Tunnel soot monitoring and processing method and system

Abstract

The application relates to the technical field of tunnel monitoring methods, in particular to a tunnel smoke dust monitoring and processing method and system. When the application is applied, the building tunnel can be automatically monitored and dedusted, and excellent dedusting effect can be achieved. A monitoring track and a monitoring trolley are arranged in the building tunnel, the monitoring trolley stops at each detection point, a smoke dust sensing device is used to detect the smoke dust concentration, when the concentration is less than a preset value, the monitoring trolley goes to the next point, when the concentration is greater than or equal to the preset concentration, the swing speed is matched according to the concentration, and the swing arm and the dedusting device are used for scanning and swing dedusting, meanwhile, the swing speed is corrected according to the historical smoke dust reference value, after dedusting, the monitoring trolley stops and waits for the second detection average value to judge whether the standard is reached, if not, the monitoring trolley alarms and repeats the dedusting, if the standard is not reached for many times, it is determined that there is a hidden trouble of continuously generating smoke dust, and finally, all the detection point inspection and dedusting work are completed.

Description

Technical Field

[0001] This application relates to the technical field of tunnel monitoring methods, specifically to methods and systems for monitoring and treating tunnel dust. Background Technology

[0002] During the construction and operation of tunnels, dust pollution within the tunnels has always been a significant factor affecting construction safety and air quality. Traditional methods for monitoring and treating tunnel dust mostly rely on fixed-point monitoring equipment and manual dust removal. Fixed-point monitoring suffers from limited coverage, failing to accurately and promptly grasp changes in dust concentration throughout the tunnel. Manual dust removal is not only inefficient but also poses safety hazards, failing to meet the timeliness and effectiveness requirements for dust control within tunnels. Furthermore, existing tunnel dust treatment technologies often operate in fixed modes, unable to adjust dust removal strategies based on dust concentration, resulting in poor dust removal effectiveness. In conclusion, how to automate the monitoring and dust removal of construction tunnels to achieve excellent dust control results is a technical problem that needs to be solved in this field. Summary of the Invention

[0003] In view of this, this application provides a method and system for monitoring and treating dust in tunnels, which can automatically monitor and remove dust in building tunnels and achieve excellent dust removal effect.

[0004] In a first aspect, this application provides a method for monitoring and treating dust in tunnels, applied to building tunnels. The building tunnel is equipped with a monitoring track and a monitoring trolley. Multiple detection points are located along the tunnel's extension direction. The monitoring track is arranged along the tunnel's extension direction. The monitoring trolley is slidably connected to the monitoring track. The monitoring trolley is equipped with a dust sensor and a swing arm, and the swing arm is equipped with a dust removal device. The method for monitoring and treating dust in tunnels includes: controlling the monitoring trolley to run at a uniform speed along the monitoring track in a first direction; controlling the monitoring trolley to stop at each of the detection points; controlling the dust sensor to detect the dust concentration at the current location; if the dust concentration is greater than or equal to a preset concentration, matching a corresponding swing speed according to the dust concentration; and controlling the swing arm to swing at the currently corresponding swing speed. The system performs dust removal using the dust removal device; obtains historical dust reference values ​​at the current parking position, calculates corresponding scan correction coefficients based on these historical dust reference values, and corrects the swing speed using these scan correction coefficients; if the dust concentration is lower than the preset concentration, it controls the swing arm and the dust removal device to stop; it controls the monitoring trolley to stop and wait for a first preset time, and controls the dust sensor to detect the average of two detections within the first preset time; if the average of the two detections is lower than the preset concentration, it controls the monitoring trolley to move to the next detection point; if the average of the two detections is greater than or equal to the preset concentration, it generates a first warning message and controls the swing arm to swing and the dust removal device to perform dust removal; and if the monitoring trolley completes all the detection points, the current detection is completed and a detection completion message is generated.

[0005] In conjunction with the first aspect, one possible implementation further includes: summarizing all the dust concentrations and the average values ​​of the secondary detections corresponding to the current detection, comparing them with all the dust concentrations and the average values ​​of the secondary detections corresponding to other detections, and comparing them one by one according to the corresponding detection points to obtain a first change value of the dust concentration corresponding to each detection point, and a second change value of the average value of the secondary detections corresponding to each detection point; if there is a first change value that exceeds a first preset change range, then generating first abnormal information corresponding to the detection point; and if there is a second change value that exceeds a second preset change range, then generating second abnormal information corresponding to the detection point.

[0006] In conjunction with the first aspect, in one possible implementation, the monitoring vehicle is equipped with an image device; wherein controlling the monitoring vehicle to stop at each of the detection points includes: acquiring image data of the current position of the monitoring vehicle with a preset orientation through the image device; determining whether the detection point exists based on the image data; and if the detection point is identified and matches the pre-stored positioning of the detection point, then stopping is executed.

[0007] In conjunction with the first aspect, one possible implementation further includes: if the visibility of the image data is lower than a preset visibility, then stopping the vehicle and controlling the smoke and dust sensing device to detect the smoke and dust concentration at the current location.

