Tunnel blasting smoke exhaust intelligent control system

Abstract

The utility model relates to tunnel engineering construction technical field discloses a kind of tunnel blasting smoke exhaust intelligent control system, including spraying subsystem, multi-sensor detection module and remote control terminal with display;Spraying subsystem includes several spray heads and booster water pump;Remote control terminal with display receives the information of multi-sensor detection module, and controls booster water pump;Remote control terminal with display shows the data detected by multi-sensor detection module;Multi-sensor detection module includes smoke inductor, sound inductor, vibration inductor and air quality detector;The utility model is applied in tunnel or underground cavern group, especially in the environment of poor ventilation and continuous blasting construction needs, can effectively reduce dust in air, dust generated by blasting will not affect operation construction after passing through multiple atomization spraying, can effectively save spraying water resource simultaneously, with good economic benefit and social benefit, suitable for promotion and use.

Description

Technical Field

[0001] This utility model relates to the field of tunnel engineering construction technology, specifically to an intelligent control system for tunnel blasting smoke extraction. Background Technology

[0002] In tunnel engineering, blasting operations and support construction often take place in the same construction space, or multiple interconnected chambers may undergo blasting and other construction operations simultaneously. The smoke generated by blasting has always been a problem in the construction environment. Traditional methods mainly rely on axial flow fans combined with ductwork for ventilation, but the ventilation efficiency is extremely low. Some construction companies have tried using traditional sprinkler systems, such as the existing technology in patent CN220026467U, but the smoke rejection rate is less than 60%, and the dissipation time is 2 hours; manual triggering of sprinklers results in a response delay of 3-5 seconds, by which time the smoke has already spread to adjacent chambers (data from the *Journal of Underground Space and Engineering*, 2023); and the surface water depth reaches 2-5 cm. Furthermore, fixed-duration sprinkler operations generate more than 10 tons of wastewater daily, causing long-term water accumulation on the construction surface, seriously affecting construction progress and the environment. Utility Model Content

[0003] The purpose of this utility model is to solve at least one of the problems in the prior art mentioned above, and to provide an intelligent control system for tunnel blasting smoke extraction, so as to achieve rapid smoke blocking and efficient utilization of water resources.

[0004] To achieve the above objectives, this utility model provides the following technical solution:

[0005] A smart control system for smoke extraction during tunnel blasting includes a spray subsystem, a multi-sensor detection module, and a remote control terminal with a display. The spray subsystem includes several nozzles and a booster pump that supplies water to the nozzles. The remote control terminal with the display receives information from the multi-sensor detection module and controls the booster pump. The remote control terminal with the display displays the data detected by the multi-sensor detection module. The multi-sensor detection module includes a smoke sensor, a sound sensor, a vibration sensor, and an air quality detector installed on the tunnel wall.

[0006] Furthermore, the spray subsystem includes several gate-shaped spray pipes, and several nozzles are evenly arranged along the upper part of the spray pipes; an external water pipe is connected between the booster pump and the spray pipes.

[0007] Furthermore, the inlet end of the booster pump is connected to a coagulant tank.

[0008] Furthermore, a water collection tank is provided below the spray pipe.

[0009] Furthermore, the air quality detector includes a PM2.5 concentration detector.

[0010] Furthermore, the nozzle is an ultra-atomizing nozzle.

[0011] Compared with the prior art, the beneficial effects of this utility model are as follows:

[0012] This invention can accurately identify designated areas within a tunnel and automatically trigger a spray system to quickly reduce the dust concentration in the air at the first moment when a large amount of dust is generated by blasting or vehicle disturbance.

[0013] This utility model integrates advanced vibration sensing technology, which can intelligently detect blasting vibrations and vibrations caused by passing vehicles, and respond in real time; by dynamically adjusting the spraying parameters, it can not only effectively isolate smoke, but also minimize the waste of water resources and energy.

[0014] This invention significantly improves air quality inside tunnels, creating a clean and safe working environment for workers and greatly reducing the risk of occupational diseases. At the same time, the system's ultra-atomizing device greatly reduces water consumption while ensuring dust suppression, achieving efficient use of water resources. The intelligent control system for tunnel blasting smoke exhaust has profound practical significance for improving workers' working conditions, protecting their health, and promoting green construction.

