Multi-dimensional cooperative tunnel harmful gas detection ventilation self-adaptive regulation and control method

Abstract

The invention discloses a multi-dimensional cooperative tunnel harmful gas detection ventilation self-adaptive regulation and control method, and relates to the technical field of tunnel engineering environment detection regulation and control, a data collection and preprocessing module is used for collecting and processing real-time data related to harmful gas, wind speed and wind direction in a tunnel, and a comprehensive prediction and regulation and control module is used for predicting the real-time data in the tunnel. The method comprises the following steps: predicting the concentration of harmful gas at each part of a tunnel, calculating and outputting a fan adjustment strategy according to the predicted concentration and the average value YHNavg of the concentration of the harmful gas, comprehensively evaluating the fan adjustment strategy and the standard exceeding degree of the harmful gas, calculating and outputting an early warning level YJ, giving a regulation and control suggestion, and utilizing a regulation and control execution module to carry out regulation and control according to the early warning level YJ and real-time data. According to the method, the concentration of the harmful gas can be monitored in real time, the ventilation strategy can be dynamically adjusted, the characteristics of the wind speed, the wind direction and the tunnel structure are comprehensively considered, and then the multi-dimensional cooperative tunnel harmful gas detection ventilation self-adaptive regulation and control method is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel engineering environment detection and control, and in particular to a multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method. Background Art

[0002] During the tunnel excavation process, gases in the rocks and soil, including methane and hydrogen sulfide, will be released into the tunnel. At the same time, harmful gases such as exhaust gas emitted by construction machinery and vehicles and carbon monoxide produced by incomplete combustion of oil will also accumulate in the tunnel. It is worth noting that long-term exposure to harmful gases will have a serious impact on the health of construction workers and even endanger their lives. In severe cases, it may cause safety accidents such as explosions and fires, causing significant losses to tunnel construction. In addition, poor air quality and low visibility in the tunnel will seriously affect driving safety and increase the risk of traffic accidents.

[0003] The adaptive control method of traditional tunnels is often implemented by the ventilation strategy of the ventilation system. However, most of the existing ventilation systems operate based on preset parameters and cannot be accurately controlled in real time according to the changes in the concentration of harmful gases in the tunnel. In addition, there are differences in the concentration of harmful gases, wind speed and ventilation conditions in different parts of the tunnel, but the existing system often adopts a unified ventilation strategy and ignores this difference. In addition, wind direction has a significant impact on the ventilation effect, but the existing system often ignores the wind direction factor, resulting in low ventilation efficiency under certain wind direction conditions. The existing system lacks a mechanism for comprehensively evaluating the system's control capabilities and the degree of harmful gas exceeding the standard, making it difficult to issue timely warnings and take effective measures. Summary of the invention

[0004] The purpose of the present invention is to provide a multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution, and the specific implementation steps are as follows: Step S1, using the data collection and preprocessing module to collect and process real-time data related to harmful gases, wind speed and wind direction in the tunnel; Step S2-1: Use the comprehensive prediction and control module to predict the concentration of harmful gases in various parts of the tunnel, and based on the concentration of harmful gases in various parts, output the average value YHN of the concentration of harmful gases that requires the use of long rail pushers and long tractors in various parts of the tunnel. avg , and perform adaptive regulation; Step S2-2: Based on the predicted concentration and the average concentration of harmful gases YHN avg , and combined with real-time data related to wind speed and wind direction, calculate the output fan adjustment strategy; Step S2-2, comprehensively evaluate the fan adjustment strategy and the degree of harmful gas exceeding the standard, calculate the output warning level YJ, and give control suggestions; Step S3: Using the control execution module, according to the warning level YJ and real-time data, carry out warning response and dynamically adjust the ventilation strategy, and execute adjustment measures.

[0006] Among them, the comprehensive prediction and control module includes a harmful gas concentration prediction and evaluation unit, a fan adjustment strategy unit based on the prediction results, and a comprehensive evaluation system overall operating status and determination warning level unit.

[0007] Optionally, the equipment used by the data collection and preprocessing module includes harmful gas sensors, wind speed sensors, wind direction sensors, and tunnel cross-section dimension measuring equipment; The equipment used in the comprehensive prediction and control module includes a data processing and analysis system; The equipment used by the control execution module includes ventilation system controller, construction guidance and emergency response equipment; The harmful gas sensor is used to detect the concentration of harmful gases in the tunnel in real time; The wind speed sensor is used to measure the wind speed at various locations in the tunnel; The wind direction sensor is used to determine the wind direction information in the tunnel; The tunnel cross-sectional dimension measuring device is used to obtain tunnel cross-sectional area data; The ventilation system controller is used to execute the fan adjustment strategy and control the operation of the ventilation system; The data processing and analysis system includes a computer, data processing software and an algorithm library, and is used to process real-time data, calculate predicted concentrations, adjust strategies and early warning indices; The construction guidance and emergency response equipment includes communication equipment, safety warning devices, emergency lighting and escape equipment, and is used for construction guidance and emergency response.

