A highway tunnel harmful gas concentration on-line monitoring system and method

Abstract

The application relates to the technical field of harmful gas monitoring, and discloses a highway tunnel harmful gas concentration online monitoring system and method, which comprises the following modules: a sensor layout module, which lays out sensors based on historical harmful gas concentration detection data; a data acquisition module, which acquires harmful gas concentration, environmental parameters, traffic flow and sensor position data; a data comparison module, which compares the harmful gas concentration with a highest concentration threshold value, and generates a highest warning level if the concentration reaches the threshold value; a data processing module, which adjusts the harmful gas concentration according to the environmental parameters and the traffic flow data when the concentration is lower than the highest threshold value, and determines the warning levels of different positions based on the sensor positions; and a warning control module, which performs online warning and controls ventilation according to the warning levels. The application realizes optimized sensor layout, accurate concentration data correction and spatially differentiated hierarchical warning, and improves the accuracy of tunnel harmful gas monitoring.

Description

Technical Field

[0001] This invention relates to the field of hazardous gas monitoring technology, and in particular to an online monitoring system and method for hazardous gas concentration in highway tunnels. Background Technology

[0002] As a semi-enclosed space, highway tunnels are prone to the accumulation of various harmful gases emitted by motor vehicles during operation, which cannot effectively disperse. When the concentration of these harmful gases exceeds safety limits, it not only seriously threatens the health and safety of drivers and passengers but may also trigger major safety accidents such as explosions and fires. Therefore, real-time and accurate online monitoring of harmful gas concentrations within tunnels, and timely implementation of control measures such as ventilation based on the monitoring results, are crucial for ensuring the safe operation of highway tunnels.

[0003] However, existing highway tunnel hazardous gas monitoring systems suffer from the following technical shortcomings: sensor deployment lacks scientific basis; monitoring data is severely affected by environmental factors, resulting in insufficient accuracy; the early warning mechanism is simplistic, lacking tiered and spatially differentiated early warning capabilities; and ventilation control and monitoring / early warning systems lack effective linkage. Therefore, there is an urgent need for an online monitoring system and method for hazardous gas concentrations in highway tunnels to achieve accurate monitoring of hazardous gases in tunnels. Summary of the Invention

[0004] The purpose of this invention is to provide an online monitoring system and method for the concentration of harmful gases in highway tunnels, aiming to solve one or more of the above-mentioned problems.

[0005] This invention provides an online monitoring system for harmful gas concentrations in highway tunnels, the system comprising: The sensor deployment module is configured to acquire historical hazardous gas concentration detection data of highway tunnels, determine the sensor deployment spacing based on the historical hazardous gas concentration detection data, and deploy the sensor group according to the deployment spacing. The data acquisition module is configured to acquire harmful gas concentration data, environmental parameter data, traffic flow data, and sensor location data based on the sensor group; The data comparison module is configured to compare the harmful gas concentration data with the highest concentration threshold. If the harmful gas concentration data is greater than or equal to the highest concentration threshold, a harmful gas warning level of the highest warning level is generated. The data processing module is configured to process the harmful gas concentration data according to the environmental parameter data and traffic flow data if the harmful gas concentration data is less than the highest concentration threshold, and determine the harmful gas warning level of each sensor group location based on the sensor location data. The early warning control module is configured to issue an online early warning based on the warning level of the harmful gas and to control the ventilation mechanism to ventilate.

[0006] Preferably, the sensor deployment module determines the sensor deployment spacing based on the historical hazardous gas concentration detection data, including: The historical hazardous gas concentration detection data is compared with the concentration limit. If the historical hazardous gas concentration detection data is greater than the concentration limit, the deployment spacing is set as the first deployment spacing. If the historical hazardous gas concentration detection data is less than or equal to the concentration limit, then the deployment spacing is set as the second deployment spacing; wherein, the first deployment spacing is less than the second deployment spacing.

[0007] Preferably, the sensor group includes a gas concentration sensor group, an environmental parameter sensor group, a traffic flow detection group, and a positioning calibration group. The gas concentration sensor group is used to collect harmful gas concentration data; the environmental parameter sensor group is used to collect environmental parameter data; the traffic flow detection group is used to collect traffic flow data; and the positioning calibration group is used to collect sensor location data.

[0008] Preferably, the harmful gas concentration data includes: CO concentration, NO2 concentration, SO2 concentration, and VOCs concentration; The environmental parameter data includes: temperature, humidity, air pressure, and wind speed data; The traffic flow data includes: vehicle flow and vehicle speed data; The sensor location data includes the sensor's spatial coordinate data.