[0008] In conjunction with the first aspect, in one possible implementation, obtaining the historical smoke and dust reference value at the current parking location, obtaining the corresponding scan correction coefficient based on the historical smoke and dust reference value, and correcting the oscillation speed based on the scan correction coefficient includes: backtracking the smoke and dust data of the current parking location with a preset number of historical detections; and calculating the average smoke and dust concentration based on the smoke and dust data to obtain the historical smoke and dust reference value.

[0009] In conjunction with the first aspect, in one possible implementation, after controlling the monitoring vehicle to stop at each of the detection points, the method further includes: obtaining a corresponding delay duration based on the vehicle speed of the monitoring vehicle; the greater the vehicle speed, the greater the corresponding delay duration; wherein, controlling the dust sensor to detect the dust concentration at the current location includes: after the monitoring vehicle stops for the duration of the delay, controlling the dust sensor to detect the dust concentration at the current location.

[0010] In conjunction with the first aspect, one possible implementation further includes: if the second abnormal information is obtained, controlling the monitoring vehicle to move to the position corresponding to the detection point; controlling the dust sensor to continuously detect the dust fluctuation value within a second preset time period; and if the dust fluctuation value is greater than a preset fluctuation range, generating a second warning message.

[0011] In conjunction with the first aspect, one possible implementation further includes: obtaining a dust removal command issued by a host server; obtaining the detection position and dust removal intensity of the corresponding detection point based on the dust removal command; controlling the monitoring trolley to move to the detection position; controlling the swing arm to perform reciprocating swing at a swing speed and swing time corresponding to the dust removal intensity; and controlling the monitoring trolley to perform dust removal work at a working power and working time corresponding to the dust removal intensity.

[0012] In conjunction with the first aspect, one possible implementation further includes: if the monitoring vehicle completes the dust removal command, then controlling the monitoring vehicle to return to the position of the detection point before the dust removal command was issued.

[0013] Secondly, this application provides a tunnel dust monitoring and treatment system applied to a building tunnel. The building tunnel is equipped with a monitoring track and a monitoring trolley. Multiple detection points are arranged along the tunnel's extension direction. The monitoring track is arranged along the tunnel's extension direction. The monitoring trolley is slidably connected to the monitoring track. The monitoring trolley is equipped with a dust sensor and a swing arm. The swing arm is equipped with a dust removal device. The tunnel dust monitoring and treatment system includes: a monitoring control module configured to: control the monitoring trolley to run at a uniform speed along the monitoring track in a first direction; control the monitoring trolley to stop at each of the detection points; control the dust sensor to detect the dust concentration at the current location; if the dust concentration is greater than or equal to a preset concentration, match a corresponding swing speed according to the dust concentration; the higher the dust concentration, the slower the swing speed; control the swing arm to swing at the currently corresponding swing speed, and perform dust removal through the dust removal device; and a swing speed compensation module, communicatively connected to the monitoring control module. The swing speed compensation module is configured to: The system comprises: obtaining historical dust reference values ​​at the current parking location; obtaining a corresponding scan correction coefficient based on the historical dust reference values; and correcting the swing speed based on the scan correction coefficient; the scan correction coefficient is inversely proportional to the historical dust reference values; a re-inspection module, communicatively connected to the monitoring and control module, configured to: control the swing arm and the dust removal device to stop if the dust concentration is lower than the preset concentration; control the monitoring trolley to stop and wait for a first preset time, and control the dust sensor to detect the average value of two detections within the first preset time; if the average value of two detections is lower than the preset concentration, control the monitoring trolley to move to the next detection point; if the average value of two detections is greater than or equal to the preset concentration, generate a first warning message and control the swing arm to swing and control the dust removal device to perform dust removal; and a decision module, communicatively connected to the monitoring and control module and the re-inspection module respectively, configured to: if the monitoring trolley completes all the detection points, the current detection is completed and a detection completion message is generated.

[0014] This application enables automated monitoring and dust removal in construction tunnels, achieving excellent dust control results. By setting up a monitoring track and trolley within the tunnel, the trolley stops at each detection point, using a dust sensor to detect dust concentration. If the concentration is below a preset value, it moves to the next point; if the concentration is above or equal to the preset value, the oscillation speed is matched to the concentration, and the oscillation is scanned and oscillated using a swing arm and dust removal device for dust removal. Simultaneously, the oscillation speed is adjusted based on historical dust reference values. After dust removal, the system stops and waits to acquire the average of secondary detection values ​​to determine if the standard is met. If the standard is not met, an alarm is triggered, and dust removal is repeated. Multiple failures to meet the standard indicate a potential malfunction of continuously generating dust. Finally, the inspection and dust removal work at all detection points is completed. This method achieves effective monitoring and treatment of tunnel dust, improves dust removal efficiency through scanning dust removal, enhances dust removal effect by adjusting the dust removal strategy based on concentration and historical data, ensures dust removal quality through a secondary detection mechanism, and can promptly detect potential malfunctions, thus protecting air quality within the tunnel. Attached Figure Description

[0015] Figure 1 The diagram shown is a schematic representation of the steps of a tunnel dust monitoring and treatment method according to an embodiment of this application.

[0016] Figure 2 The diagram shown is a partial structural schematic of a building tunnel provided in an embodiment of this application.

