Real-time visualization method and system for underwater rock breaking based on water flow compensation and sonar point cloud evolution

Abstract

The application discloses a kind of underwater rock breaking real-time visualization method and system based on water flow compensation and sonar point cloud evolution, comprising: obtaining the time series sonar point cloud data of underwater rock breaking operation area and the spatial positioning data of equipment, establish water flow influence compensation geometric model to carry out reverse correction;Based on the point cloud pretreatment of sonar imaging geometric model, construct coordinate mapping matrix, adopt adaptive filtering to remove water spot noise;Spatial difference calculation is carried out to the point cloud after pretreatment, the morphological change characteristic quantity of rock point cloud is extracted, the physical parameters of rock breaking equipment and rock are obtained, are substituted into the preset rock damage mechanics model, calculate theoretical crushing parameter;Morphological change characteristic quantity and theoretical parameter are matched to analyze to determine evolution state;Marking result is mapped to three-dimensional rendering engine and outputs real-time visualization scene.The method of the application breaks through the limitation of pure graphics visual contrast, improves the image processing efficiency and state recognition accuracy in complex environment.

Description

Technical Field

[0001] This invention relates to the field of underwater operation monitoring technology, and in particular to a real-time visualization method and system for underwater rock breaking based on water flow compensation and sonar point cloud evolution. Background Technology

[0002] In deep-water rock-breaking operations such as channel clearing and submarine trench excavation, high turbidity water can render traditional optical imaging equipment completely ineffective. Current underwater operations often rely on experience and involve blind drilling. This blind drilling not only easily leads to over-crushing of the target rock, causing prolonged ineffective operation of construction machinery and significantly increasing energy consumption and greenhouse gas emissions, but also triggers large-scale seabed disturbances due to excessive fragmentation, forming large-scale plumes of high-turbidity suspended sediment, causing long-term negative impacts on the surrounding marine benthic habitats and aquatic ecosystems. Although sonar detection technology has been introduced, existing methods are mostly static, single-scan measurements, lacking the tracking and quantification of the continuous dynamic evolution of the rock after impact. Furthermore, in deep water (greater than 40m) and high-velocity (greater than 2m / s) environments, detection equipment and construction machinery experience severe lateral drift, causing the coordinate references of successive sonar scans to not coincide, making high-precision dynamic comparison impossible. Furthermore, traditional point cloud processing relies solely on pure graphic contour comparison, making it difficult to accurately distinguish between suspended sediment, detached rock blocks, and internally damaged but not detached rocks under conditions of heavy suspended sediment interference.

[0003] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide a real-time visualization method and system for underwater rock breaking based on water flow compensation and sonar point cloud evolution, thereby overcoming the shortcomings of complex underwater operating environments and the inability to accurately determine rock breaking effects.

[0005] To achieve the above objectives, this invention provides a real-time visualization method for underwater rock breaking based on water flow compensation and sonar point cloud evolution, comprising the following steps:

[0006] (1) Acquire time-series sonar point cloud data of the underwater rock breaking operation area and spatial positioning data of the rock breaking equipment; simultaneously acquire water surface positioning reference data and hydrological dynamic monitoring data, establish a water flow impact compensation geometric model for reverse correction, and unify the absolute coordinate reference of sonar scanning.

[0007] (2) Based on the point cloud preprocessing of the sonar imaging geometric model, a coordinate mapping matrix from the two-dimensional acoustic image to the three-dimensional world coordinate system is constructed, and adaptive filtering is used to remove muddy water spot noise to obtain the three-dimensional point cloud.

[0008] (3) Perform spatial difference calculation on the preprocessed three-dimensional point cloud, extract morphological change feature quantities, obtain the operating parameters of the rock breaking equipment and the physical property parameters of the target rock, substitute them into the preset rock damage mechanics model, and calculate the theoretical breaking parameters; perform matching analysis between the morphological change feature quantities and the theoretical breaking parameters, determine and mark the evolution state of the rock point cloud.

