An Internet of Things-based health monitoring system and method for highway tunnel smoke exhaust ducts

Abstract

The present invention discloses a health monitoring system for a highway tunnel smoke exhaust duct based on the Internet of Things, which includes an air pressure sensor inside the smoke exhaust duct, an air pressure sensor outside the smoke exhaust duct, a temperature sensor, and a wind speed tester. The data monitored by each sensor is sequentially uploaded to the Internet of Things backend monitoring system for processing and analysis through a data acquisition and control module and an information communication module, and then sent to a management terminal. The management terminal sends control commands to corresponding front-end operating devices sequentially through the Internet of Things backend monitoring system, the information communication module, and the data acquisition and control module. The present invention also discloses a health monitoring method for a highway tunnel smoke exhaust duct based on the Internet of Things, which realizes rapid inspection, automatic abnormal detection and positioning of the smoke exhaust valve, thereby reducing the work pressure of tunnel operation and maintenance personnel; further calculates the air leakage coefficient of the smoke exhaust port and the overall friction coefficient of the smoke exhaust duct, and quantitatively analyzes the health status of the smoke exhaust duct in real time.

Description

Technical Field

[0001] The invention belongs to the technical fields of highway tunnel operation safety and industrial Internet of Things, and particularly relates to a health monitoring system for a highway tunnel smoke exhaust duct based on the Internet of Things, and also relates to a health monitoring method for a highway tunnel smoke exhaust duct based on the Internet of Things. Background Art

[0002] Due to the long and narrow space and strong airtightness of the tunnel, during a fire, the generated smoke is the biggest threat to the safety of personnel's lives. If the trapped personnel cannot be evacuated in time, heavy casualties and property losses will be caused. Therefore, the design of the smoke exhaust system in the tunnel is particularly important. Key smoke exhaust can effectively control the diffusion of smoke in the tunnel by setting up a dedicated smoke exhaust duct, and has good smoke control and exhaust effects.

[0003] At present, the dedicated smoke exhaust ducts are mostly prefabricated and assembled on site, and there are air leakage phenomena caused by various reasons. It is necessary to monitor the air leakage situation of the smoke exhaust duct. However, at present, no monitoring sensors are installed in the dedicated smoke exhaust ducts of tunnels adopting the key smoke exhaust mode. During the test and acceptance stage, once the key smoke exhaust fails to meet the design requirements, it is necessary to rely on manual inspection to determine the air leakage points and the positions of sudden resistance changes, which is time-consuming and laborious, and cannot achieve comprehensive inspection. The design party and the equipment construction party each stick to their own opinions and the responsibilities are not clear. At the same time, during the operation stage, due to the lack of dynamic monitoring of the smoke flow parameters in the smoke exhaust duct, quantitative analysis cannot be carried out, and it is even more impossible to start relevant rectification and smoke exhaust control. With the increase in the length of the tunnel, the length of the key smoke exhaust duct and the number of smoke valves on the smoke exhaust duct also increase, and the problems of system air leakage and even failure will be more obvious.

[0004] Therefore, it is urgent to monitor the operation state of the smoke exhaust duct in real time; combine the characteristics of the air flow, the composition of the wind pressure, the direction of the wind pressure, and the influence range of the smoke after a fire to establish an integrated intelligent sensor for comprehensive perception of ventilation parameters; combine the air flow distribution law in the tunnel and the change law of the smoke flow velocity in the smoke exhaust duct and at the smoke valve under different smoke exhaust volumes and different air leakage conditions at the unopened smoke valve to establish a smoke exhaust duct air leakage diagnosis and early warning system. Thus, comprehensively optimize the design of the ventilation and smoke exhaust system, establish an intelligent key smoke exhaust control system for the tunnel, and ensure the safety of drivers and passengers and reduce the losses caused by fire accidents.

[0005] Most of the existing tunnel smoke exhaust duct monitoring systems are temporarily built and are mainly used for the hot smoke experiment during the tunnel fire acceptance, which can verify the smoke control effect of the tunnel smoke exhaust system. However, this system does not consider the problem of the failure of the smoke exhaust system caused by the long-term operation and aging of the tunnel smoke exhaust duct system and the degradation of the performance of the sealing materials. At the same time, it cannot provide first-hand data support for the later intelligent operation and maintenance of the tunnel, and most of the flue monitoring systems are mainly used for air ducts. The invention is applied to the field of tunnel smoke exhaust systems for the first time. At the same time, the sensors are cumbersome when measuring the average wind speed of the measurement section in the prior art and are not suitable for the tunnel smoke exhaust duct area with limited space. Summary of the Invention

[0006] The present invention is to solve the problems of poor reliability of highway tunnel smoke exhaust, difficult monitoring of air leakage in the smoke exhaust duct, inability to quickly grasp the health status of the smoke exhaust duct, locate the air leakage points in the smoke exhaust duct during long-term operation, and the existing air leakage situation in the smoke exhaust duct cannot be quantitatively evaluated in real time, making it difficult to timely grasp the air leakage situation of the entire smoke exhaust duct. A health monitoring system for highway tunnel smoke exhaust ducts based on the Internet of Things is proposed, and a health monitoring method for highway tunnel smoke exhaust ducts based on the Internet of Things is also proposed.

[0007] In order to achieve the above object, the main technical means adopted in this technical solution are as follows:

[0008] A health monitoring system for highway tunnel smoke exhaust ducts based on the Internet of Things includes front-end sensing devices. The data monitored in real time by the front-end sensing devices are sequentially uploaded to the Internet of Things back-end monitoring system in the server for processing and analysis through the data acquisition control module and the information communication module, and then sent to the management terminal; the management terminal sends control commands to the corresponding front-end operating devices through the Internet of Things back-end monitoring system, the information communication module, and the data acquisition control module in sequence.