[0017] Figure 3 The diagram shown is a schematic representation of the steps for generating exception information according to another embodiment of this application.

[0018] Figure 4 The diagram shows a method step for dual verification detection points based on image recognition, provided in another embodiment of this application.

[0019] Figure 5 The diagram shown is a schematic representation of the steps of a method for monitoring dust removal based on visibility during temporary parking, according to another embodiment of this application.

[0020] Figure 6 The diagram shows a method for calculating historical dust reference values ​​according to another embodiment of this application.

[0021] Figure 7 The diagram shown is a schematic representation of the delayed execution method steps provided in an embodiment of this application.

[0022] Figure 8 The diagram shows a method step for re-inspection based on second anomaly information provided in an embodiment of this application.

[0023] Figure 9 The diagram shown is a schematic representation of the steps of a command-based dust removal method according to an embodiment of this application.

[0024] Figure 10 The diagram shows a method step for dust removal following a command, according to an embodiment of this application.

[0025] Figure 11 The figure shown is a schematic diagram of the system structure of a tunnel dust monitoring and treatment system provided in an embodiment of this application. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0027] An exemplary method for monitoring and treating dust in tunnels is as follows:

[0028] Figure 2 The diagram shown is a partial structural schematic of a building tunnel according to an embodiment of this application. This application provides a method for monitoring and treating tunnel smoke and dust, such as... Figure 2 As shown, this method is applied to a building tunnel 10. The building tunnel 10 is equipped with a monitoring track 3 and a monitoring trolley 4. In urban building tunnels 10, tracks are generally provided to facilitate construction. The monitoring track 3 can be an existing track or laid at a specific location within the building tunnel 10. Multiple detection points 2 are provided along the tunnel's extension direction within the building tunnel 10. These detection points 2 can be evenly distributed or arranged as required. The monitoring track 3 is arranged along the tunnel's extension direction. The monitoring trolley 4 is slidably connected to the monitoring track 3. The monitoring trolley 4 is equipped with a dust sensor and a swing arm 5. The swing arm 5 is equipped with a dust removal device 6.

[0029] Figure 1 The diagram shown is a schematic representation of the method steps for monitoring and treating tunnel dust according to an embodiment of this application. Figure 1 As shown, the methods for monitoring and treating tunnel dust include:

[0030] Step 110: Control the monitoring trolley 4 to run at a constant speed along the monitoring track 3 in the first direction.

[0031] Step 120: Control the monitoring vehicle 4 to stop at each detection point 2.

[0032] In this step, detection points 2 are pre-set, for example, one detection point 2 can be set every 10 meters, or at a predetermined location in the building tunnel 10, or at a location in the building tunnel 10 where smoke and dust are easily generated. When the monitoring vehicle 4 travels at a constant speed in the first direction, it stops at each detection point 2 to perform smoke and dust detection. After the entire detection process is completed, the monitoring vehicle 4 returns to the detection starting point in the opposite direction of the first direction. The detection starting point is generally set at the entrance of the building tunnel 10, or at a predetermined location. Sensors can be installed at detection points 2. The monitoring vehicle 4 is equipped with sensors that match the sensors. When the monitoring vehicle 4 reaches detection point 2 and senses the sensors, it stops and prepares to begin smoke and dust detection at detection point 2. Specifically, the sensors can use radio frequency identification (RFID) technology; or the monitoring vehicle 4 can use machine vision to identify whether its current position has reached detection point 2; or it can use pre-stored map data to control the monitoring vehicle 4 to stop at detection point 2.

[0033] Step 130: Control the dust sensor to detect the dust concentration at the current location.

[0034] In this step, if the detected dust concentration is lower than the preset concentration, it can be considered that the dust concentration is low and no dust removal is required. The monitoring trolley 4 then proceeds to the next detection point 2. The preset concentration is determined according to the detection requirements. In building tunnels 10 with high dust removal requirements, the preset concentration is appropriately increased, while in building tunnels 10 with low dust removal requirements, the preset concentration can be decreased.

[0035] Step 140: If the dust concentration is greater than or equal to the preset concentration, then match the corresponding oscillation speed according to the dust concentration.

[0036] In this step, the higher the dust concentration, the slower the swing speed. A pre-set relationship between dust concentration and swing speed is used in this step. This step takes into account that if the dust concentration is too high, the swing arm 5 may move too fast and fail to remove dust effectively. The denser the dust, the slower the swing speed, thereby improving the dust removal effect.

[0037] Step 150: Control the swing arm 5 to swing at the current corresponding swing speed, and perform dust removal through the dust removal device 6.

[0038] In this step, the swing arm 5 drives the dust removal device 6 to perform scanning and oscillating dust removal. This scanning dust removal method can cover a large area, improving dust removal efficiency. (Refer to...) Figure 2 Adjust the length and swing angle range θ of the swing arm 5 to sweep across the cross section where the detection point 2 is located over a wide area without colliding with the inner wall of the building tunnel 10. The swing arm 5 can be a commonly available mechanical swing device.

[0039] Step 160: Obtain the historical smoke and dust reference value at the current parking location, obtain the corresponding scanning correction coefficient based on the historical smoke and dust reference value, and correct the swing speed based on the scanning correction coefficient.

