An intelligent environment monitoring system for tunnel construction sites

Abstract

The invention discloses an intelligent environment monitoring system for a tunnel construction site, belonging to the technical field of tunnel environment monitoring. The invention comprises the following steps: comprising an information acquisition module, an information processing module and an execution module; the information acquisition module is used to acquire information required by the system; the information processing module is used to store, analyze and transmit information of each module; the execution module is used to execute the information of the information processing module; the information acquisition module comprises an environment information unit and an equipment information unit; the information processing module comprises an information storage unit, an information analysis unit and an information transmission unit; the execution module comprises a display unit and a control unit; the invention effectively improves the quality of concrete and ensures the overall quality and durability of the tunnel by real-time monitoring and analysis of the temperature, humidity and dust concentration of the tunnel construction site; at the same time, effective control of the dust concentration is achieved, thereby improving the working safety of the construction site.

Description

Technical Field

[0001] The present invention belongs to the technical field of tunnel environment monitoring, and specifically relates to an intelligent environment monitoring system for tunnel construction sites. Background Technique

[0002] Tunnel construction environment monitoring is an important link to ensure construction safety and improve project quality. By real-time monitoring of the construction environment, potential safety hazards can be detected in a timely manner, providing valuable data support for the construction team, thus avoiding accidents. At the same time, the monitoring data can also provide reference for subsequent engineering design, construction and management, helping to improve the overall quality and durability of the tunnel;

[0003] Tunnel construction includes construction stages such as excavation, filling, and maintenance. During the filling stage, specific concrete usually needs to be configured at the construction site, and the area is closed to maintain the temperature and humidity of the construction site to ensure the quality of the concrete and the overall quality and durability of the tunnel. However, a large amount of dust will appear when the construction equipment configures specific concrete. When using ventilation equipment for ventilation, while the dust is taken away, it is very difficult to maintain the temperature and humidity of the construction site, reducing the overall quality and durability of the tunnel;

[0004] Therefore, there is an urgent need for an intelligent environment monitoring system for tunnel construction sites to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent environment monitoring system for tunnel construction sites to solve the problems raised in the above background technique.

[0006] To solve the above technical problems, the present invention provides the following technical solutions:

[0007] An intelligent environment monitoring system for tunnel construction sites, the system includes an information collection module, an information processing module and an execution module;

[0008] The information collection module is used to collect the information required by the system; the information processing module is used to store, analyze and transmit the information of each module; the execution module is used to execute the information of the information processing module.

[0009] According to the above technical solution, the information collection module includes an environmental information unit and an equipment information unit;

[0010] The environmental information unit is used to collect historical data information and real-time data information of temperature, humidity and dust concentration in the site to be monitored; the equipment information unit is used to collect historical data information and real-time data information of ventilation equipment in the site to be monitored.

[0011] According to the above technical solution, the information processing module includes an information storage unit, an information analysis unit and an information transmission unit;

[0012] The information storage unit is used for storing information of each module in the system; the information analysis unit is used for analyzing information of each module in the system; the information transmission unit is used for transmitting information of each module in the system.

[0013] According to the above technical solution, the execution module includes a display unit and a control unit;

[0014] The display unit is used for displaying the temperature, humidity and dust concentration of the site to be monitored, and forming visual data; the control unit is used for controlling the ventilation equipment.

[0015] According to the above technical solution, the information analysis process of the information analysis unit includes the following steps:

[0016] S1. Collect the temperature and humidity range required for the site to be monitored, analyze the temperature and humidity target values of the site to be monitored, and calculate the change range of the wet-bulb temperature and the target wet-bulb temperature of the site to be monitored;

[0017] S2. Collect the ventilation area, safety power range and historical ventilation records of the ventilation equipment in the site to be monitored, analyze the relationship between the ventilation volume and the equipment power of the ventilation equipment in the site to be monitored, and the ventilation volume range of the ventilation equipment in the site to be monitored;

[0018] S3. Record the start time and concrete configuration amount of the construction equipment in the site to be monitored, and obtain the initial dust concentration of the site to be monitored; collect the real-time equipment power of the ventilation equipment, and analyze the real-time ventilation volume of the ventilation equipment; collect the real-time temperature and humidity of the site to be monitored, and analyze the real-time wet-bulb temperature of the site to be monitored;

[0019] S4. According to the change range of the wet-bulb temperature of the site to be monitored, the target wet-bulb temperature of the site to be monitored, the ventilation volume range of the ventilation equipment in the site to be monitored and the initial ventilation volume of the ventilation equipment, analyze the real-time influence degree of the ventilation equipment;

[0020] S5. Collect the real-time dust concentration of the site to be monitored, and combine the concrete configuration amount of the construction equipment in the site to be monitored, the initial dust concentration of the site to be monitored and the real-time influence degree of the ventilation equipment to analyze the real-time dust change of the site to be monitored; adjust the ventilation equipment according to the real-time dust change.