[0009] The front-end sensing devices include an in-duct air pressure sensor, an out-duct air pressure sensor, a temperature sensor, and a wind speed tester. The in-duct air pressure sensor, the temperature sensor, and the wind speed tester are all installed in the smoke exhaust duct, and the out-duct air pressure sensor is installed outside the smoke exhaust duct.

[0010] The front-end operating devices include a smoke exhaust valve and a fan.

[0011] As described above, a plurality of smoke exhaust openings are arranged at intervals in the smoke exhaust duct, a smoke exhaust valve is arranged in the smoke exhaust opening, a section of the smoke exhaust duct between every two adjacent smoke exhaust openings is a smoke exhaust duct section, a cross-section perpendicular to the central axis of the smoke exhaust duct in each smoke exhaust duct section is used as a test cross-section, a wind speed tester, an in-duct air pressure sensor, and a temperature sensor are arranged in each test cross-section, the in-duct air pressure sensor and the temperature sensor are located at the center of the corresponding test cross-section, and the distance between adjacent test cross-sections is equal to the distance between adjacent smoke exhaust openings.

[0012] A health monitoring method for highway tunnel smoke exhaust ducts based on the Internet of Things uses the above-mentioned health monitoring system for highway tunnel smoke exhaust ducts based on the Internet of Things, and is characterized by including the following steps:

[0013] Step 1: Select the first smoke exhaust valve as the current smoke exhaust valve;

[0014] Step 2: The Internet of Things back-end monitoring system starts to record: the curve of the air pressure change with time in the smoke exhaust duct section monitored by the in-duct air pressure sensor corresponding to the current smoke exhaust valve and the curve of the wind speed change with time in the smoke exhaust duct section monitored by the wind speed tester.

[0015] Step 3: The Internet of Things backend monitoring system sends an opening or closing execution signal to the current smoke exhaust valve once.

[0016] Step 4: When there is no turning point in the curve of the wind pressure changing with time in the corresponding smoke exhaust duct section or the curve of the wind speed changing with time in the smoke exhaust duct section, the Internet of Things backend monitoring system records the corresponding smoke exhaust valve serial number and executes Step 5. If there is a turning point in the curve of the wind pressure changing with time in the smoke exhaust duct section and the curve of the wind speed changing with time in the smoke exhaust duct section, then the next smoke exhaust valve is taken as the current smoke exhaust valve and Step 2 is returned until all smoke exhaust valves are traversed.

[0017] Step 5: The Internet of Things backend monitoring system determines the location where the abnormal smoke exhaust valve is located according to the product of the smoke exhaust valve serial number and the spacing between the smoke exhaust valves, and sends the location where the abnormal smoke exhaust valve is located to the management terminal. Then, the next smoke exhaust valve is taken as the current smoke exhaust valve and Step 2 is returned until all smoke exhaust valves are traversed.

[0018] 4. A health monitoring method for a highway tunnel smoke exhaust duct based on the Internet of Things, using the health monitoring system for a highway tunnel smoke exhaust duct based on the Internet of Things described in claim 2, characterized by including the following steps:

[0019] Step 1: Select the first smoke exhaust valve as the current smoke exhaust valve.

[0020] Step 2: The Internet of Things backend monitoring system starts to record: the curve of the wind pressure changing with time in the smoke exhaust duct section monitored by the wind pressure sensor in the smoke exhaust duct corresponding to the current smoke exhaust valve and the curve of the wind speed changing with time in the smoke exhaust duct section monitored by the anemometer.

[0021] Step 3: Send an opening execution signal to the current smoke exhaust valve once.

[0022] Step 4: When there is no turning point in the curve of the wind pressure changing with time in the corresponding smoke exhaust duct section or the curve of the wind speed changing with time in the smoke exhaust duct section, then Step 5 is executed. If there is a turning point in the curve of the wind pressure changing with time in the smoke exhaust duct section and the curve of the wind speed changing with time in the smoke exhaust duct section, then Step 5 is directly executed. Then, the next smoke exhaust valve is taken as the current smoke exhaust valve and Step 2 is returned until all smoke exhaust valves are traversed.

[0023] Step 5: The Internet of Things backend monitoring system sends a closing execution signal to the current smoke exhaust valve once.

[0024] Step 6: When there is no turning point in the curve of the wind pressure changing with time in the corresponding smoke exhaust duct section or the curve of the wind speed changing with time in the smoke exhaust duct section, the Internet of Things backend monitoring system records the corresponding smoke exhaust valve serial number and executes Step 7. If there is a turning point in the curve of the wind pressure changing with time in the smoke exhaust duct section and the curve of the wind speed changing with time in the smoke exhaust duct section, the next smoke exhaust valve is taken as the current smoke exhaust valve and Step 2 is returned until all smoke exhaust valves are traversed;

[0025] Step 7: The Internet of Things backend monitoring system determines the location where the abnormal smoke exhaust valve is located according to the product of the smoke exhaust valve serial number and the smoke exhaust valve spacing, and sends the location where the abnormal smoke exhaust valve is located to the management terminal. Then, the next smoke exhaust valve is taken as the current smoke exhaust valve and Step 2 is returned until all smoke exhaust valves are traversed.

[0026] 5. A health monitoring method for a highway tunnel smoke exhaust duct based on the Internet of Things, which uses the health monitoring system for a highway tunnel smoke exhaust duct described in Embodiment 2, and is characterized by including the following steps:

[0027] According to the wind pressure in the smoke exhaust duct section monitored by the wind pressure sensor in the smoke exhaust duct, the wind pressure outside the smoke exhaust duct monitored by the wind pressure sensor outside the smoke exhaust duct, the wind speed in the smoke exhaust duct section monitored by the wind speed tester, and the temperature measurement value measured by the temperature sensor in the smoke exhaust duct section, and the following formula, the air leakage coefficient μ of the smoke exhaust port is obtained:

[0028]

[0029] Among them, i represents the serial number of the smoke exhaust duct section;

[0030] Q i : represents the air volume of the smoke exhaust duct section with the serial number i, Q i+1 : represents the air volume of the smoke exhaust duct section with the serial number i + 1; the air volume of the smoke exhaust duct section is equal to the product of the wind speed in the smoke exhaust duct section and the cross-sectional area S of the smoke exhaust duct;

[0031] P i : represents the wind pressure difference of the smoke exhaust duct section with the serial number i, P i =P i '-P', P i ' represents the wind pressure in the smoke exhaust duct section with the serial number i, and P' represents the wind pressure outside the smoke exhaust duct;

[0032] A: represents the area of the smoke exhaust port;

[0033] μ i : the gas density in the smoke exhaust duct section with the serial number i;

[0034] The gas density is obtained according to the following gas state equation:

[0035] P = ρi RT i

[0036] Among them, the standard atmospheric pressure P = 101325 Pa; T i represents the temperature measurement value of the i-th section of the smoke exhaust duct; R is the gas constant.