[0008] Optionally, the calculation formula of the harmful gas concentration prediction and evaluation unit is as follows: ; in: YHN i Predict the concentration value of harmful gases for the i-th tunnel location; FS i is the wind speed at the i-th tunnel location; KS i is the diffusion coefficient of the i-th tunnel part; NB i is the concentration variation factor of the i-th tunnel part; YHN prev，iis the concentration of harmful gases at the previous time point in the i-th tunnel part, YHN prev，i Reflects the concentration value of harmful gases in the same part of the tunnel in the previous test result; JM i is the cross-sectional area of ​​the i-th tunnel part; TF i is the ventilation efficiency coefficient of the ith tunnel location.

[0009] Optionally, the harmful gas concentration value YHN is predicted based on the i-th tunnel location of each location in the tunnel. i , the average concentration of harmful gases in the entire tunnel is YHN avg The calculation formula is as follows: YHN avg =(YHN1+YHN2+YHN3+......+YHN n ) / N; YHN avg is the average value of harmful gas concentration; YHN1 is the predicted concentration of harmful gases in the first tunnel, YHN2 is the predicted concentration of harmful gases in the second tunnel, YHN3 is the predicted concentration of harmful gases in the third tunnel, and YHN n Predict the concentration value of harmful gases for the nth tunnel location; N is the total number of tunnel sections, which reflects how many sections the entire tunnel is divided into; If the predicted harmful gas concentration value YHN of the i-th tunnel part i Greater than the average concentration of harmful gases YHN avg , a long-track pusher and a long tractor are used in this area.

[0010] Optionally, the wind direction adjustment factor T wind Adjust according to wind direction changes; Set A to indicate that the wind direction is consistent with the expected direction, use B to indicate that the wind direction is opposite to the expected direction, use C and θ to indicate that the wind direction has a deflection angle, and the wind direction adjustment factor T wind The wind direction change analysis formula is as follows: T wind =δ1, then A holds; T wind =δ2, then B holds; T wind =δ3, then C holds; T wind =δ3(θ), then the wind direction has a deflection angle θ; δ1, δ2, and δ3 are adjustment coefficients set according to specific wind direction conditions; If A and B are established, T wind Should take positive value; If C is established and the wind direction has a deflection angle θ, T wind It should vary with the size of the deflection angle.

[0011] Optionally, the calculation formula for formulating the fan adjustment strategy unit based on the prediction result is as follows: TL i =(YHN avg / YHN i ) a ×(FS opt / FS i ) bi × (1+T wind ); in: TL i Adjust the intensity value of the fan at the i-th tunnel location; a is the concentration ratio adjustment coefficient, which reflects the influence on the fan adjustment strength; FS opt is the optimal wind speed; bi is the wind speed sensitivity coefficient, which reflects the wind speed change on the fan adjustment force value TL of the i-th tunnel part i The degree of influence varies, and different tunnel parts have different wind speed sensitivities, so bi varies from part to part.

[0012] Optionally, the control benchmark index YJ based on the prediction and evaluation unit for harmful gas concentration and the unit for formulating a fan adjustment strategy based on the prediction result safe The calculation formula is as follows: ; TL max Adjust the maximum force for the fan; N is the total number of tunnel parts; YHN max It is the maximum concentration of harmful gases.

[0013] Optionally, the calculation formula for comprehensively evaluating the overall operating status of the system and determining the warning level unit is as follows: ; in: YJ is the warning level; The process of comprehensively evaluating the overall operating status of the system and determining the warning level unit is as follows: Taking into account the fan adjustment capacity and the degree of harmful gas concentration exceeding the standard, when the adjustment capacity is not enough to quickly reduce the concentration to a safe level, the warning level YJ rises.

[0014] Optionally, a control benchmark index YJ based on the warning level YJ safeThe regulation analysis is as follows: If the warning level YJ is lower than the control benchmark index YJ safe , it indicates that the current ventilation system control capability is sufficient to quickly and effectively reduce the concentration of harmful gases in various parts of the tunnel to a safe level, and the current control measures should be maintained; If the warning level YJ is higher than the control benchmark index YJ safe , it indicates that the current ventilation system control capability is not sufficient to quickly and effectively reduce the concentration of harmful gases in various parts of the tunnel to a safe level, and the diffusion coefficient KS of the i-th tunnel part should be dynamically adjusted. i and the ventilation efficiency coefficient TF of the i-th tunnel section i ,At the same time, the safety warning device executes early warning measures.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention realizes real-time and precise control of ventilation strategies by real-time monitoring of the concentration of harmful gases, wind speed and wind direction information at various parts of the tunnel, and calculating the predicted concentration by combining the prediction and evaluation unit of the concentration of harmful gases.

