Hydro-fluctuation belt dangerous rock underwater hidden danger identification and monitoring method based on multi-beam sonar

Abstract

The invention discloses a hydro-fluctuation belt dangerous rock underwater hidden danger identification and monitoring method based on multi-beam sonar, and belongs to the technical field of reservoir area dangerous rock ground disaster prevention and control. Installing a multi-beam measurement system; obtaining underwater data of the reservoir area; processing the underwater data of the reservoir area; fusing the overwater and underwater terrains; establishing an underwater hidden danger mark; extracting underwater hidden danger information; and monitoring underwater hidden danger deformation. According to the method, the range of underwater hidden dangers can be precisely delimited, the position information and scale data of the underwater hidden dangers can be obtained, the deformation information of the underwater part rock mass structure can be quantitatively calculated, the calculation precision is high, the result is reliable, and meanwhile, data support can be provided for subsequent dangerous rock disaster prevention and control.

Description

Technical Field

[0001] The present invention belongs to the technical field of prevention and control of dangerous rock geological disasters in reservoir areas, and particularly relates to a method for identifying and monitoring underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone based on a multi-beam sonar. Background Art

[0002] Under the combined action of the periodic fluctuation of the reservoir water level, the self-weight stress of the rock mass, and rainfall-groundwater seepage in the water-level-fluctuation zone of the reservoir area, the rock mass on the shore slope undergoes multiple deterioration processes such as chemical corrosion / dissolution, mechanical transportation, and stress corrosion, resulting in strong damage and deterioration of the base of the dangerous rock mass and a significant increase in the geological disaster risk.

[0003] Relevant research results show that the base of the rock mass on the high-steep slope is not only a sensitive indicator of the cumulative damage of the rock mass but also a key potential boundary for the instability of the rock mass. The structure of the rock mass base has a significant control effect on the fracture failure mode and instability mechanism of large-scale collapses. However, due to the limitations of detection technology, traditional investigation methods are difficult to obtain the underwater rock mass structure and shore slope morphology of the dangerous rock mass in the water-level-fluctuation zone of the reservoir area, resulting in serious deficiencies in the identification and monitoring of underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for identifying and monitoring underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone based on a multi-beam sonar to solve the problems of insufficient acquisition of underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone of the reservoir area and lack of monitoring means.

[0005] The embodiment of the present application is implemented as follows. There is provided a method for identifying and monitoring underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone based on a multi-beam sonar, including:

[0006] Collecting reservoir area data;

[0007] Installing a multi-beam measurement system;

[0008] Obtaining underwater data of the reservoir area;

[0009] Processing the underwater data of the reservoir area;

[0010] Fusing the underwater and overwater terrains;

[0011] Establishing underwater hidden danger marks:

[0012] Extracting underwater hidden danger information;

[0013] Monitoring the deformation of underwater hidden dangers.

[0014] In some embodiments, the reservoir area data includes one or more of terrain data, the slope of the shore slope rock formation, point cloud data of the water-level-fluctuation area, the distribution of dangerous rocks, and the hydrological conditions of the reservoir area after impoundment; wherein, the hydrological conditions of the reservoir area after impoundment include water level and / or flow velocity.

[0015] In some embodiments, a survey ship is provided, and the multi-beam survey system is installed on the survey ship. The multi-beam survey system includes an RTK-GNSS navigation and positioning system, an attitude sensor, a multi-beam transducer, and a sound velocity profiler.

[0016] In some embodiments, the underwater data in the reservoir area includes the water depth in the reservoir area and the sound velocity profile data at different water depths. It is also necessary to obtain the position and attitude data of the survey ship.

[0017] In some embodiments, the CARIS HIPS / SIPS or Hypack-related software is used to perform sound velocity correction, draft correction, and RTK-GNSS data calculation on the water depth data in the reservoir area respectively. Using the position and attitude data of the survey ship, the water depth data in the reservoir area is corrected to generate a high-precision underwater three-dimensional model and exported as underwater LAS or XYZ point cloud format data.

[0018] In some embodiments, the underwater LAS or XYZ point cloud format data and the water-level-fluctuation zone point cloud data above the water are imported into point cloud data processing software for ICP registration to establish an underwater three-dimensional model of the water-level-fluctuation zone; the point cloud data processing software includes one or more of LeicaCyclone 3DR, Cloud Compare, and Cloud Viewer software.

[0019] In some embodiments, the underwater three-dimensional model of the water-level-fluctuation zone is imported into point cloud data processing software, and the areas on the underwater three-dimensional model of the water-level-fluctuation zone with holes, concave terrains, and vertical texture features are marked as underwater hazard signs.

