Remote fracture development monitoring system and method for high-risk sliding slope

Abstract

The invention relates to a remote fracture development monitoring system and method for a high-risk sliding slope, the system comprises a data acquisition module, a data receiving and processing module and a power supply module, the data acquisition module comprises a digital camera, a temperature sensor, a humidity sensor and a digital rain gauge; the data acquisition module is electrically connected with the data receiving and processing module, the computer processor analyzes and records image data, and results output by the computer processor comprise time, temperature, humidity, rainfall intensity, crack length, crack width, crack cracking area and crack cracking rate. The invention provides a remote fracture development monitoring system and method suitable for slope data measurement in high-risk sliding, and the system and method can monitor the width, length, cracking area and rate of a key crack of a cracked landslide, and the temperature, humidity and rainfall intensity near the slope in real time. Data information can be provided for scientific research, early warning can be provided for deformation and damage of the side slope, and the application range is wide.

Description

Technical Field

[0001] The technical field to which the present invention relates mainly targets various types of dangerous rock slopes that are already in the sliding stage, and develops a new remote crack development monitoring system and method, so as to obtain key data at the disaster site in real time while ensuring the safety of personnel and equipment, and conduct scientific research analysis and landslide warning. Technical Background

[0002] The stability and safety of slopes have always been a major issue in the construction of highways, bridges, reservoirs, dams and other projects. The consequences of slope instability and damage are immeasurable. A large number of scholars at home and abroad have studied the mechanism of slope instability and damage. Among the three stages of slope sliding, the accelerated sliding stage is considered to be the most destructive and difficult to study. The main reason is that the accelerated sliding stage of the slope is short, fast, highly dangerous and destructive. In the monitoring of natural slopes, it is very difficult to obtain data such as crack opening displacement and rate during the accelerated sliding stage.

[0003] There is a great danger after the slope continues to crack, and it is almost impossible to measure the displacement at a short distance. At present, the displacement measurement of the sliding slope is usually monitored by pre-buried strain gauges. However, pre-buried strain gauges and other instruments have the following defects: ① can only collect data at specific points; ② it is very easy to be damaged during the deformation and destruction of the slope, and no remediation can be carried out after the damage; ③ once its location and environment change, the collected data is very easy to be distorted. Considering that the deformation and destruction of the slope in the acceleration stage are usually inseparable from rainfall, based on the sensitivity of slope deformation and destruction to rainfall intensity and duration, regional rainfall is difficult to accurately represent the real-time rainfall intensity and duration of the slope at a specific location, and the slope will release a large amount of energy at the moment of destruction, resulting in short-term changes in temperature and humidity in the local environment. The present invention designs a sliding slope remote crack development monitor with both rainfall and temperature and humidity monitoring functions to safely and effectively collect key data at the disaster site. Summary of the invention

[0004] The technical problem to be solved by the present invention is to design a remote crack development monitoring system and method suitable for high-risk sliding slopes, to safely and effectively perform large-scale continuous dynamic monitoring of high-risk sliding slopes, and to collect key data at the disaster site with high quality.

[0005] According to a first aspect of the present invention, a remote crack development monitoring system for high-risk sliding slopes is provided, comprising a data acquisition module, a data receiving and processing module and a power supply module, wherein the data acquisition module comprises a digital camera, a temperature sensor, a humidity sensor and a digital rain gauge; the data receiving and processing module comprises a display, a data receiver, a computer processor and a data storage device; the power supply module comprises a battery, a charging controller and a solar panel, the power supply module is used to supply power to the data acquisition module and the data receiving and processing module, the data acquisition module and the data receiving and processing module are electrically connected, the computer processor is used to record image data after analysis, and directly record temperature data, humidity data and rainfall data, the results output by the computer processor include time, temperature, humidity, rainfall intensity, crack length, crack width, crack opening area and crack opening rate.

[0006] Preferably, the temperature sensor is an infrared temperature sensor.

[0007] Preferably, the humidity sensor is a resistive humidity sensor.

[0008] Preferably, the digital rain gauge is a tipping bucket type digital rain gauge.

[0009] Preferably, data scales are provided around the display screen.