[0016] 2. The present invention adds a location identifier i to the calculation formula to distinguish parameters of different tunnel locations, thereby realizing differentiated ventilation strategies for different locations, thereby improving ventilation efficiency.

[0017] 3. The present invention formulates the wind direction adjustment factor T in the fan adjustment strategy unit based on the prediction results. wind , realizing adaptive adjustment to wind direction changes, effectively ensuring the effective operation of the ventilation system under different wind direction conditions.

[0018] 4. The overall operating status of the comprehensive evaluation system in the present invention is determined by calculating the warning level YJ through the comprehensive evaluation system control capability and the degree of harmful gas exceeding the standard, thereby providing a scientific basis for construction guidance and emergency response. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a method flow chart of the multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method; Figure 2 It is a schematic diagram of the structure of the comprehensive prediction and control module of the present invention; Figure 3 It is a schematic diagram of the division structure of the location identifier i in the tunnel in the present invention; Figure 4 It is a structural schematic diagram of the adaptive control method of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Regarding this multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method, it is different from the traditional detection and ventilation adaptive control method. The traditional tunnel ventilation system in the traditional detection and ventilation adaptive control method often adopts a ventilation strategy with fixed parameters, which is difficult to adapt to the complex and changeable environmental conditions in the tunnel, such as wind speed changes, uncertain wind direction, and differences in harmful gas concentrations in different parts. The algorithm unit can monitor the concentration of harmful gases in real time, dynamically adjust the ventilation strategy, and comprehensively consider the wind speed, wind direction and tunnel structure characteristics, thereby realizing a multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method.

[0022] For example, see Figures 1 to 4 This implementation provides a multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method, and the specific implementation steps are as follows: Step S1, using the data collection and preprocessing module to collect and process real-time data related to harmful gases, wind speed and wind direction in the tunnel; Step S2-1: Use the comprehensive prediction and control module to predict the concentration of harmful gases in various parts of the tunnel, and based on the concentration of harmful gases in various parts, output the average value YHN of the concentration of harmful gases that requires the use of long rail pushers and long tractors in various parts of the tunnel. avg , and perform adaptive regulation; Step S2-2: Based on the predicted concentration and the average concentration of harmful gases YHN avg , and combined with real-time data related to wind speed and wind direction, calculate the output fan adjustment strategy; Step S2-2, comprehensively evaluate the fan adjustment strategy and the degree of harmful gas exceeding the standard, calculate the output warning level YJ, and give control suggestions; Step S3, using the control execution module, according to the warning level YJ and real-time data, to carry out warning response and dynamically adjust the ventilation strategy, and execute adjustment measures.

[0023] Among them, the comprehensive prediction and control module includes a unit for predicting and evaluating the concentration of harmful gases, a unit for formulating fan adjustment strategies based on the prediction results, and a unit for comprehensively evaluating the overall operating status of the system and determining the warning level; The equipment used in the data collection and preprocessing module includes harmful gas sensors, wind speed sensors, wind direction sensors, and tunnel section dimension measuring equipment; The equipment used in the comprehensive prediction and control module includes data processing and analysis systems; The equipment used in the control execution module includes ventilation system controller, construction guidance and emergency response equipment; The harmful gas sensor is used to detect the concentration of harmful gases in the tunnel in real time; Wind speed sensors are used to measure wind speed at various locations in the tunnel; The wind direction sensor is used to determine the wind direction information in the tunnel; Tunnel cross-sectional dimension measuring equipment is used to obtain tunnel cross-sectional area data; The ventilation system controller is used to execute the fan adjustment strategy and control the operation of the ventilation system; The data processing and analysis system includes computers, data processing software and algorithm libraries, and is used to process real-time data, calculate predicted concentrations, adjust strategies and early warning indices; Construction guidance and emergency response equipment includes communication equipment, safety warning devices, emergency lighting and escape equipment, and is used for construction guidance and emergency response.

[0024] In this embodiment, the system combines the YHN i TL i The three calculation results of YHN and YJ have improved the intelligence level and operation efficiency of the tunnel ventilation system, and provided a strong guarantee for the control of harmful gases during tunnel construction and operation. i Predict the concentration of harmful gases for the i-th tunnel part. The algorithm unit can accurately predict the concentration of harmful gases in different parts of the tunnel under specific conditions. This prediction result is crucial for construction safety management because it can help the construction team identify potential risks of excessive harmful gases in advance and formulate corresponding prevention and control measures accordingly. TL i is the fan adjustment strength value of the i-th tunnel part. Through the result value of this unit, the construction team can formulate an accurate fan adjustment plan to quickly reduce the concentration of harmful gases and ensure the safety of construction personnel. YJ is the warning level. Through the result value of this unit, the construction team can timely understand the overall operation status and potential risks of the system and adjust the ventilation control strategy accordingly to ensure the safety of tunnel construction. And TL i The calculation results of YJ can also affect the feedback to YHN i Calculation and YHN i Diffusion coefficient KS of the i-th tunnel part in the algorithm unit iAnd the ventilation efficiency coefficient TFi of the i-th tunnel part is dynamically adjusted, so that the three algorithm units are interrelated and supportive of each other, and jointly realize the accurate prediction, dynamic regulation and timely warning of the concentration of harmful gases in the tunnel.