[0040] In this step, the scanning correction coefficient is inversely proportional to the historical dust reference value. This step considers the frequent occurrence of excessive dust in tunnels, and the historical dust reference value influences the dust variation trend within the tunnel. A higher historical dust reference value indicates a high probability of a potential malfunction at the current parking location, leading to frequent high-concentration conditions, necessitating a further reduction in the oscillation speed using the scanning correction coefficient. Conversely, a lower historical dust reference value indicates a high probability of no potential malfunction at the current parking location, allowing for an appropriate increase in the oscillation speed through the scanning correction coefficient to improve efficiency. For example, the scanning correction coefficient ranges from 0.5 to 1.3. When the historical dust reference value is equal to the current dust concentration, the scanning correction coefficient is 1; when the historical dust reference value is greater than the current dust concentration, the scanning correction coefficient is less than 1; when the historical dust reference value is greater than twice the current dust concentration, the scanning correction coefficient is 0.5; when the historical dust reference value is less than the current dust concentration, the scanning correction coefficient is greater than 1; and when the historical dust reference value is less than twice the current dust concentration, the scanning correction coefficient is 1.3. The above value ranges are merely examples and can be determined based on actual conditions. For building tunnels 10 prone to smoke and dust, the minimum value of the scanning correction coefficient range can be reduced; for building tunnels 10 less prone to smoke and dust, the minimum and maximum values ​​of the scanning correction coefficient range can be increased. Therefore, the oscillation speed is corrected based on air visibility.

[0041] Step 170: If the dust concentration is lower than the preset concentration, control the swing arm 5 and the dust removal device 6 to stop.

[0042] Step 180: Control the monitoring trolley 4 to stop and wait for a first preset time, and control the dust sensor to detect the average value of the two detections within the first preset time.

[0043] In this step, after the first dust removal, the machine is stopped and waited for a first preset time, and the average dust concentration within the first preset time is continuously monitored to obtain the average value of the second detection. This allows us to know whether the dust concentration at the current stopping position has increased. If it has increased, it indicates that there is a potential fault that generates dust or that the first dust removal did not meet the standard.

[0044] Step 190: If the average value of the two tests is lower than the preset concentration, control the monitoring vehicle 4 to move to the next detection point 2.

[0045] Step 200: If the average value of the two tests is greater than or equal to the preset concentration, a first warning message is generated and the swing arm 5 is controlled to swing and the dust removal device 6 is controlled to perform dust removal.

[0046] In this step, if the average value of the secondary detections is greater than the preset concentration, it indicates a potential hazard of continuous smoke and dust generation. A first warning message needs to be generated for alarm purposes, and simultaneously, oscillation and dust removal are performed. The oscillation speed is the same as the one corrected in step 160. Then, steps 150-160-170-180 are repeated. If the subsequent average value of the secondary detections is lower than the preset concentration, step 190 is executed. If the subsequent average value of the secondary detections is greater than or equal to the preset concentration, step 190 is triggered, and steps 150-160-170-180 are repeated until the average value of the secondary detections is lower than the preset concentration. In some embodiments, the number of times steps 150-160-170-180 are repeated can be limited to improve overall work efficiency. If the average value of the secondary detections is greater than or equal to the preset concentration multiple times (e.g., more than 3 times), it can be determined that there is a potential hazard of continuous smoke and dust generation at this location. Dust removal can be skipped, and step 190 can be executed directly. During this process, a first warning message is reported for staff to make decisions and eliminate the hazard in a timely manner.

[0047] Step 210: If the monitoring vehicle 4 completes all detection points 2, then the current detection is completed and detection completion information is generated.

[0048] In this step, the completion of the inspection and dust removal work at each inspection point 2 of the tunnel 10 is indicated by the completion of the operation of the monitoring vehicle 4 at all inspection points 2.

[0049] This embodiment enables automated monitoring and dust removal in building tunnels, achieving excellent dust removal results. A monitoring track 3 and a monitoring trolley 4 are installed within the tunnel. The monitoring trolley 4 stops at each detection point 2, using a dust sensor to detect dust concentration. If the concentration is below a preset value, it moves to the next point; if the concentration is above or equal to the preset value, the swing speed is matched to the concentration, and the swing arm 5 and dust removal device 6 scan and swing to remove dust. Simultaneously, the swing speed is adjusted based on historical dust reference values. After dust removal, the trolley stops and waits to acquire the average of secondary detection values ​​to determine if the standard is met. If the standard is not met, an alarm is triggered, and dust removal is repeated. Multiple failures to meet the standard indicate a potential hazard of continuous dust generation. Finally, the inspection and dust removal work at all detection points is completed. This method achieves effective monitoring and treatment of tunnel dust, improves dust removal efficiency through scanning dust removal, enhances dust removal effect by adjusting the dust removal strategy based on concentration and historical data, ensures dust removal quality through a secondary detection mechanism, and can promptly detect potential hazard, thus protecting air quality within the tunnel.