[0009] (4) Output the real-time dynamic visualization scene based on the labeling results of the evolution state.

[0010] Preferably, in the above technical solution, step (1) establishes a geometric model for water flow impact compensation, and calculates the horizontal drift offset of the water flow to the equipment below based on hydrological dynamic monitoring data. The calculation includes:

[0011] Acquire layered flow velocity data of the underwater construction area, and discretize the vertical water depth from the water surface to the target seabed into n integration layers, each with a depth of [missing information]. At any depth At each location, the drag force of the water flow on the lowering equipment body is calculated. and the cable drag force on the equipment suspension cable. ; Obtain the effective buoyancy of the lowered equipment in the water Based on the principle of spatial force system equilibrium, the total horizontal drift offset of the lowered equipment when it reaches the target water depth is calculated. The calculation formula is as follows:

[0012] ;

[0013] Combined with water flow direction angle Based on total horizontal drift offset The water surface positioning reference data is reverse-shifted and corrected to unify the absolute coordinate reference of sonar scans under different time series.

[0014] Preferably, in the above technical solution, step (2) adopts an adaptive filtering image enhancement algorithm based on spatial density to remove suspended matter and bubble noise in the time-series sonar point cloud data.

[0015] Preferably, in the above technical solution, the rock damage mechanics model in step (3) is a dynamic-static load coupled rock fragmentation model;

[0016] The acquisition of operating parameters for the rock-breaking equipment includes: acquiring the final impact velocity V of the drill bit of the rock-breaking equipment. I With average wave drag m;

[0017] The calculation yields theoretical fracture parameters, including the theoretical crack propagation length C, calculated using the following formula:

[0018] ;

[0019] In the formula, For system parameters, The ratio of the dynamic elastic modulus to the hardness of the rock. For static load damage parameters, Stress intensity factor denoted as the impact penetration index, and m as the average wave resistance of the drill bit.

[0020] Preferably, in the above technical solution, step (3) involves matching and analyzing the morphological change characteristics with theoretical fracturing parameters to determine and mark the evolution state of the rock point cloud, including:

[0021] Centered on the impact location and the impact coordinates of the rock-breaking drill bit, within a spatial envelope with a radius equal to the theoretical crack propagation length C, calculate the actual reduction in spatial volume of the point cloud in the new frame compared to the previous frame. Based on the theoretical crack propagation length C and the morphological characteristics of rock fracture, a dynamic fracture volume determination threshold is constructed. The calculation formula is as follows:

[0022] ;

[0023] In the formula, The macroscopic fracture cone angle of the target rock under impact load. The effective stripping and identification coefficients related to the spatial resolution of sonar point clouds;

[0024] Reduction in actual space volume With the dynamic crushing volume determination threshold Perform a logical comparison and judgment: If there is point cloud displacement and If the spatial change is determined to be caused by the disturbance of suspended sediment or the expansion of microcracks within the rock mass, the point cloud state of that area is marked as rock undergoing damage; If the rock mass has overcome its tensile strength and undergone macroscopic fracturing and peeling, the point cloud state of that area is marked as peeled fragments.

[0025] Preferably, in the above technical solution, step (4) maps the three-dimensional point cloud to the three-dimensional rendering engine according to the marking results of the evolution state, assigns color mapping rules and transparency levels corresponding to different states, and outputs a real-time dynamic visualization scene of the underwater rock breaking process.

[0026] Preferably, in the above technical solution, assigning color mapping rules and transparency levels to different states includes: assigning different color mapping rules and transparency levels to unbroken rocks, damaged rocks, and point clouds in the state of peeling fragments; wherein, a bright or flashing visual cue is generated for the area of ​​damaged rocks.

[0027] A system for real-time visualization of underwater rock breaking based on water flow compensation and sonar point cloud evolution, the system being constructed based on the aforementioned method, the system comprising:

[0028] The input module includes data acquisition from underwater sensors and operational and rock parameters.

