A portable real-time monitoring and alarming device for vertical displacement of the roof of tunnel karst caves

Abstract

The present invention relates to a portable real-time monitoring and alarm device for the vertical displacement of the roof of a tunnel karst cave, belonging to the technical field of tunnel engineering. The device includes a laser emission end, a laser reception end, a laser reflector, a data processing system, a portable computer and an alarm warning light; the laser emission end and the laser reception end are connected to the data processing system, and the data processing system is connected to the portable computer, wherein the laser emission end and the laser reception end are used to measure the change value of the vertical displacement of the laser reflector. The data processing system judges whether the measured change value of the vertical displacement exceeds the safety threshold. If it exceeds, the alarm warning light changes color, and at the same time, the portable computer gives an alarm. The present invention has high accuracy of monitoring data and has a prediction and early warning function. The device is simple to install, easy to carry and easy to operate; the monitoring process does not rely on manpower and does not affect the on-site construction.

Description

Technical Field

[0001] The present invention belongs to the technical field of tunnel engineering and relates to a real-time monitoring and alarming device for the vertical displacement of the roof structure of a tunnel karst cave. Background Art

[0002] With the development of the tunnel construction industry, ensuring the safety of tunnel construction is of utmost importance. However, there are many geological problems encountered in tunnel construction, and it is often necessary to monitor special structures to ensure the safety during tunnel construction. Displacement monitoring devices have thus been widely used. Currently, during construction, the method of measuring displacement still uses total stations and levels for manual measurement. This method has the problems of wasting manpower and material resources, lacking real-time performance, having a relatively high probability of human error, and being affected by construction environmental conditions (such as dust, smoke, etc.); traditional rod-type roof subsidence detectors, that is, the rod-type roof subsidence detectors are supported between the top and bottom plates of the free area. When the roof undergoes subsidence deformation, the displacement sensor located on the rod is used to detect its deformation amount. Due to the problem of buckling stability of the rod, if it is applied to the free area of a large-section tunnel, to overcome the problem of buckling instability of the rod, it is necessary to increase the cross-section or stiffness of the rod, thereby increasing the cost and installation difficulty, and especially it may interfere with the operation of construction vehicles or other construction equipment in the construction area.

[0003] Therefore, in order to monitor the displacement deformation of the tunnel karst cave roof under blasting vibration safely, at low cost and with high precision, there is an urgent need for a new real-time monitoring and alarming system for the vertical displacement of the tunnel karst cave roof. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a portable real-time monitoring and alarming device for the vertical displacement of the tunnel karst cave roof, which solves the real-time monitoring and alarming of the vertical displacement of the tunnel karst cave roof under blasting vibration conditions and can predict and alarm the change trend of the displacement of the karst cave roof.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] A portable real-time monitoring and alarming device for the vertical displacement of the tunnel karst cave roof, comprising: a laser emission end (1), a laser reception end (3), a laser reflector (4), a data processing system (6), a portable computer (7) and an alarm warning light (5);

[0007] The laser emission end (1) and the laser reception end (3) are respectively connected to the output port and the input port of the data processing system (6); the data processing system (6) and the alarm warning light (5) are connected to the portable computer (7);

[0008] The laser emission end (1) and the laser reception end (3) are used to measure the vertical displacement change value of the laser reflector (4); the data processing system (6) determines whether it exceeds the safety threshold set by the system according to the measured vertical displacement change value. When it exceeds the safety threshold, the alarm warning light (5) changes color, and at the same time, the portable computer (7) emits an alarm ringtone.

[0009] Furthermore, the system further includes laser device racks (2) arranged on both sides of the tunnel. The laser emission end (1) is installed on one side, and the laser reception end (3) is installed on the other side. Multiple laser emission devices and laser reception devices are correspondingly installed on the laser device racks (2) in sequence.

[0010] Furthermore, the bottom of the laser device rack (2) is fixed on a rectangular base (14); an adjustment knob (15) is provided at each of the four corners of the rectangular base (14).