[0050] Figure 3 The diagram illustrates the steps of a method for generating exception information according to another embodiment of this application. In one embodiment, as shown... Figure 3 As shown, the tunnel dust monitoring and treatment method also includes:

[0051] Step 220: Summarize all dust concentrations and the average of secondary detections corresponding to the current detection, and compare them with all dust concentrations and the average of secondary detections corresponding to other detections, according to the corresponding detection points 2, to obtain the first change value of dust concentration corresponding to each detection point 2, and the second change value of the average of secondary detections corresponding to each detection point 2.

[0052] Step 230: If there is a first change value that exceeds the first preset change range, then generate the first abnormal information corresponding to detection point 2.

[0053] Step 240: If there is a second change value that exceeds the second preset change range, then generate the second abnormal information corresponding to detection point 2.

[0054] In this embodiment, after completing the overall inspection and dust removal of the building tunnel 10, the data is summarized and compared with the results of different batches of tests. These different batches can be the previous batch, the batch before that, etc. The data from different batches at the same test point 2 are compared. If the first change value of a certain test point 2 exceeds the first preset change range, it indicates that the dust fluctuation at that test point 2 is significant, possibly indicating dust generation events such as construction activities. The dust removal intensity at that test point 2 can be increased based on the first anomaly information. If the second change value of a certain test point 2 exceeds the second preset change range, it further indicates that there is a high probability of a potential malfunction at that test point 2 causing continuous dust generation, leading to a continuous increase in dust concentration. Timely maintenance of that test point 2 can be carried out based on the second anomaly information to eliminate the potential malfunction.

[0055] Figure 4 The diagram illustrates the steps of a method for dual verification detection points based on image recognition, according to another embodiment of this application. In one embodiment, the monitoring vehicle 4 is equipped with an image device;

[0056] Step 120 includes:

[0057] Step 121: Collect image data of the current position and preset orientation of the monitoring vehicle 4 using the image device.

[0058] Step 122: Determine whether detection point 2 exists based on the image data.

[0059] Step 123: If detection point 2 is identified and matches the pre-stored location of detection point 2, then stop the vehicle.

[0060] In this embodiment, image recognition is used to determine whether the vehicle has reached detection point 2, and pre-stored positioning is used to verify its accuracy. This dual positioning mechanism ensures that the monitoring vehicle 4 stops at the precise detection point 2. Specifically, the image recognition method can be purely visual, for example, by setting a visible light reflective marker or an infrared light emitting marker at detection point 2. The monitoring vehicle 4 is equipped with a visible light source or infrared light source pointing forward. When the light source illuminates the marker, it produces a reflection, making it easy for the image device to capture. The image device takes a picture in the direction of travel. If the captured marker matches the pre-stored positioning, a stop command is issued, controlling the monitoring vehicle 4 to gradually decelerate and stop until it reaches the location of detection point 2. Specifically, the pre-stored positioning can be an exact location or a range. The image device can be a depth-sensing image device to detect the distance between the monitoring vehicle 4 and detection point 2, thereby controlling the vehicle to stop. (See reference...) Figure 2 Multiple detection points 2 can be set around the tunnel section where the detection location is located in the building tunnel 10. Multiple detection points 2 can improve the success rate and efficiency of the detection location identification, so that the monitoring vehicle 4 can further accurately identify and stop.

[0061] Figure 5 The diagram shown is a schematic representation of the steps of a method for monitoring dust removal based on visibility during temporary parking, according to another embodiment of this application. In one embodiment, as... Figure 5 As shown, the tunnel dust monitoring and treatment method also includes:

[0062] Step 250: If the visibility of the image data is lower than the preset visibility, then stop the vehicle. Then proceed to step 130.

[0063] In this embodiment, image processing is used to detect the real-time visibility of the image ahead of the monitoring vehicle 4 during its operation. When the visibility is lower than a preset level, it is determined that the dust concentration at this location is too high. The vehicle can then be stopped, and the dust concentration can be accurately detected by the dust sensor. Steps 140-210 can then be executed. This embodiment is independent of the detection requirements of detection point 2. If low visibility is detected while the monitoring vehicle 4 is running, a temporary decision can be made to perform dust detection and dust removal. After executing step 250, the background data can be updated to add the stopping location as a new detection point 2.

[0064] Figure 6 The diagram illustrates the steps of a method for calculating historical dust reference values ​​according to another embodiment of this application. In one embodiment, the monitoring vehicle 4 is equipped with an image acquisition device, such as... Figure 6 As shown, step 160 includes:

[0065] Step 161: Backtrack the smoke and dust data of the current parking location based on the historical preset detection count.

[0066] Step 162: Calculate the average dust concentration based on the dust data to obtain historical dust reference values.

[0067] In this embodiment, historical smoke and dust data are used to calculate an average value to obtain a historical smoke and dust reference value, thus providing a historically valuable reference value. Specifically, the preset number of historical detections can be set to any value between 2 and 10; tracing back too many times diminishes the reference value. For example, if the preset number of historical detections is 5, the average smoke and dust concentration of the parking location is obtained by averaging the smoke and dust concentrations of the past 5 times.

[0068] Figure 7 The diagram illustrates the steps of a delayed execution method according to an embodiment of this application. In one embodiment, as shown... Figure 7 As shown, after step 120, the method further includes:

[0069] Step 260: Obtain the corresponding delay duration based on the speed of the monitoring vehicle 4.