[0029] The core processing system module connects with the data in the input module, establishes a geometric model for water flow impact compensation for reverse correction, unifies the absolute coordinate reference of sonar scanning, and outputs the corrected reference coordinates.

[0030] The point cloud evolution module, connected to the input module and the core processing system module, acquires 3D point cloud data, performs spatial difference calculations on the preprocessed 3D point cloud, extracts morphological change features, obtains the operating parameters of the rock breaking equipment and the physical property parameters of the target rock, substitutes them into a preset rock damage mechanics model, and calculates theoretical fracturing parameters; it then matches and identifies the morphological change features with the theoretical fracturing parameters to determine and mark the evolution state of the rock point cloud; and...

[0031] The visualization module is connected to the point cloud evolution module and outputs a real-time dynamic visualization scene based on the marking results of the evolution state.

[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0033] (1) The present invention is an underwater rock breaking real-time visualization method based on water flow compensation and sonar point cloud evolution. It innovatively uses the water flow drag force integral model to inversely compensate spatial coordinates, eliminates the positioning error caused by deep water high flow velocity, and provides a strict alignment basis for subsequent frame evolution comparison of point cloud, forming a technical closed loop of positioning and visual acquisition.

[0034] (2) The method of the present invention breaks through the limitations of pure graphics visual comparison, and uses the underlying physical impact mechanics as the constraint condition for point cloud segmentation. Even under the cover of muddy water and sand, it can still accurately determine the rock breaking effect, which greatly improves the image processing efficiency and state recognition accuracy in complex environments.

[0035] (3) The method of this invention innovatively uses the water flow drag force integral model to inversely compensate for spatial coordinates, eliminating the positioning error caused by high current velocity in deep water. This ensures that high-intensity crushing operations are strictly limited to the target area, avoiding accidental blasting and excavation caused by positioning drift, and protecting the natural topography and benthic ecosystem of the seabed in non-operation areas from unnecessary damage to the greatest extent.

[0036] (4) The method of the present invention uses the underlying physical impact mechanics as a constraint condition for point cloud segmentation, which can accurately distinguish the point cloud state of the rock being damaged and the already peeled fragments. This mechanism effectively guides the equipment to stop hitting the rock mass as soon as it reaches the macroscopic fragmentation and peeling threshold, which greatly shortens the ineffective cutting and operation time of heavy underwater equipment and significantly reduces the total fuel consumption and overall carbon footprint of a single rock breaking project. Attached Figure Description

[0037] Figure 1 This is a flowchart of the underwater rock-breaking real-time visualization method based on water flow compensation and sonar point cloud evolution according to the present invention;

[0038] Figure 2 This is a diagram of the real-time underwater rock-breaking monitoring system architecture based on the underwater rock-breaking real-time visualization system and sonar point cloud evolution according to the present invention. Detailed Implementation

[0039] The following detailed description of specific embodiments is provided in conjunction with the accompanying drawings, but it should be understood that the scope of protection of the present invention is not limited to the specific embodiments.

[0040] Unless otherwise expressly stated, throughout the specification and claims, the term "comprising" or its variations such as "including" or "comprises" shall be understood to include the stated elements or components without excluding other elements or other components.

[0041] Unless otherwise specified, all raw materials and reagents used in the examples are commercially available.

[0042] like Figures 1 to 2 As shown, a real-time visualization method for underwater rock breaking based on water flow compensation and sonar point cloud evolution according to a specific embodiment of the present invention includes the following steps:

[0043] Step S1: Multi-source data synchronous acquisition and reverse compensation for water flow impact, acquire sonar time series data and hydrological / RTK data, establish compensation model to correct the downlink coordinates.

[0044] Acquire time-series sonar point cloud data of the underwater rock breaking operation area and spatial positioning data of the rock breaking equipment; simultaneously acquire water surface positioning reference data and hydrological dynamic monitoring data, establish a geometric model for water flow impact compensation for reverse correction, and unify the absolute coordinate reference of sonar scanning.