[0009] Preferably, the data comparison module compares the harmful gas concentration data with the highest concentration threshold, including: The maximum concentration thresholds include the maximum concentration thresholds for CO, NO2, SO2, and VOCs. The concentration data of each harmful gas in the harmful gas concentration data is compared with the corresponding highest concentration threshold. If the concentration data of one of the harmful gases is greater than or equal to the corresponding highest concentration threshold, the harmful gas warning level is generated as the highest warning level. If the concentration data of all harmful gases is less than the corresponding highest concentration threshold, the harmful gas concentration data will be transmitted to the data processing module for processing.

[0010] Preferably, the data processing module processes the harmful gas concentration data based on the environmental parameter data and traffic flow data, including: The environmental parameter data and traffic flow data are processed to generate the environmental parameter impact degree and traffic flow impact degree; The harmful gas concentration data is adjusted once based on the influence of the environmental parameters, and then adjusted a second time based on the influence of traffic flow to obtain the adjusted harmful gas concentration data.

[0011] Preferably, the data processing module processes the environmental parameter data and traffic flow data to generate environmental parameter impact degree and traffic flow impact degree, including: Obtain preset standard environmental parameter benchmark values ​​and standard traffic flow benchmark values; the standard environmental parameter benchmark values ​​include standard temperature values, standard humidity values, standard air pressure values, and standard wind speed values; the standard traffic flow benchmark values ​​include standard vehicle flow values ​​and standard vehicle speed values; The relative deviation of the environmental parameters between the standard environmental parameter benchmark value and the environmental parameter data is determined, and the environmental parameter influence degree is obtained by weighted summation of the relative environmental parameter deviations. The relative deviation of traffic flow between the standard traffic flow benchmark value and the traffic flow data is determined, and the traffic flow impact is obtained by weighted summation of the relative traffic flow deviation.

[0012] Preferably, the data processing module adjusts the hazardous gas concentration data once based on the influence of the environmental parameters, and then adjusts the hazardous gas concentration data a second time based on the influence of traffic flow, to obtain the adjusted hazardous gas concentration data. One adjustment process is: harmful gas concentration data × (1 + environmental parameter impact). The second adjustment process is as follows: the concentration data of harmful gases after the first adjustment × (1 + traffic flow impact).

[0013] Preferably, the data processing module determines the hazardous gas warning level for the location of each sensor group based on the sensor location data, including: The highway tunnel is divided into edge sections, transition sections, and middle sections. The edge sections are located at both ends of the highway tunnel, the middle sections are located in the middle of the highway tunnel, and the transition sections are located between the edge sections and the middle sections. Each of the edge sections, transition sections, and middle sections has the same length. Obtain preset standard hazardous gas reference values, which include standard CO concentration, standard NO2 concentration, standard SO2 concentration, and standard VOCs concentration; Determine the relative deviation of hazardous gas concentration between the standard hazardous gas reference value and the hazardous gas concentration data, determine the type of hazardous gas corresponding to the maximum value in the relative deviation of hazardous gas concentration, and set the hazardous gas concentration data corresponding to the type of hazardous gas with the maximum value as the hazardous gas warning concentration. The first, second, and third warning concentrations are set according to the types of hazardous gases corresponding to the maximum values. The initial hazardous gas warning level is determined by comparing the hazardous gas warning concentration with the first warning concentration, the second warning concentration, and the third warning concentration. The location of the sensor group is determined based on the sensor location data, and the initial hazardous gas warning level is adjusted based on the location of the sensor group to obtain the hazardous gas warning level. If the sensor array is located at an edge segment, the initial hazardous gas warning level will be adjusted down one level. If the sensor array is located in a transition zone, the initial hazardous gas warning level will not be adjusted. If the sensor group is located in the middle section, the initial hazardous gas warning level will be adjusted upward by one level.

[0014] This invention also discloses an online monitoring method for harmful gas concentrations in highway tunnels, applied to the aforementioned online monitoring system for harmful gas concentrations in highway tunnels. The method includes: Historical hazardous gas concentration detection data of highway tunnels are obtained, the sensor deployment spacing is determined based on the historical hazardous gas concentration detection data, and the sensor group is deployed according to the deployment spacing. Based on the sensor array, data on harmful gas concentration, environmental parameters, traffic flow, and sensor location are acquired. The harmful gas concentration data is compared with the highest concentration threshold. If the harmful gas concentration data is greater than or equal to the highest concentration threshold, the harmful gas warning level is generated as the highest warning level. If the concentration data of the harmful gas is less than the highest concentration threshold, the concentration data of the harmful gas is processed according to the environmental parameter data and traffic flow data, and the warning level of the harmful gas at the location of each sensor group is determined based on the sensor location data. Online warnings are issued based on the aforementioned hazardous gas warning levels, and ventilation systems are controlled to provide ventilation.