[0070] In this step, the higher the vehicle speed, the longer the corresponding delay time.

[0071] Step 130 includes:

[0072] Step 131: After monitoring the duration of the continuous delay of the car 4's parking, control the dust sensor to detect the dust concentration at the current location.

[0073] In this embodiment, considering that the monitoring vehicle 4 will cause airflow within the tunnel during operation, thus affecting the smoke and dust concentration, a faster vehicle speed results in faster airflow, which will cause smoke and dust to move around, leading to inaccurate smoke and dust detection results. Therefore, the delay time needs to be increased. Conversely, a slower vehicle speed will not cause as much airflow, thus reducing the amount of smoke and dust moving around and allowing for a shorter delay time. After the delay time, the smoke and dust near the monitoring vehicle 4 can stabilize for a period of time before the smoke and dust concentration is measured, resulting in more accurate data.

[0074] Figure 8 The diagram illustrates the steps of a method for re-examining based on second anomaly information according to an embodiment of this application. In one embodiment, as shown... Figure 8 As shown, the tunnel dust monitoring and treatment method also includes:

[0075] Step 270: If the second abnormal information is obtained, control the monitoring car 4 to run to the position of the corresponding detection point 2.

[0076] Step 280: Control the smoke and dust sensing device to continuously detect the smoke and dust fluctuation value within a second preset time period.

[0077] Step 290: If the smoke and dust fluctuation value is greater than the preset fluctuation range, a second warning message is generated.

[0078] In this embodiment, when a second abnormality is detected, it indicates that there is a high probability of a continuous smoke and dust generation hazard at detection point 2, leading to a continuous increase in smoke and dust concentration. The monitoring vehicle 4 is then directed to the detection point 2 corresponding to the second abnormality for re-inspection. The re-inspection lasts for a second preset duration. If the smoke and dust fluctuation value within this duration exceeds a preset fluctuation range, it further indicates a continuous smoke and dust generation hazard at that location. At this point, a second warning is generated. The priority and warning level of the second warning are higher than those of the second abnormality.

[0079] Figure 9 The diagram illustrates the steps of a command-based dust removal method according to an embodiment of this application. In one embodiment, as shown... Figure 9 As shown, the tunnel dust monitoring and treatment method also includes:

[0080] Step 300: Obtain the dust removal command issued by the host server.

[0081] Step 310: Obtain the detection position and dust removal intensity of the corresponding detection point 2 according to the dust removal command.

[0082] Step 320: Control the monitoring vehicle 4 to proceed to the detection location.

[0083] Step 330: Control the swing arm 5 to perform reciprocating swing at a swing speed and swing time corresponding to the dust removal intensity.

[0084] Step 340: Control the monitoring trolley 4 to perform dust removal work with the working power and working time corresponding to the dust removal intensity.

[0085] In this embodiment, a command-based dust removal system is introduced. When an additional dust removal command is issued, the monitoring vehicle 4 performs dust removal work according to the command. The dust removal command includes the detection location and the dust removal intensity, which can improve the dust removal flexibility of this application.

[0086] Figure 10 The diagram shows a schematic representation of the steps involved in a dust removal method according to an embodiment of this application. In one embodiment, as shown... Figure 10 As shown, the tunnel dust monitoring and treatment method also includes:

[0087] Step 350: If the monitoring trolley 4 has completed the dust removal command, then control the monitoring trolley 4 to return to the position of detection point 2 before the dust removal command was issued.

[0088] Based on steps 300-340, after the dust removal command is completed, the monitoring trolley returns to the position before the dust removal command was issued and continues to perform automatic inspection and dust removal work.

[0089] An example tunnel dust monitoring and treatment system is as follows:

[0090] This application also provides a tunnel dust monitoring and treatment system, referring to... Figure 2 As shown, this method is applied to a building tunnel 10. The building tunnel 10 is equipped with a monitoring track 3 and a monitoring trolley 4. In urban building tunnels 10, tracks are generally provided to facilitate construction. The monitoring track 3 can be an existing track or laid at a specific location within the building tunnel 10. Multiple detection points 2 are provided along the tunnel's extension direction within the building tunnel 10. These detection points 2 can be evenly distributed or arranged as required. The monitoring track 3 is arranged along the tunnel's extension direction. The monitoring trolley 4 is slidably connected to the monitoring track 3. The monitoring trolley 4 is equipped with a dust sensor and a swing arm 5. The swing arm 5 is equipped with a dust removal device 6.

[0091] Figure 11 The diagram shown is a schematic representation of a tunnel dust monitoring and treatment system according to an embodiment of this application. Figure 11 As shown, the tunnel dust monitoring and treatment system includes: a monitoring and control module 1101, a swing speed compensation module 1102, a re-inspection module 1103, and a decision module 1104.

[0092] The monitoring and control module 1101 is configured to: control the monitoring trolley 4 to run at a constant speed along the monitoring track 3 in the first direction; control the monitoring trolley 4 to stop at each detection point 2; control the dust sensor to detect the dust concentration at the current location; if the dust concentration is greater than or equal to the preset concentration, then match the corresponding swing speed according to the dust concentration; the higher the dust concentration, the slower the swing speed; control the swing arm 5 to swing at the corresponding swing speed, and perform dust removal through the dust removal device 6.