[0037] 6. The method for health monitoring of a highway tunnel smoke exhaust duct based on the Internet of Things according to claim 5, characterized in that it further includes the following steps:

[0038] Calculate the friction coefficient λ through the following formula:

[0039]

[0040] Among them, S: cross-sectional area of the smoke exhaust duct;

[0041] l: distance between smoke outlets;

[0042] d: hydraulic diameter of the smoke exhaust duct;

[0043] P i represents the wind pressure difference of the i-th section of the smoke exhaust duct, P i = P i ′ - P′, P i ′ represents the wind pressure difference of the i-th section of the smoke exhaust duct, and P′ represents the wind pressure outside the smoke exhaust duct; P i+1 represents the wind pressure difference of the i-th smoke exhaust duct,

[0044] P i+1 = P i ′ +1 - P′, P i ′ +1 represents the wind pressure inside the (i + 1)-th section of the smoke exhaust duct;

[0045] Calculate the overall friction coefficient ∈ of the smoke exhaust duct from the air leakage coefficient μ of the smoke outlet and the friction coefficient λ:

[0046]

[0047] Compared with the existing technology, the beneficial effects of this technical solution are as follows:

[0048] 1. Intelligent operation and maintenance: By combining the wind pressure and wind speed data, the present invention can achieve intelligent inspection and control of the electric smoke exhaust valve, realize the intelligent operation and maintenance of the tunnel, and reduce the workload of manual inspection.

[0049] 2. Optimize the smoke exhaust strategy: The present invention can adjust the power of the two-end fans by combining the quantitative data of the monitored wind speed and wind pressure, optimize the smoke exhaust strategy, maximize the smoke exhaust efficiency, and is also beneficial to the operation energy consumption of the ventilation equipment and reduce the operation and maintenance cost.

[0050] 3. Detect and handle problems in a timely manner: The present invention can monitor the operating status of the smoke exhaust duct in real time, quantitatively analyze the air leakage coefficient of the smoke exhaust port and the overall friction coefficient of the smoke exhaust duct, so as to detect abnormalities in a timely manner, immediately send out warning information, and give the range of the air leakage location, thereby realizing the real-time grasp of the smoke exhaust reliability. The information can be shared on the tunnel monitoring integration platform, which is convenient for tunnel operation and maintenance personnel to manage. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 is a schematic structural diagram of a highway tunnel smoke exhaust duct health monitoring system based on the Internet of Things;

[0052] Figure 2 is a schematic overall distribution diagram of a highway tunnel smoke exhaust duct health monitoring system based on the Internet of Things;

[0053] Figure 3 is a schematic diagram of the sensor layout of the cross-section of the smoke exhaust duct;

[0054] Figure 4 is a schematic diagram of the communication connection of a highway tunnel smoke exhaust duct health monitoring system based on the Internet of Things;

[0055] Among them, 1 - server; 2 - test section; 3 - on-site monitoring box; 4 - smoke exhaust port; 5 - air pressure sensor inside the smoke exhaust duct; 6 - wind speed tester; 7 - air pressure sensor outside the smoke exhaust duct; 8 - PLC programmable logic controller; 9 - information communication module; 10 - management terminal; 11 - temperature sensor; 12 - thermocouple transmitter; 13 - smoke exhaust valve; 14 - fan; 15 - drive module. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0056] In order to facilitate the understanding and implementation of the present invention by those of ordinary skill in the art, the present invention will be further described in detail below in conjunction with the embodiments. It should be understood that the embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0057] Embodiment 1:

[0058] A highway tunnel smoke exhaust duct health monitoring system based on the Internet of Things includes front-end sensing devices and front-end operating devices. The data real-time monitored by the front-end sensing devices is uploaded to the Internet of Things backend monitoring system in the server 1 through the data acquisition control module and the information communication module 9 in sequence; the Internet of Things backend monitoring system processes and analyzes the data real-time monitored by the front-end sensing devices and then sends it to the management terminal 10; the management terminal 10 sends the control command to the corresponding front-end operating device through the Internet of Things backend monitoring system, the information communication module 9 and the data acquisition control module in sequence. Specifically:

[0059] (1) Front-end sensing devices: including a wind pressure sensor, a temperature sensor 11, a wind speed tester 6, etc. Among them, the wind pressure sensor includes an in-duct wind pressure sensor 5 and an out-duct wind pressure sensor 7. The in-duct wind pressure sensor 5, the temperature sensor 11, and the wind speed tester 6 are all installed in the exhaust duct, and the out-duct wind pressure sensor 7 is installed outside the exhaust duct. In this embodiment, the temperature sensor 11 uses a thermocouple temperature sensor.