[0015] Compared with existing technologies, the advantages of this invention are as follows: By determining the sensor deployment spacing based on historical data, this invention achieves optimized allocation of sensor resources, improving the targeting and economy of the monitoring system. By introducing environmental parameters and traffic flow data for dual adjustment of concentration data, the accuracy and reliability of hazardous gas concentration monitoring are significantly improved. Through a dynamic early warning mechanism combining multi-level warning thresholds and spatial location, precise and tiered hazardous gas early warnings are achieved. The automatic linkage between early warning and ventilation is realized through the early warning control module, significantly improving the response speed and automation level of hazardous gas management in tunnels. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0017] Figure 1 This is a functional block diagram of an online monitoring system for harmful gas concentration in highway tunnels according to the present invention; Figure 2 This is a flowchart illustrating an online monitoring method for harmful gas concentrations in highway tunnels according to the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0019] like Figure 1 As shown, the present invention provides an online monitoring system for the concentration of harmful gases in highway tunnels, the system comprising: The sensor deployment module is configured to acquire historical hazardous gas concentration detection data of highway tunnels, determine the sensor deployment spacing based on the historical hazardous gas concentration detection data, and deploy the sensor group according to the deployment spacing. The data acquisition module is configured to acquire harmful gas concentration data, environmental parameter data, traffic flow data, and sensor location data based on the sensor group; The data comparison module is configured to compare the harmful gas concentration data with the highest concentration threshold. If the harmful gas concentration data is greater than or equal to the highest concentration threshold, a harmful gas warning level of the highest warning level is generated. The data processing module is configured to process the harmful gas concentration data according to the environmental parameter data and traffic flow data if the harmful gas concentration data is less than the highest concentration threshold, and determine the harmful gas warning level of each sensor group location based on the sensor location data. The early warning control module is configured to issue an online early warning based on the warning level of the harmful gas and to control the ventilation mechanism to ventilate.

[0020] This application optimizes sensor deployment based on historical hazardous gas concentration distribution patterns in tunnels, ensuring monitoring coverage and accuracy while avoiding redundant sensor deployment and reducing system construction costs. By combining environmental parameters and traffic flow data to correct the collected concentration data, the accuracy of hazardous gas concentration monitoring results can be effectively improved, reducing monitoring errors caused by environmental interference. Based on the hierarchical early warning results and linked control of ventilation mechanisms, the actual hazardous gas emission control needs of tunnels can be precisely matched, avoiding energy waste caused by ineffective ventilation. This achieves dynamic and accurate monitoring and efficient control of hazardous gases in highway tunnels, improving the safety and energy efficiency of highway tunnel operations.

[0021] In some embodiments of this application, the sensor deployment module determines the sensor deployment spacing based on the historical hazardous gas concentration detection data, including: comparing the historical hazardous gas concentration detection data with a concentration limit; if the historical hazardous gas concentration detection data is greater than the concentration limit, then setting the deployment spacing as a first deployment spacing; if the historical hazardous gas concentration detection data is less than or equal to the concentration limit, then setting the deployment spacing as a second deployment spacing; wherein, the first deployment spacing is less than the second deployment spacing.

[0022] Understandably, by comparing historical hazardous gas concentration detection data with concentration limits, the sensor deployment spacing is dynamically determined based on the historical pollution status of different tunnel sections. This allows for dense monitoring with smaller deployment spacing in areas with more severe historical pollution (historical concentrations greater than the concentration limits), and sparse monitoring with larger deployment spacing in areas with less severe historical pollution (historical concentrations less than or equal to the concentration limits). This ensures monitoring accuracy in high-risk areas while reducing equipment redundancy in low-risk areas, thus optimizing the allocation of sensor resources.

[0023] Specifically, before deploying sensors, the sensor deployment module first acquires historical hazardous gas concentration detection data for the highway tunnel. This historical data can be obtained from the historical records of existing monitoring equipment in the tunnel, or it can be obtained through on-site collection by temporarily deployed detection equipment within a preset time period. The historical hazardous gas concentration detection data includes hazardous gas concentration values ​​at multiple locations along the tunnel, which reflects the overall pollution status and distribution patterns of hazardous gases in various sections of the tunnel during historical operation.

[0024] After acquiring historical hazardous gas concentration detection data, the sensor deployment module compares it with preset concentration limits. These concentration limits serve as a benchmark for assessing the severity of hazardous gas pollution within the tunnel. The specific value can be set according to the hazardous gas concentration limits in relevant national standards, or it can be customized based on the actual operational safety requirements of the tunnel.