[0025] See also Figures 1 to 4 , the calculation formula for predicting and evaluating the harmful gas concentration unit is as follows: ; in: YHN i Predict the concentration value of harmful gases for the i-th tunnel location; FS i is the wind speed at the i-th tunnel location; KS i is the diffusion coefficient of the i-th tunnel part; NB i is the concentration variation factor of the i-th tunnel part; YHN prev，i is the concentration of harmful gases at the previous time point in the i-th tunnel part, YHN prev，i Reflects the concentration value of harmful gases in the same part of the tunnel in the previous test result; JM i is the cross-sectional area of ​​the i-th tunnel part; TF i is the ventilation efficiency coefficient of the ith tunnel location.

[0026] In this embodiment: first, the algorithm unit can more accurately predict the concentration of harmful gases in each part by comprehensively considering the specific parameters of each part in the tunnel. This refined prediction method helps to reduce errors and improve the accuracy of prediction, thereby providing a more reliable basis for subsequent ventilation control. Since the concentration of harmful gases in different parts of the tunnel is different, the traditional unified control method is often difficult to achieve the best effect. The unit for predicting and evaluating the concentration of harmful gases distinguishes the parameters of different parts, so that differentiated ventilation control strategies can be formulated for different parts. This differentiated control method can more effectively reduce the concentration of harmful gases and improve the overall efficiency of the ventilation system. Based on the prediction results of the harmful gas concentration unit, the corresponding safety average value can be calculated and set. When the predicted concentration exceeds the safety average value, the system can automatically issue a warning signal to prompt relevant personnel to take timely measures to prevent and control risks. This early warning mechanism helps to reduce the risks brought by excessive harmful gases and ensure the safety of construction and operations.

[0027] See also Figures 1 to 4 , wind direction adjustment factor T wind Adjust according to wind direction changes; Set A to indicate that the wind direction is consistent with the expected direction, use B to indicate that the wind direction is opposite to the expected direction, use C and θ to indicate that the wind direction has a deflection angle, and the wind direction adjustment factor T wind The wind direction change analysis formula is as follows: T wind =δ1, then A holds; T wind =δ2, then B holds; T wind =δ3, then C holds; T wind =δ3(θ), then the wind direction has a deflection angle θ; δ1, δ2, and δ3 are adjustment coefficients set according to specific wind direction conditions; If A and B are established, T wind Should take positive value; If C is established and the wind direction has a deflection angle θ, T wind It should vary with the size of the deflection angle; The calculation formula for the fan adjustment strategy unit based on the prediction results is as follows: TL i =(YHN avg / YHN i ) a ×(FS opt / FS i ) bi × (1+T wind ); in: TL i Adjust the intensity value of the fan at the i-th tunnel location; a is the concentration ratio adjustment coefficient, which reflects the influence on the fan adjustment strength; FS opt is the optimal wind speed; bi is the wind speed sensitivity coefficient, which reflects the wind speed change on the fan adjustment force value TL of the i-th tunnel part i The degree of influence varies, and different tunnel parts have different wind speed sensitivities, so bi varies from part to part.