[0060] A plurality of exhaust ports 4 are arranged at intervals in the exhaust duct. A smoke exhaust valve 13 is arranged in the exhaust port 4. In this embodiment, a plurality of smoke exhaust valves 13 are arranged at equal horizontal intervals. The distance between every two adjacent smoke exhaust valves 13 in the exhaust duct is 120 m. A section of the exhaust duct between every two adjacent exhaust ports 4 is an exhaust duct section. A cross-section perpendicular to the central axis of the exhaust duct in each exhaust duct section is used as a test section 2. A wind speed tester 6, an in-duct wind pressure sensor 5, and a temperature sensor 11 are arranged in each test section 2. The distance between adjacent test sections 2 is equal to the distance between adjacent exhaust ports 4, and the horizontal distance between the test sections 2 is also 120 m. Since each front-end sensing device needs to be powered, a cable tray is separately arranged in the highway tunnel, and the communication and power supply of all front-end sensing devices are uniformly planned and set. As Figure 3 shown, a wind speed tester 6 is arranged at the test section 2, and 1 in-duct wind pressure sensor 5 and 1 temperature sensor 11 are arranged at the center of the test section 2. Due to the irregularity of the exhaust duct, the boundary layer of the exhaust duct has a great influence on the uniformity of the wind speed distribution. The wind speed distribution in the exhaust duct is uneven. The wind speed measurement results will vary greatly due to different measuring point positions, which brings certain difficulties to the measurement of the average wind speed in the exhaust duct; most of the traditional wind speed measurements in the tunnel exhaust duct adopt the method of multi-point pitot tube measurement and then taking the weighted average, but it has the disadvantages of complex hardware layout and high cost, and is not suitable for establishing a permanent exhaust duct monitoring system. In this embodiment, the wind speed tester 6 at the test section 2 uses a cross wind speed tester to replace the traditional multi-point weighted average wind speed measurement method, realizing the front-end wind speed averaging process. The cross wind speed tester includes two intersecting installation pipes, and a plurality of wind speed sensors are connected to both the windward side and the leeward side of the pipe wall of the installation pipe. The wind speed sensors on the windward side and the leeward side are respectively arranged at equal intervals along the extension direction of the corresponding installation pipe. In the cross wind speed tester, the average value of the measured values of the wind speed sensors on the windward side is the average total pressure, and the average value of the measured values of the wind speed sensors on the leeward side is the average static pressure. The average wind speed at the corresponding test section 2 can be obtained according to the pressure difference between the average total pressure and the average static pressure.

[0061] In this embodiment, the outer shells of the wind pressure sensors (including the in-duct wind pressure sensor 5 and the out-duct wind pressure sensor 7) are protected by hard-structured aluminum alloy. The main structure is an OEM silicon piezoresistive differential pressure core, and the high and low pressure interfaces adopt a plugcock and an M10 thread structure.

[0062] The key to monitoring the accuracy of air leakage lies in the working accuracy of the air pressure sensor. Therefore, in order to reduce the measurement error of the air pressure sensor, the heights of the rubber hoses connected to the high and low pressure interfaces of the air pressure sensor should be ensured to be the same. After installation, the air pressure sensor should be calibrated regularly and the rubber hoses should be checked for damage to ensure the stable operation of the monitoring equipment. The arranged air pressure sensors should be installed according to the following requirements: Before installing the air pressure sensor, use a remote control to zero the data; the air pressure sensor should be arranged vertically, and at the same time, vibration or strong impact should be avoided during installation; the air pressure sensor should be arranged in a firm position with less vibration and no water spray.

[0063] Measures for dealing with air leakage: (1) Spray anti-leakage materials such as polyurethane foam at the gaps in the contact area between the decorative plate between the smoke exhaust valve 13 and the smoke exhaust port 4 to reduce or prevent air leakage through cracks. (2) Install flow guiding plates at key positions in the smoke exhaust duct to reduce the outflow of air, strengthen its integrity and reduce air leakage.

[0064] (2) Front-end operating equipment: including the smoke exhaust valve 13 and the fan 14. In this embodiment, the smoke exhaust valve 13 is an electric smoke exhaust valve 13.

[0065] (3) Data acquisition control module and information communication module 9: The data acquisition control module collects the monitoring data of the front-end sensing equipment and uploads the data through the information communication module 9.

[0066] In this embodiment, the temperature sensor 11 is a thermocouple temperature sensor, and the data acquisition control module includes a PLC programmable logic controller 8 and a thermocouple transmitter 12:

[0067] The signal output ports of the air pressure sensor 5, the wind speed tester 6 and the air pressure sensor 7 outside the smoke exhaust duct in the smoke exhaust duct are all connected to the PLC programmable logic controller 8, and the PLC programmable logic controller 8 is connected to the information communication module 9;

[0068] The signal output port of the temperature sensor 11 is sequentially connected to the information communication module 9 through the thermocouple transmitter 12 and the PLC programmable logic controller 8;

[0069] The control ports of the smoke exhaust valve 13 and the fan 14 are respectively connected to the control output ports of the corresponding drive module 15. The power input port of the drive module 15 is connected to the drive power supply, and the signal input port of the drive module 15 is connected to the control signal output port of the PLC programmable logic controller 8;

[0070] The information communication module 9 is connected to the server 1 through a wireless network; the server 1 and the management terminal 10 are connected to each other through a network, and an Internet of Things backend monitoring system is built in the server 1.

[0071] For each group of wind speed testers 6, the wind pressure sensors 5 in the smoke exhaust duct, and the temperature sensors 11 (corresponding to one test section 2), one set of on-site monitoring box 3 is correspondingly set outside the smoke exhaust duct at each test section 2. The thermocouple transmitter 12, the drive module 15, the PLC programmable logic controller 8, and the information communication module 9 corresponding to the test section 2 are all located in the on-site monitoring box 3.

[0072] In this embodiment, the PLC programmable logic controller 8 adopts the RS485 communication method, and the information communication module 9 is reserved with a wireless communication interface.