[0093] The swing speed compensation module 1102 is connected to the monitoring and control module 1101. The swing speed compensation module is configured to: obtain the historical smoke and dust reference value at the current parking position, obtain the corresponding scanning correction coefficient based on the historical smoke and dust reference value, and correct the swing speed based on the scanning correction coefficient; the scanning correction coefficient is inversely proportional to the historical smoke and dust reference value.

[0094] The re-inspection module 1103 is communicatively connected to the monitoring and control module 1101. The re-inspection module 1103 is configured as follows: if the dust concentration is lower than the preset concentration, control the swing arm 5 and the dust removal device 6 to stop; control the monitoring trolley 4 to stop and wait for a first preset time, and control the dust sensor to detect the average value of the second detection within the first preset time; if the average value of the second detection is lower than the preset concentration, control the monitoring trolley 4 to run to the next detection point 2; if the average value of the second detection is greater than or equal to the preset concentration, generate a first warning message and control the swing arm 5 to swing and control the dust removal device 6 to perform dust removal.

[0095] The decision module 1104 is connected to the monitoring and control module 1101 and the re-inspection module 1103 respectively. The decision module 1104 is configured to: if the monitoring vehicle 4 completes all detection points 2, then the current detection is completed and detection completion information is generated.

[0096] This embodiment enables automated monitoring and dust removal in building tunnels, achieving excellent dust removal results. A monitoring track 3 and a monitoring trolley 4 are installed within the tunnel. The monitoring trolley 4 stops at each detection point 2, using a dust sensor to detect dust concentration. If the concentration is below a preset value, it moves to the next point; if the concentration is above or equal to the preset value, the swing speed is matched to the concentration, and the swing arm 5 and dust removal device 6 scan and swing to remove dust. Simultaneously, the swing speed is adjusted based on historical dust reference values. After dust removal, the trolley stops and waits to acquire the average of secondary detection values ​​to determine if the standard is met. If the standard is not met, an alarm is triggered, and dust removal is repeated. Multiple failures to meet the standard indicate a potential hazard of continuous dust generation. Finally, the inspection and dust removal work at all detection points is completed. This method achieves effective monitoring and treatment of tunnel dust, improves dust removal efficiency through scanning dust removal, enhances dust removal effect by adjusting the dust removal strategy based on concentration and historical data, ensures dust removal quality through a secondary detection mechanism, and can promptly detect potential hazard, thus protecting air quality within the tunnel.

[0097] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the application to the necessity of employing the aforementioned specific details for implementation.

[0098] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0099] It should also be noted that in the apparatus, equipment, and methods of this application, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of this application.

[0100] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features of the invention herein.

[0101] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications or equivalent substitutions made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for monitoring and treating tunnel dust, characterized in that, Applied to building tunnels, the building tunnel is equipped with a monitoring track and a monitoring trolley. Multiple detection points are set up in the building tunnel along the tunnel extension direction. The monitoring track is arranged along the tunnel extension direction of the building tunnel. The monitoring trolley is slidably connected to the monitoring track. The monitoring trolley is equipped with a dust sensor and a swing arm. The swing arm is equipped with a dust removal device. The tunnel dust monitoring and treatment method includes: Control the monitoring trolley to run at a constant speed along the monitoring track in a first direction; Control the monitoring vehicle to stop at each of the detection points; The dust sensor is controlled to detect the dust concentration at the current location; If the dust concentration is greater than or equal to the preset concentration, then the corresponding oscillation speed is matched according to the dust concentration; The swing arm is controlled to swing at the currently corresponding swing speed, and dust removal is performed by the dust removal device. Obtain historical smoke and dust reference values ​​at the current parking location, obtain corresponding scanning correction coefficients based on the historical smoke and dust reference values, and correct the oscillation speed based on the scanning correction coefficients; If the dust concentration is lower than the preset concentration, then the swing arm and the dust removal device will be shut down. The monitoring trolley is controlled to stop and standby for a first preset time, and the dust sensor is controlled to detect the average value of two detections within the first preset time. If the average value of the second detection is lower than the preset concentration, the monitoring vehicle is controlled to move to the next detection point; If the average value of the secondary detections is greater than or equal to the preset concentration, a first warning message is generated, and the swing arm is controlled to swing and the dust removal device is controlled to perform dust removal; and If the monitoring vehicle completes all the detection points, the current detection is completed and detection completion information is generated; Also includes: Summarize all the dust concentrations and the average values ​​of the secondary detections corresponding to the current detection, and compare them with all the dust concentrations and the average values ​​of the secondary detections corresponding to other detections, and compare them one by one according to the corresponding detection points to obtain the first change value of the dust concentration corresponding to each detection point, and the second change value of the average value of the secondary detections corresponding to each detection point. If a first change value exceeds a first preset change range, then first anomaly information corresponding to the detection point is generated; and If there is a second change value that exceeds the second preset change range, then generate second abnormal information corresponding to the detection point; Also includes: If the second abnormal information is obtained, the monitoring vehicle is controlled to move to the position corresponding to the detection point; The smoke and dust sensing device is controlled to continuously detect smoke and dust fluctuation values ​​within a second preset time period; and If the smoke and dust fluctuation value is greater than the preset fluctuation range, a second warning message will be generated.