[0015] This invention improves isolation efficiency, achieving a smoke blocking rate of 95% and reducing dissipation time to 15 minutes; it saves 60% of water in actual tests, reducing the average daily water consumption to 4 tons and preventing ground water accumulation; the false alarm rate is less than 0.1%, and dual sensor verification reduces false triggering; the dust suppression time is reduced from an average of 2 hours to an average of 20 to 30 minutes. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the structure of this utility model.

[0017] Figure 2 This is a schematic diagram illustrating the working principle of this utility model.

[0018] Figure 3 This is the control flowchart of this utility model.

[0019] In the diagram: 1. Tunnel inner wall; 2. Galvanized water pipe; 21. Ultra-atomizing nozzle; 3. External water pipe; 31. Booster pump; 311. Coagulant tank; 4. Smoke sensor; 5. Sound and vibration integrated sensor; 6. Wire; 7. Remote control terminal with display; 8. Air quality detector; 9. Water collection tank. Detailed Implementation

[0020] The present invention will be further described in detail below. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention; that is, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] Specific embodiments of the intelligent control system for tunnel blasting smoke extraction provided by this utility model:

[0022] Please see Figure 1-3 The intelligent control system for tunnel blasting smoke extraction includes a spray subsystem, a multi-sensor detection module, an intelligent control module, and a remote control terminal with a display.

[0023] Spray subsystem: multiple parallel spray pipes (galvanized water pipes 2, spacing 1.5-10m), in this embodiment there are three pipes, each pipe is equipped with multiple ultra-atomizing nozzles 21 (working pressure 5-10MPa, atomized particles ≤50μm); the angle of the ultra-atomizing nozzles 21 is dynamically adjustable (45°-90°) to form a three-dimensional atomization isolation layer.

[0024] In this embodiment, the tunnel inner wall 1 serves as the basic installation carrier. Galvanized water pipes 2 are laid along the cross-sectional contour of the tunnel inner wall 1 and fixed with rivets. Ultra-atomizing nozzles 21 are installed at intervals on the galvanized water pipes 2. Ultra-atomizing nozzles 21 are evenly distributed on the column section and arch top of the galvanized water pipes 2 for spraying operations. The hourly water consumption is less than 1 cubic meter. 3 The ultra-atomizing nozzle 21 uses an angle-adjustable nozzle already available on the market. The angle is controlled by utilizing the reaction force of the sprayed water pressure. A galvanized water pipe 2 connects to an external water pipe 3, which in turn connects to a booster pump 31. One end of the booster pump 31 is connected to a coagulant tank 311, which contains water containing coagulant. The other end of the pump is connected to the galvanized water pipe 2 via the external water pipe 3, thus increasing water pressure and delivering the coagulant. The coagulant accelerates the coagulation of fine dust.

[0025] Smoke detector 4, sound and vibration integrated sensor 5, and air quality detector 8 are also installed on the inner wall 1 of the tunnel. The sound and vibration integrated sensor 5 includes a sound sensor and a vibration sensor. Each sensor and the air quality detector 8 are connected to a remote control terminal 7 with a display via wires 6 to realize data transmission and real-time monitoring.

[0026] The multi-sensor detection module includes: a sound sensor (sensitivity ≥40dB) to detect blasting sound waves; a vibration sensor (range 0-50g) to detect vibration and shock waves; and an air quality detector 8 (accuracy ±5μg / m³) including a PM2.5 concentration detector and other detectors to monitor the concentrations of CO, NO2, PM2.5, and PM10 in real time.

[0027] Intelligent control module: Based on a chip and integrated circuit control board, it achieves second-level response and dynamic adjustment. It can respond promptly to data changes collected by the multi-sensor detection module, fuse sensor signals using DS evidence theory, and dynamically adjust the angle of the ultra-atomizing nozzle 21 and water pressure using a fuzzy PID algorithm; it automatically shuts down the system when PM2.5 ≤ 50μg / m³. The intelligent control module is located in the remote control terminal 7 with a display.

[0028] Remote control terminal 7 with display: Located in the duty room, it has a 10.1-inch touch screen that displays multiple indicators such as CO, NO2, and PM2.5 in real time; it has a data storage unit that supports manual / automatic mode switching and historical data retrieval.

[0029] Work process and control methods:

[0030] Monitoring and data transmission: Smoke sensor 4 monitors the smoke concentration in the tunnel in real time, sound and vibration integrated sensor 5 collects sound and vibration signals, air quality detector 8 detects air quality parameters, and all monitoring data is transmitted to a remote control terminal 7 with a display via connecting wire 6 for real-time viewing in the duty room.