[0073] Internet of Things backend monitoring system: The management terminal 10 obtains the real-time monitoring data of the front-end sensing devices and the data analyzed by the Internet of Things backend monitoring system from the Internet of Things backend monitoring system, and displays them in real time and provides warning information, so that the operation and maintenance personnel can timely discover the air leakage problem of the smoke exhaust duct and perform intelligent regulation on devices such as the smoke exhaust valve 13 or the fan 14 in the smoke exhaust duct, ensuring the reliability of the smoke exhaust system and facilitating operation and maintenance traceability and management. Among them, the management terminal 10 includes a mobile phone, a computer, or other portable devices, and the operation and maintenance personnel monitor the air leakage problem of the smoke exhaust duct and perform intelligent regulation on devices such as the smoke exhaust valve 13 or the fan 14 in the smoke exhaust duct through the mobile phone APP or the computer system software.

[0074] Based on the Internet of Things backend monitoring system, the three-dimensional intelligent tunnel monitoring system software can be developed secondarily to display the operating conditions of the fan 14, the opening position / quantity of the smoke exhaust valve 13, the ventilation resistance, the wind speed and wind pressure, etc. in real time. Combining with Embodiment 2, the automatic inspection of the smoke exhaust valve 13 can be carried out; combining with Embodiment 3, the air leakage coefficient of the smoke exhaust port 4 and the overall friction coefficient of the smoke exhaust duct can be obtained, and the air leakage warning threshold can be set.

[0075] Based on the above-mentioned highway tunnel smoke exhaust duct health monitoring system based on the Internet of Things, the following software functions can also be realized:

[0076]

[0077] Before using the highway tunnel smoke exhaust duct health monitoring system based on the Internet of Things of the present invention, the system is built according to the following steps:

[0078] Step 1: Set up an IoT backend monitoring system on Server 1 and perform initialization settings for each front-end sensing device and data acquisition and control module. Initialize the average wind speed tester 6, the wind pressure sensor 5 inside the smoke exhaust duct, the wind pressure sensor 7 outside the smoke exhaust duct, and the temperature sensor 11; initialize the thermocouple transmitter 12, the drive module 15, the PLC programmable logic controller 8, and the information communication module 9, and debug the IoT backend monitoring system so that the monitoring data of the average wind speed tester 6, the wind pressure sensor 5 inside the smoke exhaust duct, the wind pressure sensor 7 outside the smoke exhaust duct, and the temperature sensor 11 can be displayed on the management terminal 10 after passing through the IoT backend monitoring system of Server 1.

[0079] Step 2: Equipment installation. Install a corresponding set of front-end sensing devices, namely the wind pressure sensor 5 inside the smoke exhaust duct, the temperature sensor 11, and the wind speed tester 6, respectively, according to the positions of each smoke exhaust valve 13 (or test section 2) inside the smoke exhaust duct. Install the wind pressure sensor 7 outside the smoke exhaust duct, as well as the corresponding data acquisition and control module and information communication module 9; and upload the real-time monitoring data of the above-mentioned front-end sensing devices to the IoT backend monitoring system through the data acquisition and control module and the information communication module 9 and display it on the management terminal 10. In Step 2, install the thermocouple transmitter 12, the drive module 15, the PLC programmable logic controller 8, and the information communication module 9 corresponding to the test section 2 in the on-site monitoring box 3, which are designed as independent modules for easy installation, maintenance, and replacement. At the same time, adopt a waterproof and dustproof design to adapt to the tunnel environment and improve the reliability of the equipment.

[0080] Example 2:

[0081] A method for health monitoring of a highway tunnel smoke exhaust duct based on the Internet of Things, which realizes rapid inspection, automatic abnormal detection and positioning of the smoke exhaust valve 13, thereby reducing the work pressure of tunnel operation and maintenance personnel, and uses the health monitoring system of a highway tunnel smoke exhaust duct based on the Internet of Things described in Example 1.

[0082] Turn on the IoT backend monitoring system, send an automatic inspection command to the IoT backend monitoring system through the management terminal 10. When the state of the fan 14 in the smoke exhaust duct remains unchanged, the IoT backend monitoring system executes the automatic inspection program of the smoke exhaust valve 13, performs opening and closing operations on each smoke exhaust valve 13 in turn, and obtains the wind pressure and wind speed change curves within the corresponding smoke exhaust duct section, so as to realize rapid inspection of the electric smoke exhaust valve 13, understand the states of each smoke exhaust valve 13, and thus realize intelligent operation and maintenance of the smoke exhaust valve 13.

[0083] Among them, performing opening and closing operations on each smoke exhaust valve 13 in turn and obtaining the corresponding wind pressure and wind speed change curves specifically include the following steps:

[0084] Step 1: Select the first smoke exhaust valve 13 as the current smoke exhaust valve 13;

[0085] Step 2: The IoT backend monitoring system starts to record the curve of the air pressure changing with time in the smoke exhaust duct section monitored by the air pressure sensor 5 in the smoke exhaust duct corresponding to the current smoke exhaust valve 13 and the curve of the wind speed changing with time in the smoke exhaust duct section monitored by the anemometer 6;

[0086] Step 3: The IoT backend monitoring system sends an opening or closing execution signal to the current smoke exhaust valve 13 once;

[0087] Step 4: When there is no turning point in the curve of the air pressure changing with time in the corresponding smoke exhaust duct section or the curve of the wind speed changing with time in the smoke exhaust duct section, the IoT backend monitoring system records the serial number of the corresponding smoke exhaust valve 13 and executes Step 5. If there is a turning point in the curve of the air pressure changing with time in the smoke exhaust duct section and the curve of the wind speed changing with time in the smoke exhaust duct section, then take the next smoke exhaust valve 13 as the current smoke exhaust valve 13 and return to Step 2 until all smoke exhaust valves 13 are traversed;

[0088] Step 5: The IoT backend monitoring system determines the location where the abnormal smoke exhaust valve 13 is located according to the product of the serial number of the smoke exhaust valve 13 and the distance between the smoke exhaust valves 13, and sends the location where the abnormal smoke exhaust valve 13 is located to the management terminal 10, then take the next smoke exhaust valve 13 as the current smoke exhaust valve 13 and return to Step 2 until all smoke exhaust valves 13 are traversed.