[0025] The comparison method is as follows: for each deployment location, the historical hazardous gas concentration detection data is compared one by one with the concentration limit. If the historical hazardous gas concentration detection data for a certain location is greater than the concentration limit, it indicates that the area where that location is located has a high concentration of hazardous gases in its historical operation, belonging to a high-risk area, requiring denser monitoring coverage. In this case, the sensor deployment spacing for that location is set as the first deployment spacing. If the historical hazardous gas concentration detection data for a certain location is less than or equal to the concentration limit, it indicates that the area where that location is located has a low concentration of hazardous gases in its historical operation, belonging to a low-risk area, requiring less dense monitoring coverage. In this case, the sensor deployment spacing for that location is set as the second deployment spacing. The first deployment spacing is smaller than the second deployment spacing to ensure that the sensor deployment density in high-risk areas is higher than in low-risk areas. After determining the deployment spacing for each location, the sensor deployment module deploys the sensor group according to the deployment spacing to complete the system deployment. After deployment, the system can enter the data acquisition phase through the deployed sensor group.

[0026] In some embodiments of this application, the sensor group includes a gas concentration sensor group, an environmental parameter sensor group, a traffic flow detection group, and a positioning calibration group. The gas concentration sensor group is used to collect harmful gas concentration data; the environmental parameter sensor group is used to collect environmental parameter data; the traffic flow detection group is used to collect traffic flow data; and the positioning calibration group is used to collect sensor location data.

[0027] In some embodiments of this application, the harmful gas concentration data includes: CO concentration, NO2 concentration, SO2 concentration, and VOCs concentration; the environmental parameter data includes: temperature, humidity, air pressure, and wind speed data; the traffic flow data includes: vehicle flow and vehicle speed data; and the sensor location data includes sensor spatial coordinate data.

[0028] Understandably, by setting up sensor groups containing multiple sensor types, comprehensive multi-dimensional data collection required for monitoring harmful gases within the tunnel can be achieved. Specifically, the gas concentration sensor group directly collects concentration data of various harmful gases, serving as the core basis for early warning judgment; the environmental parameter sensor group collects environmental data such as temperature, humidity, air pressure, and wind speed, providing a data foundation for subsequent correction of environmental interference; the traffic flow detection group collects vehicle flow and speed data, providing a data foundation for subsequent correction of traffic interference; and the positioning and calibration group collects sensor spatial coordinate data, providing a location basis for subsequent spatially differentiated early warning. These four types of sensor groups work together to provide complete data input for the data processing module and the early warning control module.

[0029] In some embodiments of this application, the data comparison module compares the hazardous gas concentration data with the highest concentration threshold, including: the highest concentration threshold includes the highest CO concentration threshold, the highest NO2 concentration threshold, the highest SO2 concentration threshold, and the highest VOCs concentration threshold; the concentration data corresponding to each hazardous gas in the hazardous gas concentration data is compared with the corresponding highest concentration threshold; if the concentration data corresponding to one hazardous gas is greater than or equal to the corresponding highest concentration threshold, then a hazardous gas warning level of the highest warning level is generated; if the concentration data corresponding to all hazardous gases is less than the corresponding highest concentration threshold, then the hazardous gas concentration data is transmitted to the data processing module for processing.

[0030] In this embodiment, when the concentration of any harmful gas reaches or exceeds its corresponding maximum concentration threshold, it indicates that the gas concentration in the tunnel is in an extremely dangerous state. No further fine-tuning or grading is required; the highest warning level is directly generated to trigger the fastest response. Only when the concentrations of all harmful gases are below their respective maximum thresholds is the data transmitted to the data processing module for further adjustment and grading warnings. This two-level processing mechanism ensures the fastest response speed in the highest-risk scenarios while reducing the computational burden on the data processing module under non-extreme conditions.

[0031] In some embodiments of this application, the data processing module processes the hazardous gas concentration data based on the environmental parameter data and traffic flow data, including: processing the environmental parameter data and traffic flow data to generate environmental parameter influence degree and traffic flow influence degree; adjusting the hazardous gas concentration data once based on the environmental parameter influence degree; and adjusting the hazardous gas concentration data a second time based on the traffic flow influence degree to obtain adjusted hazardous gas concentration data.