[0010] Preferably, the data receiving instrument includes an image data receiver, a temperature data receiver, a humidity data receiver and a rainfall data receiver, and the image data receiver, the temperature data receiver, the humidity data receiver and the rainfall data receiver are respectively connected to the digital camera, the temperature sensor, the humidity sensor and the digital rain gauge.

[0011] The second aspect of the present invention provides a remote global data acquisition method for high-risk sliding slopes, which is performed using any of the above-mentioned remote global data acquisition systems for high-risk sliding slopes, and is characterized in that it specifically comprises the following steps:

[0012] S1 processes the collected image data;

[0013] S2 collects crack data on the processed image and calculates the crack area, crack opening rate, crack length and average crack width;

[0014] S3 stores the image data processed by S1 and the crack data calculated by S2.

[0015] Preferably, S1 processes the image in the following manner:

[0016] S11 reads the image data and corrects and adjusts the image according to the equal elevation points and equal distance points pre-measured and marked near the landslide to eliminate the influence of the angle between the camera and the slope on the crack calculation;

[0017] S12 converts the color image into a grayscale image;

[0018] S13 converts the grayscale image into a binary image, identifies independent units in the image and numbers them;

[0019] S14 selects a fracture unit in the independent unit, and continuously monitors, calculates and saves the data of the selected unit.

[0020] Preferably, S2 calculates the cracks in the following manner:

[0021] S21 establishes a plane rectangular coordinate system with the lower left corner of the image as the origin, reads that the number of pixels in the x-axis direction of the image is M, the number of pixels in the y-axis direction is N, the actual measured length of the image interval corresponding to M is m meters, and the actual measured length of the image interval corresponding to N is n meters, and inputs m and n into the computer;

[0022] S22 counts the number of crack pixels in the x direction, L, through the formula Calculate the crack length l, where: M is the number of pixels in the x-axis direction of the corrected image, and m is the measured length in the x-axis direction of the corrected image;

[0023] S23 counts the number of pixels at different locations of the crack in the y direction H i , through the formula Calculate the width h of the crack at different locations i According to the number of pixels in the crack length direction, the value range of i is [1, L], and the crack width is the average width Where: h i is the calculated width of the crack in the y direction when the length is i, n is the measured length in the y-axis direction of the corrected image, and N is the number of pixels in the y-axis direction of the corrected image;

[0024] S24 by formula Calculate the crack opening area, where: S is the crack opening area;

[0025] S25 by formula Calculate the crack opening rate, where t k+1 -t k is the time interval between the k+1th crack measurement and the kth crack measurement, where: Calculate the average width of the crack in the y direction;

[0026] S26 Comparison With l size, when When , the length and width of the crack are recalculated, and the number of pixels in the y direction of the crack is counted H, and the formula Calculate the crack length h;

[0027] S27 counts the number of pixels L at different positions in the crack in the x direction i , through the formula Calculate the width l of the crack at different positions i According to the number of pixels in the crack length direction, the value range of i is [1, H], and the crack width is the average width Where: H i is the number of pixels in the crack y direction at length i.

[0028] Compared with the prior art, the present invention has the following advantages:

[0029] 1. The present invention provides a remote crack development monitoring system and method for high-risk sliding slopes, which can monitor the width, length, cracking area and rate of key cracks in cracked landslides in real time, as well as the temperature, humidity and rainfall intensity near the slope. It can provide data for scientific research and provide early warning for deformation and damage of slopes, and has wide application.

[0030] 2. The present invention provides a remote crack development monitoring system for high-risk sliding slopes, which can monitor the dynamic development process of key cracks in the landslide body on a large scale, in all directions and continuously outside the sliding slope body, and can collect key data at the disaster site while ensuring the safety of personnel and equipment.

[0031] 3. The remote crack development monitoring system for high-risk sliding slopes of the present invention adopts solar panels for continuous power supply and is suitable for long-term field use.

[0032] 4. The present invention provides a remote crack development monitoring system for high-risk sliding slopes, which integrates data collection and analysis, is simple to operate, and is easy to use. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The present invention will be further described below with reference to the accompanying drawings and implementation examples:

[0034] Figure 1 4 is a system structure block diagram of an embodiment of the present invention.