[0028] In this embodiment, the algorithm unit formulates a fan adjustment strategy unit based on the prediction results, and introduces a wind direction adjustment factor T based on the prediction and evaluation of harmful gas concentration units. wind , realizing the adaptive control of wind direction for the fan adjustment strategy, by adjusting the wind direction adjustment factor T wind The value of can make the fan maintain a high ventilation efficiency under different wind direction conditions. This adaptive control method helps to overcome the adverse effects of wind direction changes on ventilation effects and improve the stability and reliability of the ventilation system. Specifically, by adjusting the working strategy of the fan based on the wind direction conditions, the operating efficiency of the ventilation system under different wind directions can be maximized. When A is established, increasing the fan power and adjusting the ventilation direction can more effectively remove harmful gases or pollutants. When B is established, reducing the fan power and changing the ventilation direction can avoid ineffective ventilation and save energy. When C is established and the wind direction has a deflection angle θ, taking corresponding adjustment measures can reduce wind resistance and improve ventilation efficiency. In closed or semi-closed environments such as tunnels and mines, the accumulation of harmful gases will pose a threat to construction workers. It is necessary to monitor the wind direction in real time and adjust the ventilation system to ensure that the harmful gases are diluted and discharged in time, thereby ensuring the safety of construction workers. In addition, a reasonable wind direction adjustment strategy can reduce unnecessary operation of the fan, thereby reducing energy consumption. Introducing the wind direction adjustment factor into the control strategy of the ventilation system can enable the system to respond to different wind direction conditions more flexibly. This flexibility helps the system to maintain efficient and stable operation under different environments and working conditions. In addition, by adjusting the wind direction adjustment factor T wind The research and application of ventilation system optimization can provide a scientific basis for the design and optimization of ventilation system, so that engineers can optimize the fan layout and duct design according to the ventilation requirements under different wind direction conditions to improve the overall performance of the system. In tunnel construction and other projects, the effective operation of the ventilation system is crucial to ensure the construction progress. By optimizing the wind direction adjustment strategy, the downtime caused by the accumulation of harmful gases can be reduced and the construction efficiency can be improved. In summary, the wind direction adjustment factor T wind Its application under different wind direction conditions has significant beneficial effects in improving ventilation efficiency, ensuring personnel safety, reducing energy consumption, enhancing system flexibility, optimizing ventilation design and improving construction efficiency. In this embodiment, the fan adjustment strategy unit based on the prediction results also considers the wind speed sensitivity coefficient bi, and the coefficient can reflect the influence of wind speed change on the fan adjustment strength, which enables the system to more accurately control the fan adjustment strength and avoid over-adjustment or under-adjustment. Accurately controlling the strength helps to reduce energy waste and improve the economy of the ventilation system. This embodiment can reasonably allocate ventilation resources by formulating the calculation of the fan adjustment strategy unit based on the prediction results. For areas with higher concentrations of harmful gases, the ventilation intensity can be increased, while for areas with lower concentrations, the ventilation intensity can be appropriately reduced. This resource optimization configuration method helps to improve the overall efficiency and sustainability of the ventilation system.

[0029] See also Figures 1 to 4 , based on the control benchmark index YJ of the harmful gas concentration prediction and evaluation unit and the fan adjustment strategy formulation unit based on the prediction results safe The calculation formula is as follows: ; TL max Adjust the maximum force for the fan; N is the total number of tunnel parts; YHN max is the maximum concentration of harmful gases; The calculation formula for comprehensively evaluating the overall operating status of the system and determining the warning level unit is as follows: ; in: YJ is the warning level; The process of comprehensively evaluating the overall operating status of the system and determining the warning level unit is as follows: Taking into account the fan adjustment capacity and the degree of harmful gas concentration exceeding the standard, when the adjustment capacity is not enough to quickly reduce the concentration to a safe level, the warning level YJ rises.

[0030] In this embodiment, the algorithm unit firstly uses the warning level YJ as the most direct beneficial effect, which is to significantly reduce the concentration of harmful gases in various parts of the tunnel to keep it below the safe level. This is very important for protecting the health and safety of construction workers, and reduces the risk of health problems and safety accidents caused by excessive harmful gases. Reducing the concentration of harmful gases can also improve the working environment in the tunnel, improve the comfort and work efficiency of construction workers, and work in fresher air. The concentration and endurance of construction workers will be improved, which will help to speed up the construction progress and improve the quality of the project. Regulation Benchmark Index YJ safe The evaluation not only focuses on the current concentration of harmful gases, but also takes into account the comprehensive evaluation of the maximum adjustment capacity of the fan and the degree of harmful gas concentration exceeding the standard in each part. Therefore, by optimizing the control strategy, the stability and reliability of the ventilation system can be enhanced to ensure that it can maintain an efficient operating state under various working conditions. Specifically, when the control benchmark index YJ safe When the ventilation system control capacity is insufficient, timely adjustment measures can reduce the predicted harmful gas concentration value YHN at the i-th tunnel location i , thereby preventing the concentration of harmful gases from continuing to rise and reaching dangerous levels. This early warning and response mechanism helps to prevent potential safety risks in advance and ensure the smooth progress of the construction process. The evaluation and optimization process of the ventilation system's control capabilities is also a process of technological innovation and upgrading. By continuously exploring and practicing new control strategies and technical means, the ventilation system can be promoted to develop in a more intelligent, efficient and environmentally friendly direction. In summary, by dynamically adjusting the parameters of the ventilation system to reduce the predicted concentration of harmful gases, the control ability of the ventilation system can be significantly improved, bringing about many beneficial effects. These effects not only help to protect the health and safety of construction workers, but also improve work efficiency, save energy and resources, enhance system stability and reliability, and promote technological innovation and upgrading; In this algorithm unit, a comprehensive warning level YJ is given by comprehensively evaluating the relative relationship between the overall control ability of the system and the degree of harmful gas exceeding the standard. This index can comprehensively reflect the operating status and potential risks of the ventilation system and provide important reference information for relevant personnel. When the comprehensive warning level YJ exceeds the control benchmark index YJ safe When the system is detected, it can automatically send out warning signals and start the emergency response mechanism. This real-time warning and emergency response mechanism helps to quickly respond to emergencies and reduce the harm and risks caused by excessive harmful gases. By comprehensively evaluating the overall operating status of the system and determining the calculation results and feedback mechanism of the warning level unit, the control strategy and parameter settings of the ventilation system can be continuously optimized. With the accumulation of data and experience, the overall performance and stability of the ventilation system can be gradually improved, achieving continuous improvement and optimization.