[0021] According to the above technical solution, the specific process of step S1 is as follows:

[0022] S1-1. The temperature and humidity range includes a temperature range and a humidity range; the temperature and humidity target values include a temperature target value and a humidity target value;

[0023] Record the temperature range required for the site to be monitored as [T min , Tmax ; where, T min represents the minimum temperature required for the site to be monitored; P max represents the maximum temperature required for the site to be monitored;

[0024] Record the humidity range required for the site to be monitored as [H min , H max ; where, H min represents the minimum humidity required for the site to be monitored; H max represents the maximum humidity required for the site to be monitored;

[0025] S1-2. According to the temperature range [T min , T max required for the site to be monitored, calculate the temperature target value of the site to be monitored. The specific calculation formula is T target = (T min + T max ) / 2 × α1; where, T target represents the temperature target value of the site to be monitored; α1 represents the parameter preset by the system;

[0026] According to the humidity range [H min , H max required for the site to be monitored, calculate the humidity target value of the site to be monitored. The specific calculation formula is H target = (H min + H max ) / 2 × α2; where, H target represents the humidity target value of the site to be monitored; α2 represents the parameter preset by the system;

[0027] S1-3. Establish a wet-bulb temperature calculation model, specifically as follows: G out = T int × arctan{β1 × (H int + β2) β3} + arctan(T int + H int ) - arctan(H int - β4) + β5 × (H int ) β6 × arctan(β7 × H int ) - β8; where, G out represents the output wet-bulb temperature; T int represents the input temperature; H int represents the input humidity; β1, β2, β3, β4, β5, β6, β7 and β8 all represent the parameters preset by the system;

[0028] The wet-bulb temperature reflects the evaporation capacity of moisture in the air. In tunnel filling construction, using the wet-bulb temperature as an influencing condition for data analysis can not only ensure that the moisture evaporation rate of the concrete is within a reasonable range, thus avoiding cracks caused by excessive drying and problems with the strength and durability of the concrete due to high temperatures, but also evaluate the ventilation effect of the ventilation equipment to maintain a suitable temperature and humidity in the working environment, ensuring construction safety and worker comfort.

[0029] S1-4. Take the value of T max as T int and take the value of H max as H int , input into the wet-bulb temperature calculation model, and take the G obtained by the wet-bulb temperature calculation model out as the maximum wet-bulb temperature of the site to be monitored, denoted as G max ;

[0030] Take the value of T min as T int and take the value of H min as H int , input into the wet-bulb temperature calculation model, and take the G obtained by the wet-bulb temperature calculation model out as the minimum wet-bulb temperature of the site to be monitored, denoted as G min ;

[0031] Obtain the change range of the wet-bulb temperature of the site to be monitored as [G min , G max ;

[0032] Take the value of T target as T int and take the value of H target as H int , input into the wet-bulb temperature calculation model, and take the G obtained by the wet-bulb temperature calculation model out as the target wet-bulb temperature of the site to be monitored, denoted as G target .

[0033] According to the above technical solution, the specific process of step S2 is as follows:

[0034] S2-1. The historical ventilation record includes equipment power and air flow velocity at the ventilation opening;

[0035] Denote the ventilation opening area of the ventilation equipment at the site to be monitored as S;

[0036] Denote the safe power range of the ventilation equipment at the site to be monitored as [P min , P max ; where P min represents the minimum safe power of the ventilation equipment at the site to be monitored; Pmax Represents the maximum safe power of the ventilation equipment at the site to be monitored;

[0037] Denote the equipment power in the a-th historical ventilation record of the ventilation equipment at the site to be monitored as P1 a ; Denote the air flow velocity at the ventilation opening in the a-th historical ventilation record of the ventilation equipment at the site to be monitored as V1 a ; Calculate the ventilation volume of the ventilation equipment at the site to be monitored in each historical ventilation record. The specific calculation formula is: Q1 a = S × V1 a ; where, Q1 a Represents the ventilation volume of the ventilation equipment at the site to be monitored in the a-th historical ventilation record;

[0038] S2-2. Establish a neural network model. Use the P1 corresponding to each historical ventilation record of the ventilation equipment at the site to be monitored a as the input, and use the Q1 corresponding to each historical ventilation record of the ventilation equipment at the site to be monitored a as the output to train the neural network model; Obtain the relationship between the ventilation volume and the equipment power of the ventilation equipment;

[0039] The neural network model can be trained with historical data to learn the influence relationship between the ventilation volume and the equipment power of the ventilation equipment; The model can be continuously updated to adapt to the changes of the ventilation equipment in different construction sites, making the adjustment of the ventilation equipment more accurate;

[0040] S2-3. Input the P corresponding to the safe power range of the ventilation equipment at the site to be monitored min , into the trained neural network model, and output the minimum ventilation volume of the ventilation equipment at the site to be monitored, denoted as Q min ; Input the P corresponding to the safe power range of the ventilation equipment at the site to be monitored max , into the trained neural network model, and output the maximum ventilation volume of the ventilation equipment at the site to be monitored, denoted as Q max ; Obtain the ventilation volume range of the ventilation equipment at the site to be monitored as [Q min , Q max .

