an alarm is issued in time to notify the operation and maintenance personnel to carry out maintenance, which effectively improves the maintenance efficiency and reliability of the system.

[0064] In some embodiments, the future The alarm when the CO concentration and VI data exceed the threshold within a certain time period is different from the alarm when the real-time operation status of the equipment is abnormal. The alarm is classified by the C4.5 decision tree algorithm before it is issued. By classifying the pollution concentration alarms and the abnormal alarms of the real-time operation status of the equipment within the future time period T through the C4.5 decision tree algorithm, different types of abnormal situations can be more accurately identified and handled, ensuring the accuracy and efficiency of the system response.

[0065] Through the description of multiple embodiments of the intelligent ventilation system in a tunnel and the control method thereof of the present invention, it can be seen that the intelligent ventilation system in a tunnel and the control method thereof of the present invention have at least one or more of the following advantages:

[0066] 1. The intelligent ventilation system in the tunnel provided by the present invention can monitor the CO concentration, VI (visibility) data, wind speed, wind direction, vehicle flow and other data in the tunnel in real time through the data acquisition unit, and can timely reflect the air quality and traffic conditions in the tunnel. When it is detected that the pollutant concentration exceeds the threshold, the control unit quickly starts the ventilation unit to effectively improve the air quality;

[0067] 2. The data analysis unit in the intelligent ventilation system in the tunnel provided by the present invention generates an early warning model using the stored data to predict the CO concentration and VI data in the future T time. If the predicted value exceeds the threshold, the system can start the ventilation unit in advance, thereby intervening before the pollution concentration increases, effectively avoiding the period of insufficient ventilation and ensuring that the air quality in the tunnel is always good;

[0068] 3. The intelligent ventilation system control method in the tunnel provided by the present invention can systematically divide the detection sections, scientifically arrange the fans, collect and store data in real time, and then perform accurate analysis and prediction based on the data to achieve ventilation on demand.

[0069] Finally, it should be noted that: the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0070] The above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or some technical features can be replaced by equivalents without departing from the spirit of the technical solution of the present invention, which should be included in the scope of the technical solution for protection of the present invention.

Claims

1. A method for controlling an intelligent ventilation system in a tunnel, characterized in that: Applied to the intelligent ventilation system in the tunnel, the intelligent ventilation system in the tunnel includes: The data acquisition unit is installed in each detection section inside the tunnel, and includes a COVI detector, a wind speed and direction detector, and a vehicle flow detection module; wherein the COVI detector collects CO concentration and VI data in the tunnel; the wind speed and direction detector is used to collect wind speed and wind direction data in the tunnel; and the vehicle flow detection module is used to collect vehicle flow, vehicle type, and fuel type data in the tunnel; The ventilation unit includes an axial flow fan arranged in the equipment room, a jet fan at the top of the tunnel and a roof fan at the top of the tunnel; wherein the axial flow fan is arranged in the equipment room, and the axial flow fan in each equipment room corresponds to adjusting one or more detection sections; the jet fan is distributed in each detection section of the entire tunnel, and the roof fan is arranged at the tunnel exit; A control unit is respectively connected to the data acquisition unit and the ventilation unit for controlling the ventilation unit to enter a corresponding working mode when the CO concentration and the VI exceed a threshold value; A data storage unit, which is communicatively connected to the data acquisition unit and is used to store all data acquired by the data acquisition unit; The data analysis unit is connected to the data storage unit for generating an early warning model based on the data in the data storage unit. The early warning model is used to obtain future predictions based on wind speed and direction data, vehicle flow, vehicle type, fuel type data, and changes in CO concentration and VI. The control unit is also connected to the data analysis unit for communication. When the CO concentration and VI exceed the threshold within a certain time, the ventilation unit is controlled to start working in advance; the data analysis unit is also used to calculate the average speed of vehicles in the tunnel; time According to formula (1), the expression of formula (1) is: （1）； In formula (1), is the tunnel length, is the average speed of vehicles in the tunnel; the average speed of vehicles in the tunnel Obtained through the Data Analysis Unit; The control method of the intelligent ventilation system in the tunnel includes the following steps: Divide the detection sections: Divide the two lines and ramps of the tunnel into several detection sections, and set up COVI detectors in each detection section. At the same time, set up wind speed and direction detectors and vehicle flow detection modules in the tunnel according to the design plan; Fan setting: Axial flow fans are arranged in the equipment room. The axial flow fans in each equipment room are corresponding to one or more detection sections. Jet fans are distributed in the detection sections of the entire tunnel, and roof fans are arranged at the tunnel exit. Data collection: The COVI detector collects the CO concentration and VI in the tunnel in real time, and the wind speed and direction detector collects the wind speed and direction in the tunnel in real time; the vehicle flow detection module collects the vehicle flow, vehicle type, and fuel type in the tunnel in real time; Data storage: Store CO concentration and VI, wind speed and direction, vehicle flow, vehicle type, and fuel type data in the database; Data analysis: Generate early warning models based on wind speed and direction data, vehicle flow, vehicle model, fuel type data, and CO concentration and VI changes, and obtain future CO concentration and VI data over time; Ventilation: When CO concentration and VI exceed the threshold, each fan is controlled to enter the corresponding working mode; When the CO concentration and VI data within a certain period exceed the threshold, each fan is controlled to start working in advance; when the future When the CO concentration and VI data within a certain period of time exceed the threshold, the method of controlling each fan to start working in advance includes: When a detection section is in the future The CO concentration exceeds 80ppm or the VI exceeds 5.2x10 -3 m -1 When the alarm is sounded, the axial flow fan in the detection section is controlled to be turned on in advance; When a detection section is in the future The CO concentration exceeds 90 ppm or the VI exceeds 5.85 x10 -3 m -1 When the detection section is in danger, an alarm is sounded and the axial flow fan and jet fan of the detection section are turned on in advance. For the detection section with roof fans, the roof fans of the detection section should be turned on in advance at the same time.