[0032] Understandably, by eliminating the interference of environmental parameters and traffic flow on the detection data of harmful gas concentrations, the adjusted concentration data can more accurately reflect the actual level of harmful gas pollution within the tunnel. Specifically, environmental parameters such as temperature, humidity, air pressure, and wind speed, as well as traffic flow parameters such as vehicle volume and speed, all significantly affect the diffusion, transport, and accumulation of harmful gases, causing the concentration data directly collected by sensors to fail to accurately characterize the actual degree of pollution. This invention calculates the influence of environmental parameters and traffic flow separately, and performs two progressive adjustments on the original concentration data, removing the interference of environmental and traffic factors from the detection data. This yields adjusted concentration data that more accurately reflects the true pollution situation, providing an accurate data foundation for subsequent graded early warning systems.

[0033] In some embodiments of this application, the data processing module processes the environmental parameter data and traffic flow data to generate environmental parameter impact and traffic flow impact, including: obtaining preset standard environmental parameter benchmark values ​​and standard traffic flow benchmark values; the standard environmental parameter benchmark values ​​include standard temperature values, standard humidity values, standard air pressure values, and standard wind speed values; the standard traffic flow benchmark values ​​include standard vehicle flow values ​​and standard vehicle speed values; determining the relative deviation of environmental parameters between the standard environmental parameter benchmark values ​​and the environmental parameter data, and performing a weighted summation of the relative environmental parameter deviations to obtain the environmental parameter impact; determining the relative deviation of traffic flow between the standard traffic flow benchmark values ​​and the traffic flow data, and performing a weighted summation of the relative traffic flow deviations to obtain the traffic flow impact.

[0034] It is understandable that the four environmental sub-parameters (temperature, humidity, air pressure, and wind speed) and the two traffic sub-parameters (traffic flow and vehicle speed) are synthesized into a single comprehensive quantitative index, namely, the influence degree of environmental parameters and the influence degree of traffic flow. However, because the units and magnitudes of the various environmental and traffic flow parameters differ (e.g., temperature is in degrees Celsius, wind speed in meters per second), they cannot be directly added together to characterize the comprehensive influence. This invention introduces standard environmental parameter benchmark values ​​and standard traffic flow benchmark values, calculates the relative deviations of each sub-parameter separately, and then synthesizes the multidimensional parameters into a single influence index through weighted summation. This achieves unified quantification and convenient calculation of the influence of environmental and traffic factors on concentration, facilitating subsequent quantitative correction of concentration data.

[0035] Specifically, firstly, preset standard environmental parameter benchmark values ​​and standard traffic flow benchmark values ​​are obtained. The standard environmental parameter benchmark values ​​include standard temperature, standard humidity, standard air pressure, and standard wind speed values, representing the ideal environmental state of the tunnel under standard operating conditions, where environmental factors do not cause additional interference to the harmful gas concentration detection data. The standard traffic flow benchmark values ​​include standard vehicle volume and standard vehicle speed values, representing the ideal traffic state of the tunnel under standard operating conditions, where traffic factors do not cause additional interference to the harmful gas concentration detection data. The specific values ​​of these standard benchmarks can be preset and stored in the system based on tunnel design specifications, historical statistical averages, or experimental calibration results.

[0036] Secondly, the relative deviations of environmental parameters between the standard environmental parameter baseline values ​​and the actual environmental parameter data collected by the data acquisition module are determined. Specifically, the relative deviations between the standard temperature value and the actual collected temperature value, the standard humidity value and the actual collected humidity value, the standard air pressure value and the actual collected air pressure value, and the standard wind speed value and the actual collected wind speed value are calculated. Each relative deviation can be calculated by dividing the difference by the standard value to obtain a dimensionless relative deviation value, thus eliminating unit differences between different parameters.

[0037] Then, the relative deviations of the four environmental parameters are weighted and summed to obtain the degree of influence of each environmental parameter. Weighted summation involves assigning a corresponding weight coefficient to each environmental parameter, multiplying each relative deviation by its corresponding weight coefficient, and then summing the results. The specific values ​​of each weight coefficient can be pre-set based on experimental test results of the degree of influence of each environmental parameter on the diffusion of harmful gases. For example, wind speed usually has a greater impact on the diffusion of harmful gases and can be assigned a higher weight; humidity has a relatively smaller impact and can be assigned a lower weight.

[0038] Similarly, the relative deviation of traffic flow between the standard traffic flow benchmark value and the actual traffic flow data collected by the data acquisition module is determined. Specifically, the relative deviation between the standard traffic flow value and the actual collected traffic flow value, and the relative deviation between the standard vehicle speed value and the actual collected vehicle speed value are calculated separately. Subsequently, the two relative deviations of traffic flow are weighted and summed to obtain the traffic flow impact degree. The specific values ​​of each weight coefficient in the weighted summation can be preset based on the experimental test results of the influence of traffic flow and vehicle speed on the intensity of harmful gas emissions. In this way, both the environmental parameter impact degree and the traffic flow impact degree are dimensionless values, which can intuitively reflect the overall deviation of the current environmental and traffic conditions from the standard state. The greater the deviation, the greater the impact degree value, and the greater the correction range for the harmful gas concentration data.