[0020] In some embodiments, based on the underwater three-dimensional model of the water-level-fluctuation zone and the underwater hazard signs, three-dimensional visual human-computer interactive interpretation is adopted to delimit the range with underwater hazard signs, and the central point coordinates, length, width, and depth data of the delimited area are extracted.

[0021] In some embodiments, the underwater part of the water-level-fluctuation zone is regularly data-collected to obtain the underwater LAS or XYZ point cloud format data for each period. The underwater LAS or XYZ point cloud format data for each period is processed, and the processed underwater LAS or XYZ point cloud format data for each period is imported into point cloud data processing software for ICP registration to construct underwater three-dimensional models of different periods in the same coordinate system, and differential comparison is performed on the underwater area to output a cumulative displacement map of deformation; among them, the methods for processing the underwater LAS or XYZ point cloud format data for each period include one or more of coordinate registration and point cloud thinning.

[0022] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are:

[0023] The present invention has completely acquired the underwater topographic data of the dangerous rocks in the water-level-fluctuation zone through a multi-beam underwater measurement system, making up for the deficiency of traditional investigation methods in obtaining the underwater structure of water-related dangerous rocks; and combined with the underwater hazard identification marks established based on the water-level-fluctuation zone's above-water point cloud data, it has achieved the accurate acquisition of the location and scale data of the underwater hazards of water-related dangerous rocks; by regularly obtaining the underwater topographic data and conducting elevation comparative analysis based on at least two phases of underwater topographic point cloud data, the deformation of the underwater part of the dangerous rocks can be quantitatively obtained, realizing the regular monitoring of the underwater part of the dangerous rocks, with high calculation accuracy and reliable results, and providing reasonable data support for the subsequent prevention and control of dangerous rock disasters. Description of the Drawings

[0024] Figure 1 It is a flowchart of the method for identifying and monitoring underwater hazards of dangerous rocks in the water-level-fluctuation zone based on multi-beam sonar provided by an embodiment of the present invention;

[0025] Figure 2 It is a three-dimensional underwater model diagram of the water-level-fluctuation zone provided by an embodiment of the present invention;

[0026] Figure 3 It is a schematic diagram of the characteristics of underwater hazard points provided by an embodiment of the present invention;

[0027] Figure 4 It is a schematic diagram of delineating underwater hazards provided by an embodiment of the present invention;

[0028] Figure 5 It is a diagram showing the deformation monitoring of underwater hazards in a typical water-level-fluctuation zone of the Three Gorges Reservoir area provided by an embodiment of the present invention. Detailed Embodiments

[0029] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0030] The technical solution of the present application is as follows:

[0031] As Figure 1 shown, in the first aspect, the embodiment of the present application provides a method for identifying and monitoring underwater hazards of dangerous rocks in the water-level-fluctuation zone based on multi-beam sonar, including:

[0032] S01. Collect data of the reservoir area;

[0033] S02. Install a multi-beam measurement system;

[0034] S03. Obtain underwater data of the reservoir area;

[0035] S04. Process the underwater data of the reservoir area;

[0036] S05. Integrate the above-water and underwater topographies;

[0037] S06. Establishment of underwater hidden danger signs:

[0038] S07. Extraction of underwater hidden danger information;

[0039] S08. Deformation monitoring of underwater hidden dangers.

[0040] This application can accurately delimit the scope of underwater hidden dangers, obtain their location information and scale data, quantitatively calculate the deformation information of the underwater part of the rock mass structure, with high calculation accuracy and reliable results. At the same time, it can also provide data support for the prevention and control of subsequent dangerous rock disasters.

[0041] The present invention has completely obtained the underwater terrain data of dangerous rocks in the water-level-fluctuation zone through a multi-beam underwater measurement system, making up for the deficiency of traditional investigation means in obtaining the underwater structure of water-related dangerous rocks; and combined with the underwater hidden danger identification signs established based on the water-level-fluctuation zone's above-water point cloud data, realizing the accurate acquisition of the location and scale data of underwater hidden dangers of water-related dangerous rocks; by regularly obtaining underwater terrain data and based on the elevation comparison analysis of at least two-phase underwater terrain point cloud data, the deformation situation of the underwater part of the dangerous rocks can be quantitatively obtained, realizing the regular monitoring of the underwater part of the dangerous rocks, with high calculation accuracy and reliable results, and providing reasonable data support for the prevention and control of subsequent dangerous rock disasters.