[0035] Figure 2 This is a color image of the landslide monitored by the embodiment of the present invention.

[0036] Figure 3 This is a corrected image of the landslide monitored in an embodiment of the present invention.

[0037] Figure 4 This is a grayscale image of the landslide monitored by the embodiment of the present invention.

[0038] Figure 5 This is a binary image of the landslide monitored in the embodiment of the present invention.

[0039] Figure 6 This is the image of the landslide fissure unit monitored by the embodiment of the present invention.

[0040] Figure 7 This is a schematic diagram of the calculation of landslide fissures monitored in an embodiment of the present invention.

[0041] Figure 8 Schematic diagram of the display screen scale according to an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The present invention is described in detail below in conjunction with specific implementation modes.

[0043] In the description of the present invention, the symbols in the formula are explained as follows:

[0044] M: the number of pixels in the x-axis direction of the corrected image; N: the number of pixels in the y-axis direction of the corrected image; m: the measured length in the x-axis direction of the corrected image; n: the measured length in the y-axis direction of the corrected image; L i : The number of pixels in the crack x direction at height i; l i : The calculated width of the crack in the x direction when the height is i; The average width of the crack in the x direction; H i : The number of pixels in the crack y direction at length i; h i : The calculated width of the crack in the y direction when the length is i; The average value of the crack width calculated in the y direction; S: crack opening area; v: crack opening velocity t k : The time of the kth record.

[0045] like Figure 1As shown, a remote crack development monitoring system for high-risk sliding slopes includes a data acquisition module, a data receiving and processing module and a power supply module, characterized in that: the data acquisition module includes a digital camera, a temperature sensor, a humidity sensor and a digital rain gauge; the data receiving and processing module includes a display, a data receiver, a computer processor and a data storage device; the power supply module includes a battery, a charging controller and a solar panel, the power supply module is used to supply power to the data acquisition module and the data receiving and processing module, the data acquisition module and the data receiving and processing module are electrically connected, the computer processor is used to record the image data after analysis, and directly record the temperature data, humidity data and rainfall data, the results output by the computer processor include time, temperature, humidity, rainfall intensity, crack length, crack width, crack cracking area, and crack cracking rate; the data acquisition module collects data and transmits the collected data to the data receiving and processing module, the data receiving and processing module processes the data after receiving the data, and outputs and saves the data after the processing is completed, and the power supply module continuously provides power for the entire set of instruments in the field.

[0046] In the above embodiment, the display is connected to the computer processor, and the display screen is provided with a data ruler around it, through which the crack area is located. When the image collector is offset due to external influences, such as Figure 8 As shown, by scaling the image or adjusting the direction and position of the image collector so that the feature points of the image displayed on the display screen are located on a fixed scale, the image size and position settings can be made consistent with the original settings. The aspect ratio of the displayed image can be set according to the range of the monitored slope, ranging from 1:1 to 18:9; the image DPI can be adjusted according to the distance of the monitored slope, ranging from 120 to 1200; the image acquisition frequency is in seconds, minutes, and hours, ranging from 5 images / second to 1 image / 48 hours; during the data acquisition process, the above settings can be dynamically adjusted according to the development status of the monitored object.

[0047] In a specific embodiment, the temperature sensor is an infrared temperature sensor.

[0048] In a specific embodiment, the humidity sensor is a resistive humidity sensor.

[0049] In a specific embodiment, the digital rain gauge is a tipping bucket type digital rain gauge.

[0050] In a specific embodiment, data scales are provided around the display screen.

[0051] In a specific embodiment, the data receiving instrument includes an image data receiver, a temperature data receiver, a humidity data receiver and a rainfall data receiver, and the image data receiver, the temperature data receiver, the humidity data receiver and the rainfall data receiver are respectively connected to a digital camera, a temperature sensor, a humidity sensor and a digital rain gauge.

[0052] The method of the present invention is introduced below with a practical application case. First, image acquisition is performed. The above-mentioned image is selected in each direction outside the landslide surface. Figure 2 The equal elevation and equal distance points A, B, C, D are shown, and their actual elevations and distances are recorded.