[0039] It is understood that the relative deviations of environmental parameters and traffic flow in this embodiment are positive and negative. For example, when the actual collected temperature value is less than the standard temperature value, the relative deviation between the two is negative.

[0040] In some embodiments of this application, the data processing module adjusts the harmful gas concentration data once based on the influence of the environmental parameters, and then adjusts the harmful gas concentration data a second time based on the influence of traffic flow, to obtain the adjusted harmful gas concentration data. One adjustment process is: harmful gas concentration data × (1 + environmental parameter impact). The second adjustment process is as follows: the concentration data of harmful gases after the first adjustment × (1 + traffic flow impact).

[0041] In some embodiments of this application, the data processing module determines the hazardous gas warning level for the location of each sensor group based on the sensor location data, including: The highway tunnel is divided into edge sections, transition sections, and middle sections. The edge sections are located at both ends of the highway tunnel, the middle sections are located in the middle of the highway tunnel, and the transition sections are located between the edge sections and the middle sections. Each of the edge sections, transition sections, and middle sections has the same length. Obtain preset standard hazardous gas reference values, which include standard CO concentration, standard NO2 concentration, standard SO2 concentration, and standard VOCs concentration; Determine the relative deviation of hazardous gas concentration between the standard hazardous gas reference value and the hazardous gas concentration data, determine the type of hazardous gas corresponding to the maximum value in the relative deviation of hazardous gas concentration, and set the hazardous gas concentration data corresponding to the type of hazardous gas with the maximum value as the hazardous gas warning concentration. The first, second, and third warning concentrations are set according to the types of hazardous gases corresponding to the maximum values. The initial hazardous gas warning level is determined by comparing the hazardous gas warning concentration with the first warning concentration, the second warning concentration, and the third warning concentration. The location of the sensor group is determined based on the sensor location data, and the initial hazardous gas warning level is adjusted based on the location of the sensor group to obtain the hazardous gas warning level. If the sensor array is located at an edge segment, the initial hazardous gas warning level will be adjusted down one level. If the sensor array is located in a transition zone, the initial hazardous gas warning level will not be adjusted. If the sensor group is located in the middle section, the initial hazardous gas warning level will be adjusted upward by one level.

[0042] Understandably, by implementing spatially differentiated graded early warning for different sections of a tunnel, this addresses the problem that existing technologies with uniform early warning standards cannot reflect the actual risk differences at different locations within the tunnel. Because the ends (edge ​​sections) of a highway tunnel are close to the entrance and have frequent air exchange with the outside, harmful gases easily diffuse, resulting in relatively lower actual risks. Conversely, the middle section (middle section) is furthest from the entrance, has the worst air circulation, and harmful gases tend to accumulate most easily, resulting in relatively higher actual risks. The risk level of the transition section falls between these two. This invention first determines the initial early warning level based on harmful gas concentration data, and then dynamically adjusts the initial early warning level upwards or downwards according to the location of the sensor array. This ensures that the early warning level matches the actual risk level of different sections of the tunnel, avoiding both the "false alarm" problem caused by a uniform standard in the edge sections and the "missed alarm" problem in the middle sections, thus achieving accurate early warning.

[0043] In this embodiment, the hazardous gas warning concentration is compared with the first warning concentration, the second warning concentration, and the third warning concentration to determine the initial hazardous gas warning level. Specifically: if the hazardous gas warning concentration is less than the first warning concentration, the initial hazardous gas warning level is set to a low warning level; if the hazardous gas warning concentration is greater than or equal to the first warning concentration and less than the second warning concentration, the initial hazardous gas warning level is set to a medium warning level; if the hazardous gas warning concentration is greater than or equal to the second warning concentration and less than the third warning concentration, the initial hazardous gas warning level is set to a high warning level; and if the hazardous gas warning concentration is greater than or equal to the third warning concentration, the initial hazardous gas warning level is set to the highest warning level.

[0044] In this embodiment, the hazardous gas warning levels include low warning level, medium warning level, high warning level, and highest warning level. When the initial hazardous gas warning level is adjusted upward, if the initial hazardous gas warning level is the highest warning level, no further adjustment will be made; when the initial hazardous gas warning level is adjusted downward, if the initial hazardous gas warning level is the low warning level, no further adjustment will be made.