[0042] In the above-mentioned S01:

[0043] In some embodiments, the reservoir area data includes one or more of terrain data, bank slope rock layer slope, water-level-fluctuation zone point cloud data, dangerous rock distribution, and the hydrological conditions of the reservoir area after impoundment.

[0044] Further, the hydrological conditions of the reservoir area after impoundment include water level.

[0045] Further, the hydrological conditions of the reservoir area after impoundment include flow velocity.

[0046] In the above-mentioned S02:

[0047] In some embodiments: A survey ship is provided, and the multi-beam measurement system is installed on the survey ship. The multi-beam measurement system includes an RTK-GNSS navigation and positioning system, an attitude sensor, a multi-beam transducer, and a sound velocity profiler.

[0048] Further, the measurement accuracy of the multi-beam measurement system within a range of 50 m underwater is not less than 0.1 m.

[0049] Further, the measurement depth range of the multi-beam transducer is greater than the water depth range, and the measurement frequency of the multi-beam transducer is not less than 400 kHz.

[0050] Furthermore, the angle between the multi-beam transducer and the horizontal plane is 0° to 45°, for example, it can be 0°, 5°, 10°, 15°, 20°, 25°, 30°, 35°, 40°, 45°, etc.

[0051] It can be understood that the RTK-GNSS navigation and positioning system has the function of a continuously operating GNSS reference station network system CORS. After being solved by multiple reference stations, the positioning accuracy of this technology reaches the centimeter level.

[0052] It can be understood that the survey ship should have a speed control function, and its speed range can be controlled as low as 4 knots to 6 knots at the lowest.

[0053] It can be understood that the survey ship is selected according to the hydrological conditions in the reservoir area after impoundment.

[0054] In S03:

[0055] In some embodiments, the underwater data in the reservoir area includes the water depth in the reservoir area and the sound velocity profile data at different water depths.

[0056] Furthermore, the position and attitude data of the survey ship need to be obtained.

[0057] In S04:

[0058] In some embodiments, the CARIS HIPS / SIPS or Hypack related software is used to perform sound velocity correction, draft correction, and RTK-GNSS data solution on the water depth data in the reservoir area respectively. Using the position and attitude data of the survey ship, the water depth data in the reservoir area is corrected to generate a high-precision underwater three-dimensional model and exported as underwater LAS or XYZ point cloud format data.

[0059] It can be understood that since the temperature, pressure, and salinity are different at different water depths, the sound wave propagation rate is different. Therefore, when processing the water depth data in the reservoir area, the sound velocity profile data at different water depths needs to be measured and the sound velocity correction needs to be performed on the water depth data in the reservoir area.

[0060] It can also be understood that the multi-beam measurement system measures the actual water depth data without coordinate information. Therefore, it is necessary to collect the position information of the survey ship through the RTK-GNSS navigation and positioning system and the attitude data measured by the attitude sensor, and perform conversion on the water depth data in the reservoir area to obtain the underwater terrain data with coordinate information.

[0061] In S05:

[0062] In some embodiments, the underwater LAS or XYZ point cloud format data and the water surface drawdown area point cloud data are imported into the point cloud data processing software for ICP registration to establish a three-dimensional model of the drawdown area underwater.

[0063] Further, the point cloud data processing software includes one or more of Leica Cyclone 3DR, Cloud Compare, and CloudViewer software.

[0064] In S06:

[0065] In some embodiments, the underwater three-dimensional model of the drawdown area is imported into the point cloud data processing software, and the areas on the underwater three-dimensional model of the drawdown area with holes, concave terrains, and vertical texture features are marked as underwater hidden danger signs.

[0066] It can be understood that by combining the micro-topography features of the water surface part of the drawdown area, the convexity and concavity of the underwater three-dimensional model of the drawdown area are calculated, and the areas on the underwater three-dimensional model of the drawdown area with holes, concave terrains, and vertical texture features are marked as underwater hidden danger signs.

[0067] In S07:

[0068] In some embodiments: Based on the underwater three-dimensional model of the drawdown area and the underwater hidden danger signs, three-dimensional visual human-computer interactive interpretation is adopted to delimit the range with underwater hidden danger signs, and the central point coordinates, length, width, and depth data of the delimited area are extracted.