[0053] A remote crack development monitor for high-risk sliding slopes is placed near the landslide where the slope cracks can be clearly observed. After the instrument is installed, the camera position is adjusted so that the selected equal-elevation points and equal-distance points can be completely included in the monitoring image.

[0054] The image is then preprocessed, mainly including setting the image aspect ratio, acquisition frequency, temperature, humidity, rainfall recording frequency, etc.

[0055] After adjusting the image position, pick up the coordinates of points A, B, C, and D in the image by moving the cursor. The coordinates are automatically entered into the computer processor, and all the images collected in the same project will be corrected according to the coordinates.

[0056] The actual distance between AB and AD is input into the computer processor, and the computer automatically corrects and calculates the image. After the calculation is completed, the output result and the collected original image are compressed and saved.

[0057] After the above work in the evening, the remote global data collection for high-risk sliding slopes can be carried out, which mainly includes the following steps:

[0058] S1 processes the collected image data;

[0059] S2 collects crack data on the processed image and calculates the crack area, crack opening rate, crack length and average crack width;

[0060] S3 stores the image data processed by S1 and the crack data calculated by S2.

[0061] The computer processor is connected to the data receiver and transmits the data received by the data receiver to the computer for analysis and recording. The image data is recorded after analysis, and the temperature data, humidity data and rainfall data are recorded directly. The specific steps of image data processing are:

[0062] S11 reads image data (see Figure 2), and based on the pre-measured and marked iso-elevation points near the landslide ( Figure 2 A and B are equal elevation points, C and D are equal elevation points), and equal distance points (field measurement distance AB = CD) are used to calibrate and adjust the image to eliminate the influence of the angle between the camera and the slope on the crack calculation. The calibrated and adjusted image is shown in Figure 3 ;

[0063] S12 converts the color image to a grayscale image. Figure 4 ;

[0064] S12 converts the grayscale image into a binary image, identifies the independent units in the image and numbers them. Figure 5 ;

[0065] S14 selects the fracture unit in the independent unit, and continuously monitors, calculates and saves the data of the selected unit. Figure 6 .

[0066] After image acquisition and processing, the cracks can be processed and calculated. The calculation of the crack unit is based on Figure 6 Take the No. 90 crack as an example. The specific steps are:

[0067] S21 Figure 6 The lower left corner is the origin to establish a plane rectangular coordinate system, read Figure 6 The number of pixels in the x-axis direction is M, and the number of pixels in the y-axis direction is N (see Figure 7 ), the actual measured length of the image interval corresponding to M (i.e. the measured distance between the AB and CD segments) is m meters, and the actual measured length of the image interval corresponding to N (i.e. the measured distance between the AD and BC segments) is n meters. Input m and n into the computer;

[0068] S22 counts the number of pixels L in the x direction of crack No. 90, using the formula Calculate the length l of crack No. 90;

[0069] S23 counts the number of pixels in the y direction at different positions of crack No. 90 H i , through the formula Calculate the width h of crack No. 90 at different positions i According to the number of pixels in the crack length direction counted in ②, the value range of i is [1, L], and the width of crack No. 90 is taken as its average width

[0070] S24 by formula Calculate the crack opening area S;

[0071] S25 by formula Calculate the crack opening rate v, where t k+1 -t kis the time interval between the k+1th crack measurement and the kth crack measurement;

[0072] S26 Comparison With l size, when When , the length and width of the crack are recalculated, and the number of pixels in the y direction of the crack is counted H, and the formula Calculate the crack length h;

[0073] S27 counts the number of pixels L at different positions in the crack in the x direction i , through the formula Calculate the width l of the crack at different positions i According to the number of pixels in the crack length direction counted in ⑥, the value range of i is [1,H], and the crack width is taken as its average width The results output by the computer processor include time, temperature, humidity, rainfall intensity, crack length, crack width, crack opening area, and crack opening rate. The final output results are automatically saved in the data storage.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A remote global data acquisition system for high-risk sliding slopes, comprising a data acquisition module, a data receiving and processing module, and a power supply module, characterized in that: The data acquisition module includes a digital camera, a temperature sensor, a humidity sensor and a digital rain gauge; the data receiving and processing module includes a display, a data receiver, a computer processor and a data storage device; the power supply module includes a battery, a charging controller and a solar panel, the power supply module is used to supply power to the data acquisition module and the data receiving and processing module, the data acquisition module and the data receiving and processing module are electrically connected, the computer processor is used to record the image data after analysis, and directly record the temperature data, humidity data and rainfall data, and the results output by the computer processor include time, temperature, humidity, rainfall intensity, crack length, crack width, crack cracking area, and crack cracking rate.