[0041] According to the above technical solution, the specific process of step S3 is as follows:

[0042] S3-1. Denote the start time of the construction equipment at the site to be monitored as the t0 moment; Denote the concrete preparation volume of the construction equipment at the site to be monitored as A;

[0043] The concrete preparation volume refers to the volume of concrete that the construction equipment needs to use each time;

[0044] Collect the dust concentration at the scene to be monitored at time t0 as the initial dust concentration at the scene to be monitored, denoted as C t0 ;

[0045] S3-2: Denote the current moment as time t1; Denote the real-time device power of the ventilation equipment at time t1 as P2 t1 ;

[0046] Input the real-time device power P2 of the ventilation equipment t1 into the trained neural network model, and output the real-time ventilation volume of the ventilation equipment, denoted as Q2 t1 ;

[0047] S3-3: Denote the real-time temperature at the scene to be monitored at time t1 as T1 t1 ; Denote the real-time humidity at the scene to be monitored at time t1 as H1 t1 ;

[0048] Use the value of T1 t1 as T int and use the value of H1 t1 as H int , input them into the wet-bulb temperature calculation model, and use the G out obtained by the wet-bulb temperature calculation model as the real-time wet-bulb temperature at the scene to be monitored at time t1, denoted as G1 t1 .

[0049] According to the above technical solution, the specific process of step S4 is as follows:

[0050] According to the real-time wet-bulb temperature G1 at the scene to be monitored at time t1 t1 , the target wet-bulb temperature G at the scene to be monitored target , the maximum wet-bulb temperature G at the scene to be monitored max , the maximum ventilation volume Q of the ventilation equipment at the scene to be monitored max and the real-time ventilation volume Q2 of the ventilation equipment t1 , calculate the real-time influence degree of the ventilation equipment at time t1. The specific calculation formula is: F t1 =1 - γ×{(G target - G1 t1 ) / (G max - G1 t1 ) + Q2 t1 / Q max}; where, F t1 represents the real-time influence degree of the ventilation equipment at time t1; γ represents the parameter preset by the system;

[0051] The real-time influence degree of the ventilation equipment reflects the influence of the changes in the real-time wet-bulb temperature and the real-time ventilation volume on the real-time dust change, providing data support for subsequent adjustment of the ventilation equipment.

[0052] According to the above technical solution, the specific process of step S5 is as follows:

[0053] S5-1. Denote the real-time dust concentration at the site to be monitored at time t1 as C1 t1 ; Combine the concrete configuration quantity A of the facilities at the site to be monitored, the initial dust concentration C of the site to be monitored t0 and the real-time influence degree F of the ventilation equipment at time t1 t1 , and calculate the real-time dust change at the site to be monitored at time t1. The specific calculation formula is: R t1 =δ×A×(1 + C1 t1 / C t0 )×F t1 ; Among them, R t1 represents the real-time dust change at the site to be monitored at time t1; δ represents the parameter preset by the system;

[0054] The dust change reflects the change of the dust concentration in the air at the construction site, that is, the fluctuation of the air pollution level; Combining the real-time conditions of the equipment and the environment can not only more accurately and quickly reflect the sudden change of the dust concentration, but also more comprehensively consider the change of the temperature and humidity in the environment;

[0055] S5-2. Set the dust concentration safety threshold of the site to be monitored, denoted as C safe ;

[0056] According to the real-time dust change R t1 at the site to be monitored at time t1, adjust the ventilation equipment, and adjust the ventilation volume of the ventilation equipment after time t1 to Q3 adjust，t1 =ε1×R t1 ×(C1 t1 / C safe -1)+ε2×Q2 t1 ; Among them, Q3 adjust，t1 represents the ventilation volume of the ventilation equipment after time t1; Both ε1 and ε2 represent the parameters preset by the system;

[0057] By comparing and calculating the real-time dust concentration C1 t1 at the site to be monitored at time t1 with the dust concentration safety threshold C safe of the site to be monitored, when C1 t1 exceeds C safe , combine the R t1 , increase the ventilation volume, and maintain the temperature and humidity of the construction environment while reducing the dust concentration;

[0058] By integrating multiple factors into a single function, comprehensively considering the influence of equipment and environment on the change of dust concentration, and dynamically adjusting the ventilation equipment according to the real-time dust change, while ensuring the temperature and humidity, ensuring that the dust concentration is within the safe range, not only improves the overall quality and durability of the tunnel, but also ensures the construction safety of the construction personnel.