[0011] Furthermore, a level (13) is also installed on the laser device rack (2), and the level (13) is made to reach a horizontal stable state through the adjustment knobs (15) on the rectangular base (14).

[0012] Furthermore, the position of the level (13) on the laser device rack (2) is lower than the fixed positions of the laser emission end (1) or the laser reception end (3).

[0013] Furthermore, a coarse adjustment screw knob (11) and a fine adjustment screw knob (12) are also provided on the laser device rack (2). The working angles of the laser emission end (1), the laser reflector (4), and the laser reception end (3) are adjusted through the coarse / fine screw knobs, and the three need to be calibrated before measurement.

[0014] Furthermore, the laser reflector (4) is evenly embedded and fixed at the position with relatively weak thickness of the roof (8) of the tunnel karst cave; the alarm warning light (5) is fixed beside the monitoring point on the roof (8) of the tunnel karst cave.

[0015] Furthermore, the alarm warning light (5) is connected to the portable computer (7) via wireless Bluetooth.

[0016] Furthermore, the data processing system (6) is integrated inside the computer.

[0017] Furthermore, the data processing system (6) uses a Flash unit for data analysis, including safety threshold comparison and neural network method for predicting the deformation trend of the karst cave roof.

[0018] Furthermore, the specific steps for predicting the deformation trend of the karst cave roof using the neural network method are as follows:

[0019] 1) Normalize the monitored displacements of multiple points to form a normalized set;

[0020] 2) Set the weight parameters and thresholds of the neural network through the neural network prediction model;

[0021] 3) Divide the normalized data into training data and test data, and import the training data into the set neural network prediction model for training through forward propagation and backward propagation;

[0022] 4) Calculate the training error of the training result and determine whether it meets the set judgment conditions; if the conditions are met, the algorithm ends and this model is used as the optimal prediction model; if not, continuously correct the weight coefficients and thresholds and return for retraining;

[0023] 5) Import the test data into the optimal prediction model for prediction.

[0024] The beneficial effects of the present invention are as follows:

[0025] (1) The present invention adopts a laser dynamic monitoring device, which has the advantages of high monitoring accuracy, simple operation, and easy portability;

[0026] (2) The present invention fully considers the construction site environment, optimizes the equipment layout, and will not affect the tunnel construction operation;

[0027] (3) The present invention adopts an automatic monitoring device, which does not rely on manpower and can greatly reduce the input of manpower and time.

[0028] (4) The data processing system of the device of the present invention introduces neural network prediction, which can monitor and alarm the vertical change of the tunnel karst cave roof in real time and predict the future change trend.

[0029] Other advantages, objectives, and features of the present invention will be described to some extent in the subsequent specification, and to some extent, will be obvious to those skilled in the art based on the study of the following text, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the following specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be described in detail preferably with reference to the accompanying drawings, where:

[0031] Figure 1 is the overall installation schematic diagram of the present invention;

[0032] Figure 2 is the schematic diagram of the laser device frame of the present invention;

[0033] Figure 3Schematic diagram of the internal structure connection of the data processing system of the present invention;

[0034] Reference numerals: 1 - Laser emission end, 2 - Laser device frame, 3 - Laser reception end, 4 - Laser reflector, 5 - Alarm warning light, 6 - Data processing system, 7 - Portable computer, 8 - Tunnel karst cave roof, 9 - Tunnel, 10 - Karst cave, 11 - Coarse adjustment screw knob, 12 - Fine adjustment screw knob, 13 - Level, 14 - Rectangular base, 15 - Base adjustment knob. Specific implementation manners

[0035] The following uses specific specific examples to illustrate the implementation manners of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation manners. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the drawings provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0036] Among them, the drawings are only for illustrative purposes, showing only schematic diagrams, not physical diagrams, and should not be construed as limiting the present invention; in order to better illustrate the embodiments of the present invention, some components in the drawings will be omitted, enlarged or reduced, and do not represent the dimensions of actual products; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0037] In the drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components; in the description of the present invention, it should be understood that if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc. indicating the orientation or positional relationship, they are based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, the terms describing the positional relationship in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0038] Please refer to Figures 1 to 3 , in the advanced geological prediction, measure the distribution range of the karst cave and the distribution of the thickness of the karst cave roof, and arrange the number and positions of monitoring points according to its distribution characteristics. In this example, 3 monitoring points are arranged.