[0045] A geometric model for water flow impact compensation is established, and the horizontal drift offset of the downstream equipment due to water flow is calculated based on hydrological dynamic monitoring data. The calculation includes:

[0046] Obtain layered flow velocity data of the underwater construction area, and discretize the vertical water depth from the water surface to the target seabed into n integration layers, each with a depth of [missing information]. At any depth At each location, the drag force of the water flow on the lowering equipment body is calculated. and the cable drag force on the equipment suspension cable. ; Obtain the effective buoyancy of the lowered equipment in the water Based on the principle of spatial force system equilibrium, the total horizontal drift offset of the lowered equipment when it reaches the target water depth is calculated. The calculation formula is as follows:

[0047] ;

[0048] Combined with water flow direction angle Based on total horizontal drift offset The water surface positioning reference data is reverse-shifted and corrected to unify the absolute coordinate reference of sonar scans under different time series.

[0049] Step S2: Based on the point cloud preprocessing of the sonar imaging geometric model, construct the coordinate mapping matrix and use adaptive filtering to remove murky spot noise.

[0050] Point cloud preprocessing based on sonar imaging geometric model: construct coordinate mapping matrix from two-dimensional acoustic image to three-dimensional world coordinate system; use adaptive filtering to remove muddy water spot noise and obtain three-dimensional point cloud.

[0051] The method of removing murky water spot noise by adaptive filtering includes using an adaptive filtering image enhancement algorithm based on spatial density to remove suspended matter and bubble noise in time-series sonar point cloud data.

[0052] Step S3: Perform point cloud dynamic evolution analysis and differential calculation of point cloud changes based on the fusion of rock damage constitutive model, and compare the state with the RHT damage model and crack propagation formula.

[0053] Spatial difference calculation is performed on the preprocessed 3D point cloud to extract morphological change features, obtain the operating parameters of the rock breaking equipment and the physical property parameters of the target rock, substitute them into the preset rock damage mechanics model, and calculate the theoretical breaking parameters; the morphological change features are matched and analyzed with the theoretical breaking parameters to determine and mark the evolution state of the rock point cloud.

[0054] The rock damage mechanics model is a dynamic-static load coupled rock fragmentation model;

[0055] The acquisition of operating parameters for the rock-breaking equipment includes: acquiring the final impact velocity V of the drill bit of the rock-breaking equipment. I With average wave drag m;

[0056] The calculation yields theoretical fracture parameters, including the theoretical crack propagation length C, calculated using the following formula:

[0057] ;

[0058] In the formula, For system parameters, The ratio of the dynamic elastic modulus to the hardness of the rock. For static load damage parameters, Stress intensity factor denoted as the impact penetration index, and m as the average wave resistance of the drill bit.

[0059] By matching morphological change characteristics with theoretical fracturing parameters, the evolutionary state of rock point clouds is determined and labeled, including:

[0060] Centered on the impact location and the impact coordinates of the rock-breaking drill bit, within a spatial envelope with a radius equal to the theoretical crack propagation length C, calculate the actual reduction in spatial volume of the point cloud in the new frame compared to the previous frame. Based on the theoretical crack propagation length C and the morphological characteristics of rock fracture, a dynamic fracture volume determination threshold is constructed. The calculation formula is as follows:

[0061] ;

[0062] In the formula, The macroscopic fracture cone angle of the target rock under impact load. The effective stripping and identification coefficients related to the spatial resolution of sonar point clouds;

[0063] Reduction in actual space volume With the dynamic crushing volume determination threshold Perform a logical comparison and judgment: If there is point cloud displacement and If the spatial change is determined to be caused by the disturbance of suspended sediment or the expansion of microcracks within the rock mass, the point cloud state of that area is marked as rock undergoing damage; If the rock mass has overcome its tensile strength and undergone macroscopic fracturing and peeling, the point cloud state of that area is marked as peeled fragments.