[0031] Automatic control activation: When any two of the monitoring data from the smoke sensor 4, the sound and vibration integrated sensor 5, and the air quality detector 8 reach the set value, the automatic control program is triggered. The booster water pump 31 starts, drawing coagulant and water from the coagulant tank 311, and transporting them to the ultra-atomizing nozzle 21 through the external water pipe 3 and the galvanized water pipe 2 to achieve drug atomization and delivery.

[0032] Manual / Automatic Switching Control: The system supports both manual and automatic control modes. In manual control mode, the booster pump 31 can be started and stopped directly via a remote control terminal 7 with a display. In automatic control mode, the system automatically performs spraying operations based on sensor monitoring data.

[0033] A water collection tank 9 is installed at the bottom of the tunnel to collect wastewater after the spraying operation. The wastewater generated by the spraying operation flows into the water collection tank 9 along the tunnel slope, completing centralized collection and treatment, and preventing the wastewater from being discharged indiscriminately.

[0034] Through the above structural design and control process, real-time monitoring of environmental parameters inside the tunnel, automatic spraying operations, and wastewater collection are achieved, thereby improving the intelligence and efficiency of tunnel environmental treatment.

[0035] Intelligent control method for smoke extraction during tunnel blasting, applied in a dual-track tunnel project (controlled by an intelligent control module):

[0036] Step 1: Explosion detection, dual-sensor fusion detection of blasting events; sound sensor (50m from the blast source) and vibration sensor detect signals synchronously, and the blasting event is determined by fusing the sensor signals through DS evidence theory;

[0037] Step 2: Spraying is initiated, triggering the formation of a three-dimensional isolation layer; the three spray pipes open within 0.5 seconds, and the ultra-atomizing nozzle 21 sprays at a pressure of 8MPa (particles 30μm) to form the isolation layer;

[0038] Step 3: Dynamic control, parameters are dynamically adjusted based on the concentration of airborne dust; the air quality detector 8 provides real-time feedback data, and the system adjusts the angle of the ultra-atomizing nozzle 21 (initially 60° → finally 80°) through a fuzzy PID algorithm.

[0039] Step 4: Automatic shutdown. The system will automatically shut down once the air quality meets the standard, that is, the system will automatically stop spraying when PM2.5 ≤ 50 μg / m³.

[0040] In step 1, a dual-sensor decision rule is constructed using DS evidence theory: the "credibility of evidence" for sound sensor (S1) detecting blast sound waves is set to 0.6, the "credibility of evidence" for vibration shock waves detected by vibration sensor (S2) is set to 0.8, and the "credibility of evidence" for airborne dust detected by smoke sensor 4 (S3) is set to 0.9. When S1 outputs a "suspected blast signal" (sound wave frequency 50-200Hz and lasting for more than 0.3 seconds), S2 outputs a "confirmed blast signal" (vibration amplitude exceeding 3cm / s), and S3 outputs a "confirmed smoke signal" (smoke content PM2.5 exceeding 250μg / m³), the DS formula is used to fuse the signals.

[0041] m(explosion) = m S1 (Explosion) ×w S1 +m S2 (Explosion) ×w S2 +m S3 ×w S3

[0042] (m is the "probability of detonation" after evidence fusion, and w is the credibility of sensor evidence).

[0043] When m (blasting) ≥ 0.7, the spraying is triggered within 0.5 seconds; if a single sensor triggers (for example, only S1 indicates blasting, and S2 does not react), it is judged as a "false alarm" (such as noise interference from tunnel mechanical construction), and the system is not triggered, so that the false alarm rate < 0.1% has specific technical support.

[0044] DS evidence theory acts as a "voting judge" for sensor signals. For example, if a sound sensor says "it might be an explosion" (giving 60 points of evidence), and a vibration sensor says "it definitely is an explosion" (giving 80 points of evidence), DS theory will integrate these "evidence scores" to calculate a comprehensive probability (e.g., 90% certainty of an explosion), helping the system decide whether or not to trigger the sprinkler system, thus solving the problem of how to reach a unified decision when multiple sensor signals "argue".

[0045] In step 3, the fuzzy PID algorithm constructs a "dust concentration-control parameter" mapping rule: the PM2.5 concentration is divided into three fuzzy intervals (low: ≤50μg / m³; medium: 50-200μg / m³; high: ≥200μg / m³), and the nozzle angle (θ) and water pressure (P) are adjusted accordingly.