[0039] Such as Figure 1As shown in the figure, the laser reflector 4 is evenly embedded and fixed at the position with relatively thin thickness of the roof 8 of the tunnel karst cave, and is fixed with glue. The laser reflector 4 is provided with threaded nails, aiming to fix the laser reflector 4 and the roof 8 of the tunnel karst cave into a whole, so as to facilitate the measurement of the deflection change of the roof 8 of the tunnel karst cave. The alarm warning lights 5 are fixedly arranged beside the monitoring points in sequence. The alarm warning lights 5 are connected to the portable computer 7 by wireless Bluetooth. If the alarm warning lights 5 show green within the safety threshold and show red beyond the safety threshold, at the same time, the portable computer 7 emits an alarm bell.

[0040] As Figure 2 shown in the figure, the laser device racks 2 are distributed at the side walls of the tunnel. One side is the laser reflection end 1 and the other side is the laser receiving end 3. The laser emission end 1 and the laser receiving end 3 are installed on the laser device racks 2 in sequence. A level 13 is installed on the laser device rack. The level 13 is made to reach a horizontal stable state through the base adjustment knob 15 on the rectangular base 14. The rectangular base 14 is made of high-density steel, and a base adjustment knob 15 is arranged at each of the four corners; there are a coarse adjustment screw knob 11 and a fine adjustment screw knob 12 on the laser device rack 2. The working angles of the laser emission end 1, the laser reflection sheet 4, and the laser receiving end 3 are adjusted through the coarse and fine screw knobs, and the three need to be calibrated before measurement.

[0041] The laser emission end 1 and the laser receiving end 3 are respectively connected to the output port and the input port of the data processing system 6. The data processing system 6 is connected to the portable computer 7, and the collected data is processed and then transmitted to the portable computer 7.

[0042] As Figure 3 shown in the figure, the data processing system 6 is composed of a data acquisition unit, a storage unit, a data analysis unit, and an image generation unit connected in sequence; the data acquisition unit (for example: laser displacement sensor) is connected to the laser emission end 1 and the laser receiving end 3 to obtain the vertical displacement change value of the measured laser reflector 4; the storage unit (for example: large-capacity SSD hard disk) stores the acquisition data obtained by the acquisition unit; the data analysis unit uses a Flash chip to complete data analysis and prediction; the image generation unit (for example: image generator) generates a data change image from the analyzed data and transmits it to the portable computer to display the deformation condition of the roof of the tunnel karst cave in the form of a dynamic curve, so as to predict the displacement change trend of the tunnel karst cave.

[0043] Data analysis is carried out using a Flash chip, including comparing the safety threshold and predicting the deformation trend of the roof of the karst cave by the neural network method. Among them, the specific steps for predicting the deformation trend of the roof of the karst cave by the neural network method are as follows:

[0044] 1) Normalize the monitored displacements of multiple points to form a normalized set;

[0045] 2) Set the weight parameters and thresholds of the neural network through the neural network prediction model;

[0046] 3) Divide the normalized data into training data and test data, and import the training data into the set neural network prediction model for training through forward propagation and backward propagation;

[0047] 4) Calculate the training error of the training result and determine whether it meets the set judgment conditions; if it meets the conditions, the algorithm ends and this model is used as the optimal prediction model; if it does not meet the conditions, continuously correct the weight coefficients and thresholds and return for retraining;

[0048] 5) Import the test data into the optimal prediction model for prediction.