2. A remote global data acquisition system for high-risk sliding slopes according to claim 1, characterized in that: The temperature sensor is an infrared temperature sensor.

3. The remote global data acquisition system for high-risk sliding slopes according to claim 1 is characterized in that: The humidity sensor is a resistive humidity sensor.

4. The remote global data acquisition system for high-risk sliding slopes according to claim 1 is characterized in that: The digital rain gauge adopts a tipping bucket type digital rain gauge.

5. The remote global data acquisition system for high-risk sliding slopes according to claim 1 is characterized in that: Data scales are arranged around the display screen.

6. The remote global data acquisition system for high-risk sliding slopes according to claim 1 is characterized in that: The data receiving instrument comprises an image data receiver, a temperature data receiver, a humidity data receiver and a rainfall data receiver, and the image data receiver, the temperature data receiver, the humidity data receiver and the rainfall data receiver are respectively connected to the digital camera, the temperature sensor, the humidity sensor and the digital rain gauge.

7. A remote global data acquisition method for high-risk sliding slopes, using a remote global data acquisition system for high-risk sliding slopes as claimed in any one of claims 1 to 6, characterized in that: The specific steps include: S1 processes the collected image data; S2 collects crack data on the processed image and calculates the crack area, crack opening rate, crack length and average crack width; S3 stores the image data processed by S1 and the crack data calculated by S2.

8. The remote global data acquisition method for high-risk sliding slopes according to claim 7 is characterized in that: S1 processes the image in the following way: S11 reads the image data and corrects and adjusts the image according to the equal elevation points and equal distance points pre-measured and marked near the landslide to eliminate the influence of the angle between the camera and the slope on the crack calculation; S12 converts the color image into a grayscale image; S13 converts the grayscale image into a binary image, identifies independent units in the image and numbers them; S14 selects a fracture unit in the independent unit, and continuously monitors, calculates and saves the data of the selected unit.

9. The remote global data acquisition method for high-risk sliding slopes according to claim 7 is characterized in that: S2 calculates the cracks as follows: S21 establishes a plane rectangular coordinate system with the lower left corner of the image as the origin, reads that the number of pixels in the x-axis direction of the image is M, the number of pixels in the y-axis direction is N, the actual measured length of the image interval corresponding to M is m meters, and the actual measured length of the image interval corresponding to N is n meters, and inputs m and n into the computer; S22 counts the number of crack pixels in the x direction, L, through the formula Calculate the crack length l, where: M is the number of pixels in the x-axis direction of the corrected image, and m is the measured length in the x-axis direction of the corrected image; S23 counts the number of pixels at different locations of the crack in the y direction H i , through the formula Calculate the width h of the crack at different locations i According to the number of pixels in the crack length direction, the value range of i is [1, L], and the crack width is the average width Where: h i is the calculated width of the crack in the y direction when the length is i, n is the measured length in the y direction of the corrected image, and N is the number of pixels in the y direction of the corrected image; S24 by formula Calculate the crack opening area, where: S is the crack opening area; S25 by formula Calculate the crack opening rate, where t k+1 -t k is the time interval between the k+1th crack measurement and the kth crack measurement, where: Calculate the average width of the crack in the y direction; S26 Comparison With l size, when When , the length and width of the crack are recalculated, and the number of pixels in the y direction of the crack is counted H, and the formula Calculate the crack length h; S27 counts the number of pixels L at different positions in the x direction of the crack i , through the formula Calculate the width l of the crack at different positions i According to the number of pixels in the crack length direction, the value range of i is [1, H], and the crack width is the average width Where: H i is the number of pixels in the crack y direction at length i.

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