[0031] See also Figures 1 to 4 , based on the regulatory benchmark index YJ of the warning level YJ safe The regulation analysis is as follows: If the warning level YJ is lower than the control benchmark index YJ safe , it indicates that the current ventilation system control capability is sufficient to quickly and effectively reduce the concentration of harmful gases in various parts of the tunnel to a safe level, and the current control measures should be maintained; If the warning level YJ is higher than the control benchmark index YJ safe , it indicates that the current ventilation system control capability is not sufficient to quickly and effectively reduce the concentration of harmful gases in various parts of the tunnel to a safe level, and the diffusion coefficient KS of the i-th tunnel part should be dynamically adjusted. i and the ventilation efficiency coefficient TF of the i-th tunnel section i ,At the same time, the safety warning device executes early warning measures.

[0032] In this embodiment, the algorithm unit is based on the ventilation efficiency coefficient TF of the i-th tunnel part. i And the diffusion coefficient KS of the i-th tunnel part i , which can accelerate the dilution and discharge of harmful gases in the tunnel, thereby quickly reducing the predicted harmful gas concentration value YHN at the i-th tunnel location i , to ensure the health and safety of construction workers, and dynamically adjust the diffusion coefficient KS of the i-th tunnel part i and the ventilation efficiency coefficient TF of the i-th tunnel sectioni , is based on real-time monitoring data and system feedback. This targeted optimization can significantly improve the operating efficiency of the ventilation system and reduce ineffective ventilation and energy waste; The tunnel construction environment is complex and changeable. The generation and diffusion of harmful gases are affected by many factors. Through dynamic adjustment strategies, the ventilation system can better adapt to different working conditions and environmental conditions, ensuring efficient operation in any situation. Warning level YJ and control benchmark index YJ safe The comparison results not only provide a basis for dynamic adjustment, but also realize real-time monitoring and early warning of the ventilation system's control capabilities. Once the warning level increases, the system can immediately initiate corresponding adjustment measures to prevent the concentration of harmful gases from continuing to increase and reaching a dangerous level. By effectively controlling the concentration of harmful gases in the tunnel, the downtime caused by excessive harmful gases can be reduced, thereby ensuring the smooth progress of the construction progress. At the same time, good ventilation conditions can also help improve the quality and safety of tunnel construction. The cyclic influence between the comprehensive evaluation of the overall operating status of the system and the determination of the warning level unit and the prediction and evaluation of the harmful gas concentration unit also promotes the coordinated optimization of the entire ventilation system. By continuously adjusting and optimizing the parameters and strategies of each module, the coordinated work of various parts of the system can be achieved, and the overall efficiency and stability can be improved. This collaborative optimization mechanism helps to reduce the operating costs and risks of the ventilation system and improve the safety and reliability of construction and operation. The cyclical influence of the comprehensive evaluation system's overall operating status and the determination of the warning level unit on the prediction and evaluation of the harmful gas concentration unit is also reflected in improving the prediction accuracy and real-time performance. By continuously feeding back and adjusting the prediction parameters, the performance of the prediction model can be gradually optimized, and the prediction accuracy and real-time performance can be improved. This helps to more accurately reflect the actual concentration changes of harmful gases in the tunnel and provide more reliable data support for ventilation control. In summary, when the warning level YJ is higher than the control benchmark index YJ safe When the diffusion coefficient KS of the i-th tunnel part is adjusted dynamically i and the ventilation efficiency coefficient TF of the i-th tunnel section iIt is an effective means to reduce the concentration of harmful gases in tunnels, improve the efficiency of ventilation systems, enhance system adaptability, achieve early warning and response, and ensure construction progress and quality. These beneficial effects work together on the tunnel construction environment, providing strong guarantees for the health and safety of construction workers and the smooth progress of the project. In the specific implementation process, the harmful gas concentration prediction and evaluation unit, the fan adjustment strategy unit based on the prediction results, and the comprehensive evaluation system The overall operating status and determine the warning level unit together constitute a multi-dimensional and coordinated tunnel harmful gas detection and ventilation adaptive control system. Through the implementation of this system, the construction team can manage the harmful gas problems in the tunnel construction process more scientifically and efficiently, and ensure the safety and health of construction workers.