[0064] Step S4: Output a real-time dynamic visualization scene based on the labeling results of the evolutionary state.

[0065] Based on the labeling results of the evolutionary state, the 3D point cloud is mapped to the 3D rendering engine, and different color mapping rules and transparency levels are assigned to the point cloud of unbroken rock, damaged rock, and point cloud in the state of peeling fragments; in particular, a highlight or flashing visual cue is generated for the area of ​​damaged rock; and a real-time dynamic 3D visualization scene of the underwater rock breaking process is output to guide construction operations.

[0066] like Figure 2As shown, a system for real-time visualization of underwater rock breaking based on water flow compensation and sonar point cloud evolution is presented. This system is constructed based on the aforementioned method and includes:

[0067] The input module includes data acquisition from underwater sensors and operational and rock parameters.

[0068] The core processing system module connects with the data in the input module, establishes a geometric model for water flow impact compensation for reverse correction, unifies the absolute coordinate reference of sonar scanning, and outputs the corrected reference coordinates.

[0069] The point cloud evolution module, connected to the input module and the core processing system module, acquires 3D point cloud data, performs spatial difference calculations on the preprocessed 3D point cloud, extracts morphological change features, obtains the operating parameters of the rock breaking equipment and the physical property parameters of the target rock, substitutes them into a preset rock damage mechanics model, and calculates theoretical fracturing parameters; it then matches and identifies the morphological change features with the theoretical fracturing parameters to determine and mark the evolution state of the rock point cloud; and...

[0070] The visualization module is connected to the point cloud evolution module and outputs a real-time dynamic visualization scene based on the marking results of the evolution state.

[0071] The foregoing description of specific exemplary embodiments of the invention is for illustrative and explanatory purposes. These descriptions are not intended to limit the invention to the precise forms disclosed, and it will be apparent that many changes and variations can be made in accordance with the foregoing teachings. The exemplary embodiments were chosen and described in order to explain the specific principles of the invention and its practical application, thereby enabling those skilled in the art to implement and utilize various different exemplary embodiments of the invention, as well as various different choices and variations. The scope of the invention is intended to be defined by the claims and their equivalents.

Claims

1. A real-time visualization method for underwater rock breaking based on water flow compensation and sonar point cloud evolution, characterized in that, Includes the following steps: (1) Acquire time-series sonar point cloud data of the underwater rock breaking operation area and spatial positioning data of the rock breaking equipment; simultaneously acquire water surface positioning reference data and hydrological dynamic monitoring data, establish a water flow impact compensation geometric model for reverse correction, and unify the absolute coordinate reference of sonar scanning. (2) Based on the point cloud preprocessing of the sonar imaging geometric model, a coordinate mapping matrix from the two-dimensional acoustic image to the three-dimensional world coordinate system is constructed, and adaptive filtering is used to remove muddy water spot noise to obtain the three-dimensional point cloud. (3) Perform spatial difference calculation on the preprocessed three-dimensional point cloud, extract morphological change feature quantities, obtain the operating parameters of the rock breaking equipment and the physical property parameters of the target rock, substitute them into the preset rock damage mechanics model, and calculate the theoretical breaking parameters; match and identify the morphological change feature quantities with the theoretical breaking parameters, determine and mark the evolution state of the rock point cloud. (4) Output the real-time dynamic visualization scene based on the labeling results of the evolution state.

2. The method according to claim 1, characterized in that, Step (1) Establish a geometric model for water flow impact compensation, and calculate the horizontal drift offset of the equipment below the water flow based on hydrological dynamic monitoring data. The calculation includes: Obtain layered flow velocity data of the underwater construction area, and discretize the vertical water depth from the water surface to the target seabed into n integration layers, each with a depth of [missing information]. At any depth At each location, the drag force of the water flow on the lowering equipment body is calculated. and the cable drag force on the equipment suspension cable. ; Obtain the effective buoyancy of the lowered equipment in the water Based on the principle of spatial force system equilibrium, the total horizontal drift offset of the lowered equipment when it reaches the target water depth is calculated. The calculation formula is as follows: ； Combined with water flow direction angle Based on total horizontal drift offset The water surface positioning reference data is reverse-shifted and corrected to unify the absolute coordinate reference of sonar scans under different time series.