[0089] Furthermore, to avoid accidental factors, or the initial switch state of the electric smoke exhaust valve 13 is unknown, or the initial switch states of each electric smoke exhaust valve 13 are inconsistent, through two detections, the wind speed and air pressure data in the corresponding smoke exhaust duct section under the two operations of the electric smoke exhaust valve 13 can be verified with each other, so as to improve the accuracy of the smoke exhaust valve 13 state detection. The specific steps are as follows:

[0090] Step 1: Select the first smoke exhaust valve 13 as the current smoke exhaust valve 13;

[0091] Step 2: The IoT backend monitoring system starts to record the curve of the air pressure changing with time in the smoke exhaust duct section monitored by the air pressure sensor 5 in the smoke exhaust duct corresponding to the current smoke exhaust valve 13 and the curve of the wind speed changing with time in the smoke exhaust duct section monitored by the anemometer 6;

[0092] Step 3: The IoT backend monitoring system sends an opening execution signal to the current smoke exhaust valve 13 once;

[0093] Step 4: When there is no turning point in the curve of the wind pressure changing with time in the corresponding smoke exhaust duct segment or the curve of the wind speed changing with time in the smoke exhaust duct segment, step 5 is executed. If there is a turning point in the curve of the wind pressure changing with time in the smoke exhaust duct segment and the curve of the wind speed changing with time in the smoke exhaust duct segment, the next smoke exhaust valve 13 is taken as the current smoke exhaust valve 13 and step 2 is returned until all the smoke exhaust valves 13 are traversed;

[0094] Step 5: The IoT backend monitoring system sends a closing execution signal to the current smoke exhaust valve 13 once;

[0095] Step 6: When there is no turning point in the curve of the wind pressure changing with time in the corresponding smoke exhaust duct segment or the curve of the wind speed changing with time in the smoke exhaust duct segment, the IoT backend monitoring system records the serial number of the corresponding smoke exhaust valve 13 and executes step 7. If there is a turning point in the curve of the wind pressure changing with time in the smoke exhaust duct segment and the curve of the wind speed changing with time in the smoke exhaust duct segment, the next smoke exhaust valve 13 is taken as the current smoke exhaust valve 13 and step 2 is returned until all the smoke exhaust valves 13 are traversed;

[0096] Step 7: The IoT backend monitoring system determines the location where the abnormal smoke exhaust valve 13 is located according to the product of the serial number of the smoke exhaust valve 13 and the distance between the smoke exhaust valves 13, and sends the location where the abnormal smoke exhaust valve 13 is located to the management terminal 10 for prompting the location for manual inspection. Then the next smoke exhaust valve 13 is taken as the current smoke exhaust valve 13 and step 2 is returned until all the smoke exhaust valves 13 are traversed.

[0097] In traditional tunnels, there is no monitoring of the smoke exhaust valve 13. Mostly, the fans 14 and the wind speed in the tunnel are monitored. Since the electric smoke exhaust valve 13 system in the tunnel has been in long-term operation and is in disrepair, it will cause the opening and closing of the electric smoke exhaust valve 13 to fail, resulting in the need to organize personnel to inspect the electric smoke exhaust valve 13. Since the opening and closing of the electric smoke exhaust valve 13 will cause sudden changes in the wind speed and wind pressure in the smoke exhaust duct, turning points will be formed in the monitoring data. Therefore, the detected turning points of the wind speed and wind pressure represent that the opening and closing state of the corresponding electric smoke exhaust valve 13 has changed. When the electric smoke exhaust valve 13 changes from closed to open, normally the corresponding wind pressure data decreases and the wind speed also decreases because there are only fans 14 installed at both ends of the smoke exhaust duct; when the electric smoke exhaust valve 13 changes from open to closed, normally the wind pressure data will increase and the wind speed data will increase. Therefore, when there is no turning point in the curve of the wind pressure changing with time in the smoke exhaust duct segment corresponding to the opening or closing of the smoke exhaust valve 13 or the curve of the wind speed changing with time in the smoke exhaust duct segment, it is considered that the corresponding smoke exhaust valve 13 or the sensor (including: the wind pressure sensor 5 and the wind speed tester 6 in the smoke exhaust duct) is abnormal.

[0098] Further, based on an Internet of Things-based highway tunnel smoke exhaust duct health monitoring system, energy consumption management can be carried out according to the actual working conditions of the smoke exhaust duct. According to the actual working conditions of the smoke exhaust duct, the power of the two end fans 14 is dynamically adjusted to maximize the smoke exhaust efficiency while reducing energy consumption. For example, when the smoke exhaust valve 13 is in the open state and the wind speed drops to a certain threshold, the power of the fan 14 is increased until the wind speed reaches the set value or range.

[0099] Embodiment 3

[0100] An Internet of Things-based method for monitoring the health of highway tunnel smoke exhaust ducts uses the Internet of Things-based highway tunnel smoke exhaust duct health monitoring system described in Embodiment 1 to further calculate the air leakage coefficient of the smoke exhaust port 4 and the overall friction coefficient of the smoke exhaust duct in the Internet of Things backend monitoring system for evaluating the degree of air leakage in the duct.

[0101] According to the wind pressure in the smoke exhaust duct segments monitored by the wind pressure sensors 5 in each smoke exhaust duct collected by the Internet of Things-based highway tunnel smoke exhaust duct health monitoring system described in Embodiment 1, the wind pressure outside the smoke exhaust duct monitored by the external wind pressure sensor 7 of the smoke exhaust duct, the wind speed of the smoke exhaust duct segments monitored by the wind speed tester 6, and the temperature measurement values measured by the temperature sensors 11 in the smoke exhaust duct segments, the air leakage coefficient of the smoke exhaust port and the overall friction coefficient of the smoke exhaust duct are calculated in sequence.