[0033] For example 2, please refer to Figures 1 to 4 , based on the predicted harmful gas concentration value YHN of the i-th tunnel part in each part of the tunnel i , the average concentration of harmful gases in the entire tunnel is YHN avg The calculation formula is as follows: YHN avg =(YHN1+YHN2+YHN3+......+YHN n ) / N; YHN avg is the average value of harmful gas concentration; YHN1 is the predicted concentration of harmful gases in the first tunnel, YHN2 is the predicted concentration of harmful gases in the second tunnel, YHN3 is the predicted concentration of harmful gases in the third tunnel, and YHN n Predict the concentration value of harmful gases for the nth tunnel location; N is the total number of tunnel sections, which reflects how many sections the entire tunnel is divided into; If the predicted harmful gas concentration value YHN of the i-th tunnel part i Greater than the average concentration of harmful gases YHN avg , a long-track pusher and a long tractor are used in this area.

[0034] In this embodiment, in the tunnel harmful gas detection ventilation adaptive control method, by introducing the prediction and evaluation of harmful gas concentration unit, the i-th tunnel location predicted harmful gas concentration value YHN i And the corresponding average value of harmful gas concentration YHN avg ,This method has achieved a significant improvement in tunnel construction safety; Specifically, by real-time monitoring and prediction of the concentration of harmful gases in various parts of the tunnel, and when the concentration approaches or exceeds the average concentration of harmful gases YHN avgEarly warning is issued in time, so that the construction unit can have enough time to take corresponding measures to effectively control the increase of harmful gas concentration, thereby greatly reducing the safety risks caused by excessive harmful gas concentration; According to the prediction results, construction guidance can formulate differentiated prevention and control measures according to the specific conditions of different tunnel parts. For example, in areas where the concentration of harmful gases is predicted to exceed the standard, mechanized operation equipment such as long rail pushers and long tractors can be deployed in advance to reduce the risk of personnel being exposed to high-concentration harmful gases, thus achieving precise and scientific construction management. By introducing automated and mechanized operation methods, it is not only possible to effectively reduce the working time and frequency of construction workers in high-risk environments and reduce health risks caused by exposure to harmful gases, but also to improve construction efficiency and ensure the smooth progress of tunnel engineering. The implementation of this method has promoted technological innovation in the field of harmful gas detection and ventilation control in tunnel construction, and promoted the establishment and improvement of relevant technical standards. At the same time, it has also provided experience and models for reference for similar projects, and promoted technological progress and standardization development in the entire industry. In summary, by introducing the mechanism of harmful gas concentration prediction and safety threshold control, the tunnel harmful gas detection and ventilation adaptive control method has achieved comprehensive protection and improvement of tunnel construction safety, providing strong support for the smooth progress of tunnel engineering and the health and safety of construction workers.

[0035] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method, characterized in that: The specific implementation steps are as follows: Step S1, using the data collection and preprocessing module to collect and process real-time data related to harmful gases, wind speed and wind direction in the tunnel; Step S2-1: Use the comprehensive prediction and control module to predict the concentration of harmful gases in various parts of the tunnel, and based on the concentration of harmful gases in various parts, output the average value YHN of the concentration of harmful gases that requires the use of long rail pushers and long tractors in various parts of the tunnel. avg , and perform adaptive regulation; Step S2-2: Based on the predicted concentration and the average concentration of harmful gases YHN avg , and combined with real-time data related to wind speed and wind direction, calculate the output fan adjustment strategy; Step S2-2, comprehensively evaluate the fan adjustment strategy and the degree of harmful gas exceeding the standard, calculate the output warning level YJ, and give control suggestions; Step S3, using the control execution module, according to the warning level YJ and real-time data, to respond to warnings and dynamically adjust ventilation strategies, and implement adjustment measures; Among them, the comprehensive prediction and control module includes a harmful gas concentration prediction and evaluation unit, a fan adjustment strategy unit based on the prediction results, and a comprehensive evaluation system overall operating status and determination warning level unit.

2. According to claim 1, a multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method is characterized in that: The equipment used in the data collection and preprocessing module includes harmful gas sensors, wind speed sensors, wind direction sensors, and tunnel section size measuring equipment; The equipment used in the comprehensive prediction and control module includes a data processing and analysis system; The equipment used by the control execution module includes ventilation system controller, construction guidance and emergency response equipment.

3. According to claim 2, a multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method is characterized by: The harmful gas sensor is used to detect the concentration of harmful gases in the tunnel in real time; The wind speed sensor is used to measure the wind speed at various locations in the tunnel; The wind direction sensor is used to determine the wind direction information in the tunnel; The tunnel cross-sectional dimension measuring device is used to obtain tunnel cross-sectional area data; The ventilation system controller is used to execute the fan adjustment strategy and control the operation of the ventilation system; The data processing and analysis system includes a computer, data processing software and an algorithm library, and is used to process real-time data, calculate predicted concentrations, adjust strategies and early warning indices; The construction guidance and emergency response equipment includes communication equipment, safety warning devices, emergency lighting and escape equipment, and is used for construction guidance and emergency response.