[0059] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0060] By real-time monitoring and analyzing the temperature, humidity and dust concentration at the tunnel construction site, the present invention realizes the precise management of the construction environment, comprehensively considers the operation data of the ventilation equipment, and adjusts the ventilation equipment in real time to ensure that the temperature and humidity at the construction site are maintained within the ideal range, thereby effectively improving the quality of concrete and ensuring the overall quality and durability of the tunnel; at the same time, it realizes the effective control of the dust concentration, reduces the impact of dust on the environment and personnel during the construction process, and improves the work safety and comfort at the construction site.

[0061] In summary, while improving the monitoring accuracy of the construction environment, ensuring the quality of concrete and enhancing the overall quality of the tunnel, the present invention optimizes resource management, enhances construction safety, and has significant technical advantages and application values. Description of the Drawings

[0062] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0063] Figure 1 is a schematic structural diagram of an intelligent environment monitoring system for a tunnel construction site according to the present invention. Detailed Embodiments

[0064] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0065] Please refer to Figure 1 , the present invention provides the following technical solutions:

[0066] An intelligent environment monitoring system for a tunnel construction site, the system includes an information collection module, an information processing module and an execution module;

[0067] The information collection module is used to collect the information required by the system; the information processing module is used to store, analyze, and transmit the information of each module; the execution module is used to execute the information of the information processing module.

[0068] According to the above technical solution, the information collection module includes an environmental information unit and a device information unit;

[0069] The environmental information unit is used to collect the historical data information and real-time data information of temperature, humidity, and dust concentration in the site to be monitored; the device information unit is used to collect the historical data information and real-time data information of the ventilation equipment in the site to be monitored.

[0070] According to the above technical solution, the information processing module includes an information storage unit, an information analysis unit, and an information transmission unit;

[0071] The information storage unit is used to store the information of each module in the system; the information analysis unit is used to analyze the information of each module in the system; the information transmission unit is used to transmit the information of each module in the system.

[0072] According to the above technical solution, the execution module includes a display unit and a control unit;

[0073] The display unit is used to display the temperature, humidity, and dust concentration of the site to be monitored, forming visual data; the control unit is used to control the ventilation equipment.

[0074] According to the above technical solution, the information analysis process of the information analysis unit includes the following steps:

[0075] S1. Collect the temperature and humidity range required for the site to be monitored, analyze the temperature and humidity target values of the site to be monitored, and calculate the change range of the wet bulb temperature and the target wet bulb temperature of the site to be monitored;

[0076] S2. Collect the ventilation opening area, safety power range, and historical ventilation records of the ventilation equipment in the site to be monitored, analyze the relationship between the ventilation volume and the equipment power of the ventilation equipment in the site to be monitored, and the ventilation volume range of the ventilation equipment in the site to be monitored;

[0077] S3. Record the start time and concrete configuration amount of the equipment in the site to be monitored, and obtain the initial dust concentration of the site to be monitored; collect the real-time equipment power of the ventilation equipment, and analyze the real-time ventilation volume of the ventilation equipment; collect the real-time temperature and humidity of the site to be monitored, and analyze the real-time wet bulb temperature of the site to be monitored;

[0078] S4. Analyze the real-time influence degree of the ventilation equipment according to the change range of the wet bulb temperature of the site to be monitored, the target wet bulb temperature of the site to be monitored, the ventilation volume range of the ventilation equipment in the site to be monitored, and the initial ventilation volume of the ventilation equipment;

[0079] S5. Collect the real-time dust concentration at the site to be monitored, analyze the real-time dust change at the site to be monitored by combining the concrete configuration quantity of the facilities at the site to be monitored, the initial dust concentration at the site to be monitored, and the real-time influence degree of the ventilation equipment; adjust the ventilation equipment according to the real-time dust change.

[0080] According to the above technical solution, the specific process of step S1 is as follows:

[0081] S1-1. The temperature and humidity range includes a temperature range and a humidity range; the temperature and humidity target values include a temperature target value and a humidity target value;

[0082] Record the required temperature range at the site to be monitored as [T min , T max ; where T min represents the minimum temperature required at the site to be monitored; P max represents the maximum temperature required at the site to be monitored;

[0083] Record the required humidity range at the site to be monitored as [H min , H max ; where H min represents the minimum humidity required at the site to be monitored; H max represents the maximum humidity required at the site to be monitored;

[0084] S1-2. According to the required temperature range [T min , T max at the site to be monitored, calculate the temperature target value at the site to be monitored. The specific calculation formula is T target = (T min + T max ) / 2 × α1; where T target represents the temperature target value at the site to be monitored; α1 represents the parameter preset by the system;