[0102] Step 1: Calculate the air leakage coefficient μ of the smoke exhaust port according to the following formula:

[0103]

[0104] where i represents the serial number of the smoke exhaust duct segment;

[0105] Q i : represents the air volume of the smoke exhaust duct segment with serial number i, Q i+1 : represents the air volume of the smoke exhaust duct segment with serial number i + 1; the air volume of the smoke exhaust duct segment is equal to the product of the wind speed of the smoke exhaust duct segment and the cross-sectional area S of the smoke exhaust duct;

[0106] P i : represents the wind pressure of the smoke exhaust duct segment with serial number i, P i = P i ′ - P′, P i ′ represents the wind pressure inside the smoke exhaust duct segment with serial number i, and P′ represents the wind pressure outside the smoke exhaust duct;;

[0107] A: represents the area of the smoke exhaust port, that is, the area of the smoke exhaust port 4 where the smoke exhaust valve 13 is installed when the smoke exhaust valve 13 is in the open state;

[0108] ρ i : the gas density in the smoke exhaust duct segment with serial number i;

[0109] The gas density is obtained according to the following ideal gas law:

[0110] P = ρ i RT i

[0111] where the standard atmospheric pressure P = 101325 Pa; T i represents the temperature measurement value of the i-th segment of the smoke exhaust duct; R is the gas constant, for air, R = 287.06 J / (kg*K).

[0112] Step 2. Calculate the friction coefficient λ through the following formula:

[0113]

[0114] where S: cross-sectional area of the smoke exhaust duct,

[0115] l: distance between the smoke exhaust outlets, equal to the distance between adjacent smoke valves 13, in this embodiment, also equal to the distance between adjacent test sections 2,

[0116] d: hydraulic diameter of the smoke exhaust duct,

[0117] P i represents the wind pressure difference of the i-th segment of the smoke exhaust duct, P i = P i ′ - P′, P i ′ represents the wind pressure inside the i-th segment of the smoke exhaust duct, P′ represents the wind pressure outside the smoke exhaust duct; P i+1 represents the wind pressure difference of the i-th smoke exhaust duct,

[0118] P i+1 = P i ′ +1 - P′, P i ′ +1 represents the wind pressure inside the (i + 1)-th segment of the smoke exhaust duct;

[0119] Step 3. Calculate the overall friction coefficient ∈ of the smoke exhaust duct from the leakage coefficient μ of the smoke exhaust outlet calculated in Step 1 and the friction coefficient λ obtained in Step 2:

[0120]

[0121] Calculate the overall friction coefficient ∈ of the smoke exhaust duct, evaluate the airtightness of the smoke exhaust duct as a whole, quantify the airtightness and leakage points of the smoke exhaust duct, so as to provide suggestions for the maintenance and management of the smoke exhaust duct for the tunnel operation and maintenance unit, and improve the safety and resilience of the tunnel operation.

[0122] The specific embodiments described herein are merely illustrative of the spirit of the present invention. Those skilled in the art to which the present invention pertains can make various modifications or supplements to the described specific embodiments or use similar means for substitution, but will not deviate from the spirit of the present invention or exceed the scope defined by the appended claims.