2. The method for monitoring and treating tunnel dust according to claim 1, characterized in that, The monitoring vehicle is equipped with an imaging device; The step of controlling the monitoring vehicle to stop at each of the detection points includes: The imaging device acquires image data of the current position and preset orientation of the monitoring vehicle; Based on the image data, determine whether the detection point exists; and If the detection point is identified and matches the pre-stored location of the detection point, then parking is executed.

3. The method for monitoring and treating tunnel dust according to claim 2, characterized in that, Also includes: If the visibility of the image data is lower than the preset visibility, then the system will stop and control the smoke and dust sensor to detect the smoke and dust concentration at the current location.

4. The method for monitoring and treating tunnel dust according to claim 1, characterized in that, The steps of obtaining historical smoke and dust reference values ​​at the current parking location, obtaining corresponding scan correction coefficients based on the historical smoke and dust reference values, and correcting the oscillation speed based on the scan correction coefficients include: Tracing back the historical preset detection count of smoke and dust at the current parking location; and The average dust concentration is calculated based on the dust data to obtain the historical dust reference value.

5. The method for monitoring and treating tunnel dust according to claim 1, characterized in that, After controlling the monitoring vehicle to stop at each of the detection points, the method further includes: The corresponding delay duration is obtained based on the speed of the monitoring vehicle; the higher the speed, the longer the corresponding delay duration. The control of the dust sensor to detect the dust concentration at the current location includes: After the monitoring vehicle stops for the specified delay period, the dust sensor is controlled to detect the dust concentration at the current location.

6. The method for monitoring and treating tunnel dust according to claim 1, characterized in that, Also includes: Obtain dust removal instructions from the host server; The detection location and dust removal intensity of the corresponding detection point are obtained according to the dust removal command; Control the monitoring vehicle to move to the detection location; The swing arm is controlled to perform reciprocating oscillations at an oscillation speed and oscillation time corresponding to the dust removal intensity; as well as The monitoring trolley is controlled to perform dust removal work at the working power and working time corresponding to the dust removal intensity.

7. The method for monitoring and treating tunnel dust according to claim 6, characterized in that, Also includes: If the monitoring vehicle completes the dust removal command, then control the monitoring vehicle to return to the position of the detection point before the dust removal command was issued.

8. A tunnel dust monitoring and treatment system, characterized in that, Applied to building tunnels, the building tunnel is equipped with a monitoring track and a monitoring trolley. Multiple detection points are set up in the building tunnel along the tunnel extension direction. The monitoring track is arranged along the tunnel extension direction of the building tunnel. The monitoring trolley is slidably connected to the monitoring track. The monitoring trolley is equipped with a dust sensor and a swing arm. The swing arm is equipped with a dust removal device. The tunnel dust monitoring and treatment system includes: The monitoring and control module is configured to: control the monitoring trolley to run at a constant speed along the monitoring track in a first direction; control the monitoring trolley to stop at each of the detection points; control the dust sensor to detect the dust concentration at the current location; if the dust concentration is greater than or equal to a preset concentration, match the corresponding swing speed according to the dust concentration; control the swing arm to swing at the currently corresponding swing speed, and perform dust removal through the dust removal device. The swing speed compensation module is communicatively connected to the monitoring and control module. The swing speed compensation module is configured to: obtain historical smoke and dust reference values ​​at the current parking position, obtain corresponding scanning correction coefficients based on the historical smoke and dust reference values, and correct the swing speed based on the scanning correction coefficients. The re-inspection module, communicatively connected to the monitoring and control module, is configured to: if the dust concentration is lower than the preset concentration, control the swing arm and the dust removal device to stop; control the monitoring trolley to stop and wait for a first preset time, and control the dust sensor to detect the average value of the second detection within the first preset time; if the average value of the second detection is lower than the preset concentration, control the monitoring trolley to move to the next detection point; if the average value of the second detection is greater than or equal to the preset concentration, generate a first warning message and control the swing arm to swing and control the dust removal device to perform dust removal; summarize all dust concentrations and the average value of the second detection corresponding to the current detection, and compare them with all dust concentrations and the average value of the second detection corresponding to other detections. The average of the secondary detections is compared one by one with the corresponding detection points to obtain a first change value of the smoke and dust concentration for each detection point, and a second change value of the average of the secondary detections for each detection point. If the first change value exceeds a first preset change range, a first abnormality information is generated for the corresponding detection point. If the second change value exceeds a second preset change range, a second abnormality information is generated for the corresponding detection point. If the second abnormality information is obtained, the monitoring vehicle is controlled to move to the position of the corresponding detection point. The smoke and dust sensing device is controlled to continuously detect the smoke and dust fluctuation value for a second preset time period. If the smoke and dust fluctuation value is greater than a preset fluctuation range, a second warning information is generated. as well as The decision module is communicatively connected to the monitoring and control module and the re-inspection module respectively. The decision module is configured to: if the monitoring vehicle completes all the detection points, then the current detection is completed and detection completion information is generated.

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