[0085] According to the required humidity range [H min , H max at the site to be monitored, calculate the humidity target value at the site to be monitored. The specific calculation formula is H target = (H min + H max ) / 2 × α2; where H target represents the humidity target value at the site to be monitored; α2 represents the parameter preset by the system;

[0086] S1-3. Establish a wet-bulb temperature calculation model as follows: G out = T int × arctan{β1 × (H int + β2)β3}+ arctan(T int + H int ) - arctan(H int - β4) + β5×(H int ) β6 × arctan(β7×H int ) - β8; where, G out represents the output wet-bulb temperature; T int represents the input temperature; H int represents the input humidity; β1, β2, β3, β4, β5, β6, β7 and β8 all represent the parameters preset by the system;

[0087] The wet-bulb temperature reflects the evaporation ability of moisture in the air. In the tunnel filling construction, taking the wet-bulb temperature as an influencing condition for data analysis can not only ensure that the moisture evaporation rate of the concrete is within a reasonable range, thus avoiding cracks caused by excessive drying and problems with the concrete strength and durability due to high temperature, but also can evaluate the ventilation effect of the ventilation equipment to maintain a suitable temperature and humidity in the working environment, ensuring construction safety and worker comfort.

[0088] S1-4. Take the value of T max as T int and take the value of H max as H int , input into the wet-bulb temperature calculation model, and take the G out obtained by the wet-bulb temperature calculation model as the maximum wet-bulb temperature of the site to be monitored, denoted as G max ;

[0089] Take the value of T min as T int and take the value of H min as H int , input into the wet-bulb temperature calculation model, and take the G out obtained by the wet-bulb temperature calculation model as the minimum wet-bulb temperature of the site to be monitored, denoted as G min ;

[0090] Obtain the change range of the wet-bulb temperature of the site to be monitored as [G min , G max ;

[0091] Take the value of T target as T int and take the value of H target as H int , input into the wet-bulb temperature calculation model, and take the G out obtained by the wet-bulb temperature calculation model as the target wet-bulb temperature of the site to be monitored, denoted as G target ;

[0092] For example:

[0093] β1 = 0.15, β2 = 8.31, β3 = 0.5, β4 = 1.68, β5 = 0.0039, β6 = 1.5, β7 = 0.023, and β8 = 4.69, T target = 30, H target = 70;

[0094] Take the value of T target as T int and take the value of H target as H int , input into the wet-bulb temperature calculation model, and the G obtained by the wet-bulb temperature calculation model out ≈ 30×0.924 + 1.570 - 1.558 + 2.730 - 4.69 = 25.76.

[0095] According to the above technical solution, the specific process of step S2 is as follows:

[0096] S2-1. The historical ventilation records include the equipment power and the air flow velocity at the ventilation opening;

[0097] Denote the ventilation opening area of the ventilation equipment at the site to be monitored as S;

[0098] Denote the safe power range of the ventilation equipment at the site to be monitored as [P min , P max ; where P min represents the minimum safe power of the ventilation equipment at the site to be monitored; P max represents the maximum safe power of the ventilation equipment at the site to be monitored;

[0099] Denote the equipment power in the a-th historical ventilation record of the ventilation equipment at the site to be monitored as P1 a ; denote the air flow velocity at the ventilation opening in the a-th historical ventilation record of the ventilation equipment at the site to be monitored as V1 a ; calculate the ventilation volume of the ventilation equipment at the site to be monitored in each historical ventilation record, and the specific calculation formula is: Q1 a = S×V1 a ; where Q1 a represents the ventilation volume of the ventilation equipment at the site to be monitored in the a-th historical ventilation record;

[0100] S2-2. Establish a neural network model, take P1 corresponding to each historical ventilation record of the ventilation equipment at the site to be monitored as the input, and take Q1 corresponding to each historical ventilation record of the ventilation equipment at the site to be monitored a as the input, and take Q1 corresponding to each historical ventilation record of the ventilation equipment at the site to be monitored aAs an output, train the neural network model; obtain the relationship between the ventilation volume and the equipment power of the ventilation equipment; the neural network model can be trained with historical data to learn the influence relationship between the ventilation volume and the equipment power of the ventilation equipment; the model can be continuously updated to adapt to the changes of the ventilation equipment in different construction sites, making the adjustment of the ventilation equipment more accurate;

[0101] S2-3. Input the P corresponding to the safe power range of the ventilation equipment at the site to be monitored into the trained neural network model, and output the minimum ventilation volume of the ventilation equipment at the site to be monitored, denoted as Q min ; Input the P corresponding to the safe power range of the ventilation equipment at the site to be monitored into the trained neural network model, and output the maximum ventilation volume of the ventilation equipment at the site to be monitored, denoted as Q min ; Obtain the ventilation volume range of the ventilation equipment at the site to be monitored as [Q max ,Q max . min ,Q max 。