4. A multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method according to claim 3, characterized in that: The calculation formula for predicting and evaluating the harmful gas concentration unit is as follows: ； in: YHN i Predict the concentration value of harmful gases for the i-th tunnel location; FS i is the wind speed at the i-th tunnel location; KS i is the diffusion coefficient of the i-th tunnel part; NB i is the concentration variation factor of the i-th tunnel part; YHN prev，i is the concentration of harmful gases at the previous time point in the i-th tunnel part, YHN prev，i Reflects the concentration value of harmful gases in the same part of the tunnel in the previous test result; JM i is the cross-sectional area of ​​the i-th tunnel part; TF i is the ventilation efficiency coefficient of the ith tunnel location.

5. A multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method according to claim 4, characterized in that: The predicted harmful gas concentration value YHN of the i-th tunnel part based on each part in the tunnel i , the average concentration of harmful gases in the entire tunnel is YHN avg The calculation formula is as follows: YHN avg =(YHN1+YHN2+YHN3+.....+YHN n ) / N; YHN avg is the average value of harmful gas concentration; YHN1 is the predicted concentration of harmful gases in the first tunnel, YHN2 is the predicted concentration of harmful gases in the second tunnel, YHN3 is the predicted concentration of harmful gases in the third tunnel, and YHN n Predict the concentration value of harmful gases for the nth tunnel location; N is the total number of tunnel sections, which reflects how many sections the entire tunnel is divided into; If the predicted harmful gas concentration value YHN of the i-th tunnel part i Greater than the average concentration of harmful gases YHN avg , a long-track pusher and a long tractor are used in this area.

6. A multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method according to claim 5, characterized in that: The wind direction adjustment factor T wind Adjust according to wind direction changes; A is set to indicate that the wind direction is consistent with the expected direction, B is set to indicate that the wind direction is opposite to the expected direction, and C and θ are set to indicate that the wind direction has a deflection angle. The wind direction adjustment factor T wind The wind direction change analysis formula is as follows: T wind =δ1, then A holds; T wind =δ2, then B holds; T wind =δ3, then C holds; T wind =δ3(θ), then the wind direction has a deflection angle θ; δ1, δ2, and δ3 are adjustment coefficients set according to specific wind direction conditions; If A and B are established, T wind Should take positive value; If C is established and the wind direction has a deflection angle θ, T wind It should vary with the size of the deflection angle.

7. A multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method according to claim 6, characterized in that: The calculation formula for formulating the fan adjustment strategy unit based on the prediction results is as follows: TL i =(YHN avg / YHN i , a ×(FS opt / FS i , bi ×(1+T wind , in: TL i Adjust the intensity value of the fan at the i-th tunnel location; a is the concentration ratio adjustment coefficient, which reflects the influence on the fan adjustment strength; FS opt is the optimal wind speed; bi is the wind speed sensitivity coefficient, which reflects the wind speed change on the fan adjustment force value TL of the i-th tunnel part i The degree of influence varies, and different tunnel parts have different wind speed sensitivities, so bi varies from part to part.

8. A multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method according to claim 7, characterized in that: The control benchmark index YJ based on the harmful gas concentration prediction and evaluation unit and the fan adjustment strategy formulation unit based on the prediction result safe The calculation formula is as follows: ； TL max Adjust the maximum force for the fan; N is the total number of tunnel parts; YHN max It is the maximum concentration of harmful gases.

9. A multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method according to claim 8, characterized in that: The calculation formula for comprehensively evaluating the overall operating status of the system and determining the warning level unit is as follows: ； in: YJ is the warning level; The process of comprehensively evaluating the overall operating status of the system and determining the warning level unit is as follows: Taking into account the fan adjustment capacity and the degree of harmful gas concentration exceeding the standard, when the adjustment capacity is not enough to quickly reduce the concentration to a safe level, the warning level YJ rises.

10. A multi-dimensional collaborative tunnel harmful gas detection and ventilation adaptive control method according to claim 9, characterized in that: The control benchmark index YJ based on the warning level YJ safe The regulation analysis is as follows: If the warning level YJ is lower than the control benchmark index YJ safe , it indicates that the current ventilation system control capability is sufficient to quickly and effectively reduce the concentration of harmful gases in various parts of the tunnel to a safe level, and the current control measures should be maintained; If the warning level YJ is higher than the control benchmark index YJ safe , it indicates that the current ventilation system control capability is not sufficient to quickly and effectively reduce the concentration of harmful gases in various parts of the tunnel to a safe level, and the diffusion coefficient KS of the i-th tunnel part should be dynamically adjusted. i and the ventilation efficiency coefficient TF of the i-th tunnel section i ,At the same time, the safety warning device executes early warning measures.

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