[0069] In S08:

[0070] In some embodiments, data of the underwater part of the drawdown area is collected regularly to obtain underwater LAS or XYZ point cloud format data for each period. The underwater LAS or XYZ point cloud format data for each period is processed, and the processed underwater LAS or XYZ point cloud format data for each period is imported into the point cloud data processing software for ICP registration to construct underwater three-dimensional models of different periods in the same coordinate system, and differential comparison is performed on the underwater area to output a deformation cumulative displacement map.

[0071] Further, the method for processing the underwater LAS or XYZ point cloud format data for each period includes one or more of coordinate registration and point cloud thinning.

[0072] It can be understood that the purpose of processing the underwater LAS or XYZ point cloud format data is to ensure that the data resolution and coordinate system are consistent for each period.

[0073] It can be understood that the multi-beam system is used to regularly collect data of the underwater part of the drawdown zone, and the deformation of the underwater part of the dangerous rock drawdown zone is evaluated by comparing and analyzing the changes in underwater terrain elevation at different time periods.

[0074] Application Example

[0075] Taking a typical drawdown zone in the Three Gorges Reservoir Area as an example, the method for identifying and monitoring underwater hidden dangers of dangerous rocks in the drawdown zone based on a multi-beam sonar:

[0076] Collect data of the reservoir area:

[0077] According to the data collection in the early stage, the water depth range of this section is about 150 - 200m, the river width is about 500 - 800m, the bank slope structure is mainly steep slopes, with a slope of about 35° - 65°. At the same time, high-precision point cloud data of the water part of the water-level-fluctuation zone was collected.

[0078] Install the multibeam measurement system:

[0079] According to the conditions of the survey area, the HydroMax MS8240 multibeam sounding system (sounding range: 0 - 400m) is used for the measurement equipment, equipped with a POS15 attitude instrument, an SVP1500 sound velocity profiler, and a ZhongHaiDa RTK-GNSS navigation and positioning system. And this set of system is installed on the Yunzhou Smart ME120 unmanned survey boat platform.

[0080] Obtain underwater data of the reservoir area:

[0081] Two survey lines are designed. Among them, the bank slope area is the main survey line, with a length of about 4.5km, and the distance from the bank slope is about 50 - 100m. The transducer is fixed in an inclined installation manner, with an inclination angle of about 25°. The transducer frequency is set to 600kHz. Using this method, 2-phase data at different time periods were collected.

[0082] Process the underwater data of the reservoir area:

[0083] Use the HydroMax Hypack software to perform sound velocity, draft correction, and RTK-GNSS data resolution respectively. Using the ship attitude data measured by the attitude sensor, the sounding data is corrected to generate a high-precision underwater three-dimensional model topographic map, and the data is exported in LAS point cloud format.

[0084] Fuse the underwater and overwater topographies:

[0085] Import the underwater point cloud and the overwater water-level-fluctuation zone point cloud data into the Leica Cyclone 3DR software for ICP registration to establish an integrated three-dimensional model of the underwater and overwater areas of the water-level-fluctuation zone. As Figure 2 shown, it is the complete three-dimensional model of the water-level-fluctuation zone, and the elevation rendering is used to improve the visualization degree of the model.

[0086] Establish underwater hazard signs:

[0087] Through the micro-topography comparison and analysis of the integrated three-dimensional model of the underwater and overwater areas of the water-level-fluctuation zone, the main underwater hazards in this section are karst caves, cavities, and fissures. Their characteristics shown on the three-dimensional model are "holes", "concave terrain", and "vertical textures". Therefore, the underwater hazards in this survey area are interpreted with reference to the underwater hazard structure. As Figure 3As shown, the forms of underwater hidden dangers on the 3D model mainly present three types, namely karst caves - manifested as hole forms, concave cavities - manifested as concave terrains, and fissures - manifested as vertical textures.

[0088] Extraction of underwater hidden danger information:

[0089] After importing the integrated 3D model data of the water-level-fluctuation zone above and below water into the Leica Cyclone 3DR software, regional delineation is carried out according to the characteristics of underwater hidden dangers. As Figure 4 shown, through human-computer interactive interpretation, the surface flatness of the model is calculated. Among them, the green part has a higher flatness and no underwater hidden dangers develop. The red and blue parts have a lower flatness. Combining with the underwater morphology analysis, it is obvious that underwater hidden dangers develop, and they are delineated. After determining the development range of the hidden dangers, the automatic improvement algorithm is selected to encrypt and smooth the regional data, and the underwater hidden danger development plane is segmented and statistically analyzed, and batch extraction of elements such as its area, scale, and height is carried out, as shown in Table 1.