[0102] According to the above technical solution, the specific process of step S3 is as follows:

[0103] S3-1. Denote the start time of the construction equipment at the site to be monitored as time t0; denote the concrete mixing amount of the construction equipment at the site to be monitored as A;

[0104] The concrete mixing amount refers to the volume of concrete required for each use of the construction equipment;

[0105] Collect the dust concentration at the site to be monitored at time t0 as the initial dust concentration at the site to be monitored, denoted as C t0 ;

[0106] S3-2. Denote the current time as time t1; denote the real-time equipment power of the ventilation equipment at time t1 as P2 t1 ;

[0107] Input the real-time equipment power P2 of the ventilation equipment t1 into the trained neural network model, and output the real-time ventilation volume of the ventilation equipment, denoted as Q2 t1 ;

[0108] S3-3. Denote the real-time temperature at the site to be monitored at time t1 as T1 t1 ; Denote the real-time humidity at the site to be monitored at time t1 as H1 t1 ;

[0109] Take the value of T1 t1 as T int and take the value of H1 t1 as H int, input the wet-bulb temperature calculation model, and obtain G from the wet-bulb temperature calculation model out , as the real-time wet-bulb temperature of the on-site to be monitored at time t1, denoted as G1 t1 .

[0110] According to the above technical solution, the specific process of step S4 is as follows:

[0111] According to the real-time wet-bulb temperature G1 of the on-site to be monitored at time t1 t1 , the target wet-bulb temperature G of the on-site to be monitored target , the maximum wet-bulb temperature G of the on-site to be monitored max , the maximum ventilation volume Q of the ventilation equipment in the on-site to be monitored max and the real-time ventilation volume Q2 of the ventilation equipment t1 , calculate the real-time influence degree of the ventilation equipment at time t1. The specific calculation formula is: F t1 = 1 - γ × {(G target - G1 t1 ) / (G max - G1 t1 ) + Q2 t1 / Q max}; where, F t1 represents the real-time influence degree of the ventilation equipment at time t1; γ represents the parameter preset by the system;

[0112] The real-time influence degree of the ventilation equipment reflects the changes in the real-time wet-bulb temperature and the real-time ventilation volume, and provides data support for subsequent adjustment of the ventilation equipment.

[0113] According to the above technical solution, the specific process of step S5 is as follows:

[0114] S5-1. Denote the real-time dust concentration of the on-site to be monitored at time t1 as C1 t1 ; combine the concrete configuration amount A of the facilities at the on-site to be monitored, the initial dust concentration C of the on-site to be monitored t0 and the real-time influence degree F of the ventilation equipment at time t1 t1 , calculate the real-time dust change of the on-site to be monitored at time t1. The specific calculation formula is: R t1 = δ × A × (1 + C1 t1 / C t0 ) × F t1 ; where, R t1 represents the real-time dust change of the on-site to be monitored at time t1; δ represents the parameter preset by the system;

[0115] The change in dust reflects the change in the dust concentration in the air at the construction site, that is, the fluctuation of the air pollution level; combined with the real-time conditions of the equipment and the environment, it can not only more accurately and quickly reflect the sudden change in the dust concentration, but also more comprehensively consider the change in temperature and humidity in the environment;

[0116] S5-2. Set the safety threshold of the dust concentration at the site to be monitored, denoted as C safe ;

[0117] According to the real-time dust change R at the site to be monitored at time t1 t1 , adjust the ventilation equipment, and adjust the ventilation volume of the ventilation equipment after time t1 to Q3 adjust，t1 = ε1×R t1 ×(C1 t1 / C safe -1)+ε2×Q2 t1 ; where Q3 adjust，t1 represents the ventilation volume of the ventilation equipment after time t1; both ε1 and ε2 represent parameters preset by the system;

[0118] By comparing and calculating the real-time dust concentration C1 at the site to be monitored at time t1 t1 with the safety threshold C of the dust concentration at the site to be monitored safe , when C1 t1 exceeds C safe , combined with R t1 , increase the ventilation volume, while reducing the dust concentration, maintain the temperature and humidity of the construction environment;

[0119] By integrating multiple factors into a function, comprehensively consider the influence of equipment and environment on the change of dust concentration, and dynamically adjust the ventilation equipment according to the real-time dust change. While ensuring the temperature and humidity, ensure that the dust concentration is within the safe range, which not only improves the overall quality and durability of the tunnel, but also ensures the construction safety of the construction personnel.