[0045] like Figure 2 As shown, the present invention also discloses an online monitoring method for harmful gas concentration in highway tunnels, applied to the aforementioned online monitoring system for harmful gas concentration in highway tunnels. The method includes: Historical hazardous gas concentration detection data of highway tunnels are obtained, the sensor deployment spacing is determined based on the historical hazardous gas concentration detection data, and the sensor group is deployed according to the deployment spacing. Based on the sensor array, data on harmful gas concentration, environmental parameters, traffic flow, and sensor location are acquired. The harmful gas concentration data is compared with the highest concentration threshold. If the harmful gas concentration data is greater than or equal to the highest concentration threshold, the harmful gas warning level is generated as the highest warning level. If the concentration data of the harmful gas is less than the highest concentration threshold, the concentration data of the harmful gas is processed according to the environmental parameter data and traffic flow data, and the warning level of the harmful gas at the location of each sensor group is determined based on the sensor location data. Online warnings are issued based on the aforementioned hazardous gas warning levels, and ventilation systems are controlled to provide ventilation.

[0046] This application optimizes sensor deployment based on the actual tunnel environment and traffic conditions, avoiding resource waste due to over-deployment or blind spots due to insufficient deployment, ensuring comprehensive monitoring coverage. Simultaneously, it combines environmental and traffic flow information to comprehensively determine the warning level. Compared to methods relying solely on gas concentration, the warning results more accurately reflect the actual risk of harmful gas accumulation in the tunnel, enabling targeted control of ventilation systems. This ensures timely removal of harmful gases to guarantee tunnel safety while avoiding unnecessary ventilation energy consumption, thus improving the economy and safety of tunnel operation.

[0047] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program goods. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program goods embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0048] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program goods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0049] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0050] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An online monitoring system for harmful gas concentration in highway tunnels, characterized in that, The system includes: The sensor deployment module is configured to acquire historical hazardous gas concentration detection data of highway tunnels, determine the sensor deployment spacing based on the historical hazardous gas concentration detection data, and deploy the sensor group according to the deployment spacing. The data acquisition module is configured to acquire harmful gas concentration data, environmental parameter data, traffic flow data, and sensor location data based on the sensor group; The data comparison module is configured to compare the harmful gas concentration data with the highest concentration threshold. If the harmful gas concentration data is greater than or equal to the highest concentration threshold, a harmful gas warning level of the highest warning level is generated. The data processing module is configured to process the harmful gas concentration data according to the environmental parameter data and traffic flow data if the harmful gas concentration data is less than the highest concentration threshold, and determine the harmful gas warning level of each sensor group location based on the sensor location data. The early warning control module is configured to issue an online early warning based on the warning level of the harmful gas and to control the ventilation mechanism to ventilate.

2. The online monitoring system for harmful gas concentration in highway tunnels according to claim 1, characterized in that, The sensor deployment module determines the sensor deployment spacing based on the historical hazardous gas concentration detection data, including: The historical hazardous gas concentration detection data is compared with the concentration limit. If the historical hazardous gas concentration detection data is greater than the concentration limit, the deployment spacing is set as the first deployment spacing. If the historical hazardous gas concentration detection data is less than or equal to the concentration limit, then the deployment spacing is set as the second deployment spacing; wherein, the first deployment spacing is less than the second deployment spacing.

3. The online monitoring system for harmful gas concentration in highway tunnels according to claim 1, characterized in that, The sensor group includes a gas concentration sensor group, an environmental parameter sensor group, a traffic flow detection group, and a positioning calibration group. The gas concentration sensor group is used to collect harmful gas concentration data; the environmental parameter sensor group is used to collect environmental parameter data; the traffic flow detection group is used to collect traffic flow data; and the positioning calibration group is used to collect sensor location data.

4. The online monitoring system for harmful gas concentration in highway tunnels according to claim 1, characterized in that, The harmful gas concentration data include: CO concentration, NO2 concentration, SO2 concentration, and VOCs concentration; The environmental parameter data includes: temperature, humidity, air pressure, and wind speed data; The traffic flow data includes: vehicle flow and vehicle speed data; The sensor location data includes the sensor's spatial coordinate data.

5. The online monitoring system for harmful gas concentration in highway tunnels according to claim 4, characterized in that, The data comparison module compares the harmful gas concentration data with the highest concentration threshold, including: The maximum concentration thresholds include the maximum concentration thresholds for CO, NO2, SO2, and VOCs. The concentration data of each harmful gas in the harmful gas concentration data is compared with the corresponding highest concentration threshold. If the concentration data of one of the harmful gases is greater than or equal to the corresponding highest concentration threshold, the harmful gas warning level is generated as the highest warning level. If the concentration data of all harmful gases is less than the corresponding highest concentration threshold, the harmful gas concentration data will be transmitted to the data processing module for processing.