[0090] Table 1 Statistical table of underwater hidden danger development parameters at the case analysis points

[0091]

[0092] Deformation monitoring of underwater hidden dangers:

[0093] Coordinate registration and point cloud thinning are carried out using two-phase point cloud data to ensure that the resolutions and coordinate systems of the two-phase data are consistent. The two-phase point cloud data are respectively imported into the Leica Cyclone 3DR software, and the point cloud comparison function is run to obtain the deformation data of the underwater hidden dangers in two phases. As Figure 5 shown, among them, the blue area shows no deformation, and the red area has a larger deformation. According to the comparison of the two-phase data, it can be known that the deformation of the underwater hidden dangers is small during this measurement period.

[0094] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for identifying and monitoring underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone based on a multi-beam sonar, characterized in that, Including: Collecting reservoir area data; Installing a multibeam measurement system; Obtaining underwater data of the reservoir area; Processing the underwater data of the reservoir area; Fusing the underwater and overwater topographies; Establishing underwater hazard signs: Extracting underwater hazard information; Monitoring the deformation of underwater hazards.

2. The underwater hidden danger identification and monitoring method for dangerous rocks in the water-level-fluctuation zone based on multi-beam sonar according to claim 1, characterized in that The reservoir area data includes one or more of topographic data, the slope of the bank slope rock stratum, point cloud data of the drawdown zone, the distribution of dangerous rocks, and the hydrological conditions of the reservoir area after impoundment; among them, the hydrological conditions of the reservoir area after impoundment include water level and / or flow velocity.

3. The underwater hidden danger identification and monitoring method for dangerous rocks in the water-level-fluctuation zone based on multi-beam sonar according to claim 1, characterized in that Providing a survey ship, on which the multibeam measurement system is installed, and the multibeam measurement system includes an RTK-GNSS navigation and positioning system, an attitude sensor, a multibeam transducer, and a sound velocity profiler.

4. The method for identifying and monitoring underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone based on a multi-beam sonar according to claim 1, wherein The underwater data of the reservoir area includes the water depth of the reservoir area and the sound velocity profile data at different water depths, and the position and attitude data of the survey ship also need to be obtained.

5. The method for identifying and monitoring underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone based on multi-beam sonar according to claim 1, characterized in that, Using CARIS HIPS / SIPS or Hypack-related software to perform sound velocity correction, draft correction, and RTK-GNSS data calculation on the water depth data of the reservoir area respectively, and using the position and attitude data of the survey ship to correct the water depth data of the reservoir area to generate a high-precision underwater three-dimensional model and export it as underwater LAS or XYZ point cloud format data.

6. The method for identifying and monitoring underwater hidden dangers of dangerous rocks in the drawdown zone based on multi-beam sonar according to claim 5, wherein, Importing the underwater LAS or XYZ point cloud format data and the overwater drawdown zone point cloud data into point cloud data processing software for ICP registration to establish an underwater three-dimensional model of the drawdown zone; the point cloud data processing software includes one or more of Leica Cyclone 3DR, Cloud Compare, and Cloud Viewer software.

7. The method for identifying and monitoring underwater hidden dangers of dangerous rocks in the water-level-fluctuation zone based on a multi-beam sonar according to claim 1, characterized in that Importing the underwater three-dimensional model of the drawdown zone into point cloud data processing software, and marking the areas with holes, concave topography, and vertical texture features on the underwater three-dimensional model of the drawdown zone as underwater hazard signs.

8. The underwater hidden danger identification and monitoring method for dangerous rocks in the water-level-fluctuation zone based on multi-beam sonar according to claim 1, wherein Based on the underwater three-dimensional model of the drawdown zone and the underwater hazard signs, using three-dimensional visualization and human-computer interactive interpretation to delimit the range with underwater hazard signs, and extract the central point coordinates, length, width, and depth data of the delimited area.

9. The underwater hidden danger identification and monitoring method for dangerous rocks in the water-level-fluctuation zone based on multi-beam sonar according to claim 1, characterized in that Regularly collecting data on the underwater part of the drawdown zone to obtain the underwater LAS or XYZ point cloud format data for each period, processing the underwater LAS or XYZ point cloud format data for each period, importing the processed underwater LAS or XYZ point cloud format data for each period into point cloud data processing software for ICP registration, constructing underwater three-dimensional models of different periods of the drawdown zone in the same coordinate system, performing differential comparison on the underwater area, and outputting a cumulative displacement map of deformation; among them, the method for processing the underwater LAS or XYZ point cloud format data for each period includes one or more of coordinate registration and point cloud thinning.

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