[0120] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0121] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent environment monitoring system for a tunnel construction site, characterized in that: The system includes an information collection module, an information processing module and an execution module; The information acquisition module is used to collect information required by the system; the information processing module is used to store, analyze and transmit information of each module; the execution module is used to execute the information of the information processing module; The information processing module includes an information storage unit, an information analysis unit and an information transmission unit; The information storage unit is used for information storage of each module in the system; the information analysis unit is used for information analysis of each module in the system; the information transmission unit is used for information transmission of each module in the system; The information analysis process of the information analysis unit includes the following steps: S1. Collect the temperature and humidity range required by the site to be monitored, analyze the temperature and humidity target values ​​of the site to be monitored, and calculate the wet-bulb temperature variation range and target wet-bulb temperature of the site to be monitored; S2. Collect the ventilation opening area, safe power range and historical ventilation records of the ventilation equipment in the monitored site, analyze the relationship between the ventilation volume and equipment power of the ventilation equipment in the monitored site, and the ventilation volume range of the ventilation equipment in the monitored site; S3. Record the start time of the construction work at the site to be monitored and the amount of concrete configured, and obtain the initial dust concentration at the site to be monitored; collect the real-time equipment power of the ventilation equipment, and analyze the real-time ventilation volume of the ventilation equipment; collect the real-time temperature and humidity at the site to be monitored, and analyze the real-time wet-bulb temperature at the site to be monitored; S4. Analyze the real-time impact of the ventilation equipment according to the wet-bulb temperature variation range of the site to be monitored, the target wet-bulb temperature of the site to be monitored, the ventilation volume range of the ventilation equipment in the site to be monitored, and the initial ventilation volume of the ventilation equipment; S5. Collect the real-time dust concentration of the site to be monitored, analyze the real-time dust changes of the site to be monitored, based on the concrete configuration of the facility workers at the site to be monitored, the initial dust concentration at the site to be monitored, and the real-time influence of the ventilation equipment; adjust the ventilation equipment according to the real-time dust changes; The specific process of step S4 is as follows: According to the real-time wet-bulb temperature G1 of the monitored site at time t1 t1 , Target wet bulb temperature G of the site to be monitored target , the maximum wet bulb temperature G of the site to be monitored max , the maximum ventilation volume Q of the ventilation equipment in the monitored site max And the real-time ventilation volume Q2 of the ventilation equipment t1 , calculate the real-time influence of ventilation equipment at time t1, the specific calculation formula is: F t1 =1-γ×{(G target -G1 t1 ) / (G max -G1 t1 )+Q2 t1 / Q max }; where F t1 represents the real-time influence of the ventilation equipment at time t1; γ represents the system preset parameter; The specific process of step S5 is as follows: S5-1. The real-time dust concentration at the monitored site at time t1 is recorded as C1 t1 ; Combined with the concrete configuration amount A of the facility to be monitored, the initial dust concentration C of the site to be monitored t0 And the real-time influence of ventilation equipment at time t1 F t1 , calculate the real-time dust change at the monitored site at time t1, the specific calculation formula is: R t1 =δ×A×(1+C1 t1 / C t0 )×F t1 ; Among them, R t1 It indicates the real-time dust change at the monitored site at time t1; δ indicates the preset parameters of the system; S5-2. Set the dust concentration safety threshold of the site to be monitored, denoted as C safe ; According to the real-time dust change R at the monitored site at time t1 t1 , adjust the ventilation equipment and adjust the ventilation volume of the ventilation equipment after time t1 to Q3 adjust，t1 =ε1×R t1 ×(C1 t1 / C safe -1)+ε2×Q2 t1 Among them, Q3 adjust，t1 It indicates the ventilation volume of the ventilation equipment after time t1; ε1 and ε2 both represent the preset parameters of the system.

2. The intelligent environment monitoring system for tunnel construction site according to claim 1, characterized in that: The information collection module includes an environment information unit and a device information unit; The environmental information unit is used to collect historical data information and real-time data information of temperature, humidity and dust concentration in the monitored site; the equipment information unit is used to collect historical data information and real-time data information of ventilation equipment in the monitored site.

3. The intelligent environment monitoring system for tunnel construction site according to claim 2 is characterized in that: The execution module includes a display unit and a control unit; The display unit is used to display the temperature, humidity and dust concentration of the site to be monitored to form visual data; the control unit is used to control the ventilation equipment.