2. The method for controlling the intelligent ventilation system in a tunnel according to claim 1, characterized in that: The intelligent ventilation system in the tunnel also includes an early warning unit, which is connected to the data analysis unit. When the CO concentration and VI within a certain period of time exceed the threshold, the early warning unit will sound an alarm.

3. The method for controlling the intelligent ventilation system in a tunnel according to claim 2, characterized in that: The intelligent ventilation system in the tunnel also includes an automatic inspection unit, which is communicated with the early warning unit. The automatic inspection unit is used to establish a digital twin model of the intelligent ventilation system in the tunnel and perform automatic inspections on the equipment in the ventilation system. When the real-time operating status of the equipment is abnormal, the early warning unit will issue an alarm.

4. The method for controlling an intelligent ventilation system in a tunnel according to claim 1, characterized in that: When the CO concentration and VI exceed the threshold, the specific method of controlling each fan to enter the corresponding working mode is: When the COVI detector in a certain detection section detects a CO concentration exceeding 80ppm or a VI exceeding 5.2x10 -3 m -1 When the axial flow fan of the detection section is turned on, the axial flow fan of the detection section is controlled; When the CO concentration in a detection section exceeds 90 ppm or the VI exceeds 5.85 x10 -3 m -1 When the detection section is under test, the axial flow fan and jet fan of the detection section shall be controlled to be turned on; for the detection section with roof fan, the roof fan of the detection section shall be turned on at the same time.

5. The method for controlling the intelligent ventilation system in a tunnel according to claim 3, characterized in that: The control method of the intelligent ventilation system in the tunnel also includes an automatic inspection step, which includes: establishing a digital twin model of the intelligent ventilation system in the tunnel, automatically inspecting the equipment of the ventilation system, and when the real-time operating status of the equipment is abnormal, an alarm is issued to notify the operation and maintenance personnel to enter the site for inspection and maintenance.

6. The method for controlling the intelligent ventilation system in a tunnel according to claim 5, characterized in that: future The alarm when the CO concentration and VI data within a certain period exceed the threshold value is different from the alarm when the real-time operating status of the equipment is abnormal. The alarm is classified by the C4.5 decision tree algorithm before it is issued.

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