Claims

1. A health monitoring system for highway tunnel smoke exhaust ducts based on the Internet of Things, including front-end sensing devices, characterized in that, The data real-time monitored by the front-end sensing device is uploaded to the Internet of Things back-end monitoring system in the server (1) through the data acquisition control module and the information communication module (9) in sequence for processing and analysis, and then sent to the management terminal (10); the management terminal (10) sends the control command to the corresponding front-end operating device through the Internet of Things back-end monitoring system, the information communication module (9) and the data acquisition control module in sequence; The front-end sensing device includes an in-duct air pressure sensor (5) of the smoke exhaust duct, an out-duct air pressure sensor (7) of the smoke exhaust duct, a temperature sensor (11) and an air velocity tester (6). The in-duct air pressure sensor (5), the temperature sensor (11) and the air velocity tester (6) are all installed in the smoke exhaust duct, and the out-duct air pressure sensor (7) is installed outside the smoke exhaust duct; The front-end operating device includes a smoke exhaust valve (13) and a fan (14), A plurality of smoke exhaust openings (4) are arranged at intervals in the smoke exhaust duct. A smoke exhaust valve (13) is arranged in the smoke exhaust opening (4). A section of the smoke exhaust duct between every two adjacent smoke exhaust openings (4) is a smoke exhaust duct section. A cross-section perpendicular to the central axis of the smoke exhaust duct in each smoke exhaust duct section is used as a test section (2). An air velocity tester (6), an in-duct air pressure sensor (5) and a temperature sensor (11) are arranged in each test section (2). The in-duct air pressure sensor (5) and the temperature sensor (11) are located at the center of the corresponding test section (2). The distance between adjacent test sections (2) is equal to the distance between adjacent smoke exhaust openings (4), The air velocity tester (6) is a cross-shaped air velocity tester. The cross-shaped air velocity tester includes two intersecting installation pipes, and a plurality of air velocity sensors are connected to the windward side and the leeward side of the pipe wall of the installation pipe. The air velocity sensors on the windward side and the leeward side are arranged in sequence along the extending direction of the corresponding installation pipe at equal intervals. The average value of the measured values of the air velocity sensors on the windward side is the average total pressure, and the average value of the measured values of the air velocity sensors on the leeward side is the average static pressure. The average air velocity at the corresponding test section (2) is obtained according to the pressure difference between the average total pressure and the average static pressure, The distance between every two adjacent smoke exhaust valves (13) in the smoke exhaust duct is 120 m, and the horizontal distance between the test sections (2) is 120 m; According to the air pressure in the smoke exhaust duct section monitored by the in-duct air pressure sensor (5) of the smoke exhaust duct, the air pressure outside the smoke exhaust duct monitored by the out-duct air pressure sensor (7) of the smoke exhaust duct, the air velocity of the smoke exhaust duct section monitored by the air velocity tester (6), and the temperature measurement value measured by the temperature sensor (11) in the smoke exhaust duct section, and the following formula, the air leakage coefficient μ of the smoke exhaust opening is obtained: where, i represents the serial number of the smoke exhaust duct section; Q i : represents the air volume of the i-th segmented smoke exhaust duct, Q i+1 : represents the air volume of the (i + 1)-th segmented smoke exhaust duct; the air volume of the segmented smoke exhaust duct is equal to the product of the wind speed of the segmented smoke exhaust duct and the cross-sectional area S of the smoke exhaust duct; P i : represents the differential air pressure of the i-th section of the smoke exhaust duct, P i = P′ i - P′, P′ i represents the air pressure within the i-th section of the smoke exhaust duct, and P′ represents the air pressure outside the smoke exhaust duct; A: represents the area of the smoke exhaust opening; ρ i : Gas density in the i-th section of the smoke exhaust duct The gas density is obtained according to the following gas state equation: P = ρ i RT i Among them, the standard atmospheric pressure P = 101325 Pa; T i represents the temperature measurement value of the i-th section of the smoke exhaust duct; R is the gas constant, It also includes the following steps: The friction coefficient λ is calculated by the following formula: where, S: the cross-sectional area of the smoke exhaust duct; l: the distance between the smoke exhaust openings; d: the hydraulic diameter of the smoke exhaust duct; P i : The differential wind pressure of the i-th segmented smoke exhaust duct, P i = P′ i - P′, P′ i represents the differential wind pressure of the i-th segmented smoke exhaust duct, P′ represents the wind pressure outside the smoke exhaust duct; P i+1 : The differential wind pressure of the i-th smoke exhaust duct, P i+1 = P′ i+1 - P′, P′ i+1 represents the wind pressure inside the (i + 1)-th segmented smoke exhaust duct; Based on the air leakage coefficient μ of the smoke exhaust opening and the friction coefficient λ, the overall friction coefficient ∈ of the smoke exhaust duct is calculated; 2. A method for health monitoring of a highway tunnel smoke exhaust duct based on the Internet of Things, which utilizes the health monitoring system of a highway tunnel smoke exhaust duct based on the Internet of Things described in claim 1, characterized in that, It includes the following steps: Step 1. Select the first smoke exhaust valve (13) as the current smoke exhaust valve (13); Step 2: The Internet of Things backend monitoring system starts recording: the curve of the air pressure in the smoke exhaust duct section monitored by the air pressure sensor (5) in the smoke exhaust duct corresponding to the current smoke exhaust valve (13) changing with time and the curve of the wind speed in the smoke exhaust duct section monitored by the anemometer (6) changing with time; Step 3: The Internet of Things backend monitoring system sends an opening or closing execution signal to the current smoke exhaust valve (13) once; Step 4: When there is no turning point in the curve of the air pressure in the corresponding smoke exhaust duct section changing with time or the curve of the wind speed in the smoke exhaust duct section changing with time, the Internet of Things backend monitoring system records the serial number of the corresponding smoke exhaust valve (13) and executes Step 5. If there is a turning point in the curve of the air pressure in the smoke exhaust duct section changing with time and the curve of the wind speed in the smoke exhaust duct section changing with time, the next smoke exhaust valve (13) is taken as the current smoke exhaust valve (13) and Step 2 is returned until all smoke exhaust valves (13) are traversed; Step 5: The Internet of Things backend monitoring system determines the location where the abnormal smoke exhaust valve (13) is located according to the product of the serial number of the smoke exhaust valve (13) and the distance between the smoke exhaust valves (13), and sends the location where the abnormal smoke exhaust valve (13) is located to the management terminal (10). Then, the next smoke exhaust valve (13) is taken as the current smoke exhaust valve (13) and Step 2 is returned until all smoke exhaust valves (13) are traversed.

3. A health monitoring method for a highway tunnel smoke exhaust duct based on the Internet of Things, using the health monitoring system for a highway tunnel smoke exhaust duct based on the Internet of Things described in claim 1, characterized in that, It includes the following steps: Step 1: Select the first smoke exhaust valve (13) as the current smoke exhaust valve (13); Step 2: The Internet of Things backend monitoring system starts recording: the curve of the air pressure in the smoke exhaust duct section monitored by the air pressure sensor (5) in the smoke exhaust duct corresponding to the current smoke exhaust valve (13) changing with time and the curve of the wind speed in the smoke exhaust duct section monitored by the anemometer (6) changing with time; Step 3: Send an opening execution signal to the current smoke exhaust valve (13) once; Step 4: When there is no turning point in the curve of the air pressure in the corresponding smoke exhaust duct section changing with time or the curve of the wind speed in the smoke exhaust duct section changing with time, then Step 5 is executed. If there is a turning point in the curve of the air pressure in the smoke exhaust duct section changing with time and the curve of the wind speed in the smoke exhaust duct section changing with time, Step 5 is directly executed; then the next smoke exhaust valve (13) is taken as the current smoke exhaust valve (13) and Step 2 is returned until all smoke exhaust valves (13) are traversed; Step 5: The Internet of Things backend monitoring system sends a closing execution signal to the current smoke exhaust valve (13) once; Step 6: When there is no turning point in the curve of the air pressure in the corresponding smoke exhaust duct section changing with time or the curve of the wind speed in the smoke exhaust duct section changing with time, the Internet of Things backend monitoring system records the serial number of the corresponding smoke exhaust valve (13) and executes Step 7. If there is a turning point in the curve of the air pressure in the smoke exhaust duct section changing with time and the curve of the wind speed in the smoke exhaust duct section changing with time, the next smoke exhaust valve (13) is taken as the current smoke exhaust valve (13) and Step 2 is returned until all smoke exhaust valves (13) are traversed; Step 7: The IoT backend monitoring system determines the location of the abnormal smoke exhaust valve (13) based on the product of the serial number of the smoke exhaust valve (13) and the spacing of the smoke exhaust valves (13), sends the location of the abnormal smoke exhaust valve (13) to the management terminal (10), then takes the next smoke exhaust valve (13) as the current smoke exhaust valve (13) and returns to Step 2 until all smoke exhaust valves (13) are traversed.

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