4. The intelligent environment monitoring system for tunnel construction site according to claim 3 is characterized in that: The specific process of step S1 is as follows: S1-1, the temperature and humidity range includes a temperature range and a humidity range; the temperature and humidity target values ​​include a temperature target value and a humidity target value; The temperature range required by the site to be monitored is recorded as [T min , T max ]; where T min Indicates the minimum temperature required for the site to be monitored; P max Indicates the maximum temperature required for the site to be monitored; The humidity range required for the site to be monitored is recorded as [H min , H max ]; among them, H min Indicates the minimum humidity required for the site to be monitored; H max Indicates the maximum humidity required at the site to be monitored; S1-2, according to the temperature range required by the site to be monitored [T min , T max ], calculate the temperature target value of the monitored site, the specific calculation formula is T target =(T min +T max ) / 2×α1; where T target represents the temperature target value of the site to be monitored; α1 represents the system preset parameter; According to the humidity range required by the monitored site [H min , H max ], calculate the humidity target value of the site to be monitored, the specific calculation formula is H target =(H min +H max ) / 2×α2; where H target Indicates the humidity target value of the site to be monitored; α2 indicates the system preset parameter; S1-3. Establish a wet-bulb temperature calculation model, as follows: G out =T int ×arctan{β1×(H int +β2) β3 }+arctan(T int +H int )-arctan(H int -β4)+β5×(H int ) β6 ×arctan(β7×H int )-β8; among them, G out Indicates the output wet bulb temperature; T int Indicates the input temperature; H int Indicates the input humidity; β1, β2, β3, β4, β5, β6, β7 and β8 are all system preset parameters; S1-4, T max The value of T int And H max The value of H int , input the wet bulb temperature calculation model, and convert the G obtained by the wet bulb temperature calculation model into out , as the maximum wet bulb temperature of the site to be monitored, denoted as G max ; T min The value of T int And H min The value of H int , input the wet bulb temperature calculation model, and convert the G obtained by the wet bulb temperature calculation model into out , as the minimum wet bulb temperature of the site to be monitored, denoted as G min ; The wet bulb temperature variation range of the monitored site is [G min , G max ]; T target The value of T int And H target The value of H int , input the wet bulb temperature calculation model, and convert the G obtained by the wet bulb temperature calculation model into out , as the target wet-bulb temperature of the site to be monitored, denoted as G target .

5. The intelligent environment monitoring system for tunnel construction site according to claim 4 is characterized in that: The specific process of step S2 is as follows: S2-1, the historical ventilation records include equipment power and vent airflow velocity; The ventilation opening area of ​​the ventilation equipment in the monitored site is recorded as S; The safe power range of the ventilation equipment in the monitored site is recorded as [P min , P max ]; where P min Indicates the minimum safe power of the ventilation equipment in the monitored site; P max Indicates the maximum safe power of the ventilation equipment in the monitored site; The equipment power in the ath historical ventilation record of the ventilation equipment in the monitored site is recorded as P1 a ; The airflow velocity at the vent in the ath historical ventilation record of the ventilation equipment in the monitored site is recorded as V1 a ; Calculate the ventilation volume of the ventilation equipment in each historical ventilation record in the monitored site. The specific calculation formula is: Q1 a =S×V1 a ; Among them, Q1 a It indicates the ventilation volume of the ventilation equipment in the monitored site in the ath historical ventilation record; S2-2, establish a neural network model, and compare the P1 corresponding to each historical ventilation record of the ventilation equipment in the monitored site a As input, the Q1 corresponding to each historical ventilation record of the ventilation equipment in the monitored site a As output, the neural network model is trained; the relationship between the ventilation volume of the ventilation equipment and the equipment power is obtained; S2-3, the safe power range of the ventilation equipment in the monitored site corresponds to P min , input the trained neural network model, and output the minimum ventilation volume of the ventilation equipment in the monitored site, recorded as Q min ; Set the P corresponding to the safe power range of the ventilation equipment in the monitored site max , input the trained neural network model, and output the maximum ventilation volume of the ventilation equipment in the monitored site, recorded as Q max ; The ventilation volume range of the ventilation equipment in the monitored site is [Q min , Q max ].

6. The intelligent environment monitoring system for tunnel construction site according to claim 5, characterized in that: The specific process of step S3 is as follows: S3-1, the start time of the on-site construction worker to be monitored is recorded as time t0; the amount of concrete configured by the on-site construction worker to be monitored is recorded as A; Collect the dust concentration of the monitored site at time t0 as the initial dust concentration of the monitored site, denoted as C t0 ; S3-2, record the current time as time t1; record the real-time equipment power of the ventilation equipment at time t1 as P2 t1 ; The real-time power of the ventilation equipment P2 t1 , input the trained neural network model, and output the real-time ventilation volume of the ventilation equipment, recorded as Q2 t1 ; S3-3, the real-time temperature of the monitored site at time t1 is recorded as T1 t1 ; The real-time humidity of the monitored site at time t1 is recorded as H1 t1 ; T1 t1 The value of T int And H1 t1 The value of H int , input the wet bulb temperature calculation model, and convert the G obtained by the wet bulb temperature calculation model into out , as the real-time wet-bulb temperature of the monitored site at time t1, denoted as G1 t1 .

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