3. The method according to claim 1, characterized in that, Step (2) uses an adaptive filtering image enhancement algorithm based on spatial density to remove suspended matter and bubble noise from the time-series sonar point cloud data.

4. The method according to claim 1, characterized in that, The rock damage mechanics model described in step (3) is a dynamic-static load coupled rock fragmentation model; The acquisition of operating parameters for the rock-breaking equipment includes: acquiring the final impact velocity V of the drill bit of the rock-breaking equipment. I With average wave drag m; The calculation yields theoretical fracture parameters, including the theoretical crack propagation length C, calculated using the following formula: ； In the formula, For system parameters, The ratio of the dynamic elastic modulus to the hardness of the rock. For static load damage parameters, Stress intensity factor denoted as the impact penetration index, and m as the average wave resistance of the drill bit.

5. The method according to claim 1, characterized in that, Step (3) involves matching and analyzing the morphological change characteristics with theoretical fracturing parameters to determine and label the evolutionary state of the rock point cloud, including: Centered on the impact location and the impact coordinates of the rock-breaking drill bit, within a spatial envelope with a radius equal to the theoretical crack propagation length C, calculate the actual reduction in spatial volume of the point cloud in the new frame compared to the previous frame. Based on the theoretical crack propagation length C and the morphological characteristics of rock fracture, a dynamic fracture volume determination threshold is constructed. The calculation formula is as follows: ； In the formula, The macroscopic fracture cone angle of the target rock under impact load. The effective stripping and identification coefficients related to the spatial resolution of sonar point clouds; Reduction in actual space volume With the dynamic crushing volume determination threshold Perform a logical comparison and judgment: If there is point cloud displacement and If the spatial change is determined to be caused by the disturbance of suspended sediment or the expansion of microcracks within the rock mass, the point cloud state of that area is marked as rock undergoing damage; If the rock mass has overcome its tensile strength and undergone macroscopic fracturing and peeling, the point cloud state of that area is marked as peeled fragments.

6. The method according to claim 1, characterized in that, Step (4) Based on the marking results of the evolution state, the three-dimensional point cloud is mapped to the three-dimensional rendering engine, and color mapping rules and transparency levels are assigned to different states to output a real-time dynamic visualization scene of the underwater rock breaking process.

7. The method according to claim 6, characterized in that, The color mapping rules and transparency levels corresponding to different states include: assigning different color mapping rules and transparency levels to unbroken rocks, damaged rocks, and point clouds in the state of peeling fragments; among which, highlighting or flashing visual cues are generated for the areas of damaged rocks.

8. A system for real-time visualization of underwater rock breaking based on water flow compensation and sonar point cloud evolution, characterized in that, The system is constructed based on the method described in any one of claims 1-7, and the system comprises: The input module includes data acquisition from underwater sensors and operational and rock parameters. The core processing system module connects with the data in the input module, establishes a geometric model for water flow impact compensation for reverse correction, unifies the absolute coordinate reference of sonar scanning, and outputs the corrected reference coordinates. The point cloud evolution module, connected to the input module and the core processing system module, acquires 3D point cloud data, performs spatial difference calculations on the preprocessed 3D point cloud, extracts morphological change features, obtains the operating parameters of the rock breaking equipment and the physical property parameters of the target rock, substitutes them into a preset rock damage mechanics model, and calculates theoretical fracturing parameters; it then matches and identifies the morphological change features with the theoretical fracturing parameters to determine and mark the evolution state of the rock point cloud; and... The visualization module is connected to the point cloud evolution module and outputs a real-time dynamic visualization scene based on the marking results of the evolution state.

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