[0046] Low concentration: θ is maintained at 45° (basic barrier angle), P is maintained at 5MPa (basic atomization pressure), and energy-saving standby mode is enabled;

[0047] Medium concentration: θ is increased from 45° to 75° in 5° increments (the denser the dust, the steeper the angle, expanding the atomization coverage), P is increased from 5MPa to 8MPa in 1MPa increments (the greater the pressure, the finer the atomized particles, and the faster the dust is reduced).

[0048] High concentration: Directly triggers "strong intervention mode", θ is fixed at 90° (vertically sprayed towards the explosion source), P is fully charged at 10MPa, and high concentration of smoke and dust is quickly suppressed.

[0049] Meanwhile, the algorithm calculates the "adjusted PM2.5 reduction rate" in real time. If the reduction rate is slow (e.g., less than 10% reduction in 5 minutes), it automatically adds 10% water pressure compensation, giving the dynamic control a clear "if-then" logic.

[0050] Ordinary PID is a "fixed rule" (for example, when PM2.5 exceeds 50, the water pressure is always increased). However, the dust concentration in the tunnel fluctuates, and fuzzy PID can "adjust according to the situation": for example, if the dust rises quickly, the water pressure and nozzle angle are "adjusted sharply"; if it rises slowly, it is "adjusted gently", allowing the spray parameters to "intelligently adjust" according to the changes in dust.

[0051] The dynamic algorithm works as follows: A new parameter t (time) is set. Through multiple statistical analyses, a general functional relationship is established between the concentration u and t, such as u = kt + d, where k is a coefficient and d is a constant. Then, in the environment, the control system monitors in real time whether the values ​​of u and t change as a function. If the relationship is not met, such as if the change in u with t is less than expected, the nozzle angle and spray pressure are automatically increased (i.e., upgraded management). If the change in u with t exceeds expectations, the system maintains the original state or appropriately reduces the angle and spray pressure to reduce water and electricity consumption. It is worth noting that this function can be manually set, for example, to complete all dust suppression work in 3 minutes. Different functions can also be set according to time, such as setting 3 minutes for dust suppression during daytime working hours and 10 minutes for nighttime.

[0052] This invention can accurately identify designated areas within tunnels and automatically trigger a spray system the moment a large amount of dust is generated by blasting or vehicle disturbance, rapidly reducing the dust concentration in the air. Actual measurements show a smoke rejection rate of 95%, with dissipation time shortened to 15 minutes; water savings of 60%, reducing daily water consumption to 4 tons and preventing ground flooding; a false alarm rate of <0.1%, with dual-sensor verification reducing false triggering; and dust suppression time reduced from an average of 2 hours to an average of 20 to 30 minutes.

[0053] Finally, it should be noted that the above description is merely a preferred embodiment of this utility model and is not intended to limit the utility model. Although the utility model has been described in detail with reference to the foregoing embodiments, those skilled in the art can still make modifications to the technical solutions described in the foregoing embodiments without creative effort, or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this utility model should be included within the protection scope of this utility model.

Claims

1. An intelligent control system for smoke extraction in tunnel blasting, characterized in that, The system includes a sprinkler subsystem, a multi-sensor detection module, and a remote control terminal (7) with a display. The sprinkler subsystem includes several sprinkler heads and a booster pump (31) that supplies water to the sprinkler heads. The remote control terminal (7) with a display receives information from the multi-sensor detection module and controls the booster pump (31). The remote control terminal (7) with a display displays the data detected by the multi-sensor detection module. The multi-sensor detection module includes a smoke sensor (4), a sound sensor, a vibration sensor, and an air quality detector (8) installed on the inner wall (1) of the tunnel.

2. The intelligent control system for tunnel blasting smoke extraction according to claim 1, characterized in that, The spray subsystem includes several gate-shaped spray pipes, and several nozzles are evenly arranged along the upper part of the spray pipes; an external water pipe (3) is connected between the booster water pump (31) and the spray pipes.

3. The intelligent control system for tunnel blasting smoke extraction according to claim 2, characterized in that, The inlet end of the booster pump (31) is connected to a coagulant tank (311).

4. The intelligent control system for tunnel blasting smoke extraction according to claim 2, characterized in that, A water collection tank (9) is provided below the spray pipe.

5. The intelligent control system for tunnel blasting smoke extraction according to claim 1, characterized in that, The air quality detector (8) includes a PM2.5 concentration detector.

6. The intelligent control system for tunnel blasting smoke extraction according to claim 1, characterized in that, The nozzle is an ultra-atomizing nozzle (21).

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