6. The online monitoring system for harmful gas concentration in highway tunnels according to claim 1, characterized in that, The data processing module processes the harmful gas concentration data based on the environmental parameter data and traffic flow data, including: The environmental parameter data and traffic flow data are processed to generate the environmental parameter impact degree and traffic flow impact degree; The harmful gas concentration data is adjusted once based on the influence of the environmental parameters, and then adjusted a second time based on the influence of traffic flow to obtain the adjusted harmful gas concentration data.

7. The online monitoring system for harmful gas concentration in highway tunnels according to claim 6, characterized in that, The data processing module processes the environmental parameter data and traffic flow data to generate environmental parameter impact and traffic flow impact, including: Obtain preset standard environmental parameter benchmark values ​​and standard traffic flow benchmark values; the standard environmental parameter benchmark values ​​include standard temperature values, standard humidity values, standard air pressure values, and standard wind speed values; the standard traffic flow benchmark values ​​include standard vehicle flow values ​​and standard vehicle speed values; The relative deviation of the environmental parameters between the standard environmental parameter benchmark value and the environmental parameter data is determined, and the environmental parameter influence degree is obtained by weighted summation of the relative environmental parameter deviations. The relative deviation of traffic flow between the standard traffic flow benchmark value and the traffic flow data is determined, and the traffic flow impact is obtained by weighted summation of the relative traffic flow deviation.

8. The online monitoring system for harmful gas concentration in highway tunnels according to claim 7, characterized in that, The data processing module adjusts the hazardous gas concentration data once based on the influence of the environmental parameters, and then adjusts it a second time based on the influence of traffic flow, thus obtaining the adjusted hazardous gas concentration data. One adjustment process is: harmful gas concentration data × (1 + environmental parameter impact). The second adjustment process is as follows: the concentration data of harmful gases after the first adjustment × (1 + traffic flow impact).

9. The online monitoring system for harmful gas concentration in highway tunnels according to claim 8, characterized in that, The data processing module determines the hazardous gas warning level for each sensor group based on the sensor location data, including: The highway tunnel is divided into edge sections, transition sections, and middle sections. The edge sections are located at both ends of the highway tunnel, the middle sections are located in the middle of the highway tunnel, and the transition sections are located between the edge sections and the middle sections. Each of the edge sections, transition sections, and middle sections has the same length. Obtain preset standard hazardous gas reference values, which include standard CO concentration, standard NO2 concentration, standard SO2 concentration, and standard VOCs concentration; Determine the relative deviation of hazardous gas concentration between the standard hazardous gas reference value and the hazardous gas concentration data, determine the type of hazardous gas corresponding to the maximum value in the relative deviation of hazardous gas concentration, and set the hazardous gas concentration data corresponding to the type of hazardous gas with the maximum value as the hazardous gas warning concentration. The first, second, and third warning concentrations are set according to the types of hazardous gases corresponding to the maximum values. The initial hazardous gas warning level is determined by comparing the hazardous gas warning concentration with the first warning concentration, the second warning concentration, and the third warning concentration. The location of the sensor group is determined based on the sensor location data, and the initial hazardous gas warning level is adjusted based on the location of the sensor group to obtain the hazardous gas warning level. If the sensor array is located at an edge segment, the initial hazardous gas warning level will be adjusted down one level. If the sensor array is located in a transition zone, the initial hazardous gas warning level will not be adjusted. If the sensor group is located in the middle section, the initial hazardous gas warning level will be adjusted upward by one level.

10. A method for online monitoring of harmful gas concentration in highway tunnels, applied to the online monitoring system for harmful gas concentration in highway tunnels as described in any one of claims 1-9, characterized in that, The method includes: Historical hazardous gas concentration detection data of highway tunnels are obtained, the sensor deployment spacing is determined based on the historical hazardous gas concentration detection data, and the sensor group is deployed according to the deployment spacing. Based on the sensor array, data on harmful gas concentration, environmental parameters, traffic flow, and sensor location are acquired. The harmful gas concentration data is compared with the highest concentration threshold. If the harmful gas concentration data is greater than or equal to the highest concentration threshold, the harmful gas warning level is generated as the highest warning level. If the concentration data of the harmful gas is less than the highest concentration threshold, the concentration data of the harmful gas is processed according to the environmental parameter data and traffic flow data, and the warning level of the harmful gas at the location of each sensor group is determined based on the sensor location data. Online warnings are issued based on the aforementioned hazardous gas warning levels, and ventilation systems are controlled to provide ventilation.

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