[0049] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the purpose and scope of the present technical solution, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A portable real-time monitoring and alarm device for vertical displacement of tunnel karst cave roof, characterized in that, The device includes: a laser emission end (1), a laser reception end (3), a laser reflector (4), a data processing system (6), a portable computer (7), and an alarm warning light (5); The laser emission end (1) and the laser reception end (3) are respectively connected to the output port and the input port of the data processing system (6); the data processing system (6) and the alarm warning light (5) are connected to the portable computer (7); The laser emission end (1) and the laser reception end (3) are used to measure the vertical displacement change value of the laser reflector (4); the data processing system (6) determines whether it exceeds the safety threshold set by the system according to the measured vertical displacement change value. When it exceeds the safety threshold, the alarm warning light (5) changes color, and at the same time, the portable computer (7) emits an alarm ringtone; The data processing system (6) uses a Flash unit for data analysis, including safety threshold comparison and neural network method to predict the deformation trend of the karst cave roof.

2. The real-time monitoring and alarm device for vertical displacement of the roof of a portable tunnel karst cave, according to claim 1, characterized in that, The system further includes laser device frames (2) arranged on both sides of the tunnel. The laser emission end (1) is installed on one side, and the laser reception end (3) is installed on the other side. Multiple laser emission devices and laser reception devices are sequentially installed on the laser device frames (2) correspondingly.

3. The portable real-time monitoring and alarm device for vertical displacement of tunnel karst cave roof according to claim 2, wherein, The bottom of the laser device frame (2) is fixed on a rectangular base (14); an adjustment knob (15) is provided at each of the four corners of the rectangular base (14).

4. The real-time monitoring and alarm device for vertical displacement of the roof of a portable tunnel karst cave according to claim 3, characterized in that A level (13) is also installed on the laser device frame (2), and the level (13) is made to reach a horizontal stable state through the adjustment knob (15) on the rectangular base (14).

5. The portable real-time monitoring and alarming device for vertical displacement of tunnel karst cave roof according to claim 4, characterized in that The position of the level (13) on the laser device frame (2) is lower than the fixed positions of the laser emission end (1) or the laser reception end (3).

6. The real-time monitoring and alarm device for vertical displacement of the roof of a portable tunnel karst cave according to claim 1, characterized in that, A coarse adjustment screw knob (11) and a fine adjustment screw knob (12) are also provided on the laser device frame (2), and the working angles of the laser emission end (1), the laser reflector (4), and the laser reception end (3) are adjusted through the coarse / fine screw knobs.

7. The portable real-time monitoring and alarming device for vertical displacement of tunnel karst cave roof according to claim 1, characterized in that, The laser reflector (4) is evenly embedded and fixed at the position where the thickness of the karst cave roof (8) of the tunnel is relatively weak; the alarm warning light (5) is fixed beside the monitoring point of the karst cave roof (8) of the tunnel.

8. The real-time monitoring and alarm device for vertical displacement of the roof of a portable tunnel karst cave according to claim 1, characterized in that, The alarm warning light (5) is connected to the portable computer (7) by wireless Bluetooth.

9. The real-time monitoring and alarm device for vertical displacement of the roof of a portable tunnel karst cave according to claim 1, characterized in that, The specific steps for predicting the deformation trend of the karst cave roof by the neural network method are as follows: 1) Normalize the monitored displacements of multiple points to form a normalized set; 2) Set the weight parameters and thresholds of the neural network through the neural network prediction model; 3) Divide the normalized data into training data and test data, and import the training data into the set neural network prediction model for training through forward propagation and backward propagation; 4) Calculate the training error of the training result and determine whether it meets the set judgment conditions; if it meets the conditions, the algorithm ends, and this model is used as the optimal prediction model; if it does not meet the conditions, continuously correct the weight coefficient and threshold, and return for retraining; 5) Import the test data into the optimal prediction model for prediction.

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