A visual-based precision excavation guidance control system and method
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CCCC SOUTH CHINA TRANSPORTATION CONSTR CO LTD
- Filing Date
- 2026-02-06
- Publication Date
- 2026-06-09
Smart Images
Figure CN122172657A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of river channel excavation control technology, and relates to a visualization-based precision excavation guidance control system and method. Background Technology
[0002] Channel dredging refers to the widening, deepening, and dredging of natural or existing waterways using manual or mechanical methods to meet the needs of safe navigation and transportation of ships.
[0003] Current traditional excavation techniques often rely on the experience of construction workers and conventional surveying tools, resulting in significant accuracy deficiencies. They struggle to precisely meet the requirements of complex terrain and high-precision engineering, easily leading to over-excavation or under-excavation, causing resource waste and potential engineering quality issues. Existing excavation guidance technologies, when facing complex geological conditions and dynamic construction environments, lack real-time and comprehensive information feedback mechanisms, making it difficult to adjust construction parameters in a timely manner. This limits construction efficiency and may also introduce safety risks.
[0004] Current excavation control technologies suffer from low visualization levels, making it difficult for construction personnel to intuitively and accurately grasp the construction situation and equipment operating status. Information transmission is hampered, affecting the timeliness and accuracy of decision-making, and consequently impacting the overall construction progress and quality. Therefore, research on visualization-based precise excavation guidance and control is of great significance for solving these problems and improving the overall level of excavation construction. Summary of the Invention
[0005] In view of this, in order to solve the problems of timeliness and accuracy of channel excavation process control mentioned in the background technology, a visualization-based precision excavation guidance control system and method are proposed.
[0006] The objective of this invention can be achieved through the following technical solution: The first aspect of this invention provides a visualization-based precision excavation guidance and control system, including: a geological exploration imaging module, which uses radar detection equipment to detect the riverbed of the target inland waterway to obtain the corresponding geological distribution.
[0007] The geological visualization module constructs a geological distribution cross-sectional map of the target inland waterway based on the aforementioned geological distribution and displays it visually.
[0008] The regional dynamic division monitoring module divides the monitoring area into several monitoring areas in real time based on the location of the target vessel, and generates a unique code.
[0009] The intelligent data acquisition and analysis module uses lidar and total station to acquire real-time three-dimensional distribution data of each monitoring area of the target inland waterway, and calculates elevation deviation and slope deviation.
[0010] The intelligent excavation demand identification module dynamically identifies over-excavated and under-excavated areas based on the elevation and slope deviations using a machine learning model, and generates adjustment suggestions.
[0011] The excavation path optimization and display module collects data on the medium type, water flow velocity, and reference location of each monitoring area, optimizes the excavation path through an ant colony algorithm, generates the optimal operation plan, and displays the route visually.
[0012] The second aspect of the present invention provides a visualization-based precise excavation guidance and control method, comprising: S1, using radar detection equipment to detect the riverbed of the target inland waterway to obtain the corresponding geological distribution.
[0013] S2. Based on the aforementioned geological distribution, construct a geological distribution cross-sectional map of the target inland waterway and visualize it.
[0014] S3. Based on the location of the target vessel, the monitoring area is dynamically divided in real time to obtain several monitoring areas, and a unique code is generated.
[0015] S4. Use lidar and total station to acquire real-time three-dimensional distribution data of each monitoring area of the target inland waterway, and calculate elevation deviation and slope deviation.
[0016] S5. Based on the elevation deviation and slope deviation, a machine learning model is used to dynamically identify over-excavated and under-excavated areas, and adjustment suggestions are generated.
[0017] S6. Collect data on medium type, water flow velocity and reference location in each monitoring area, optimize the excavation path using ant colony algorithm, generate the optimal operation plan, and display the route visually.
[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention obtains the corresponding geological distribution by detecting the riverbed of the target inland waterway and constructs the geological distribution cross-section map of the target inland waterway. It can clearly grasp the geological composition of different locations of the riverbed, provide real-time geological information reference for operators, and facilitate the comparison between the actual excavation and the cross-section map to control the quality.
[0019] (2) This invention dynamically identifies over-excavated and under-excavated areas by calculating elevation and slope deviations. It can determine in real time and accurately which parts of the construction area exceed the design elevation or slope range, and construction personnel can carry out targeted construction operations based on the identification results.
[0020] (3) This invention optimizes the excavation path and generates the optimal operation plan through the ant colony algorithm and displays the route in a visual way, which can help inland waterway construction achieve accurate path planning, efficient communication and decision-making, and comprehensive improvement in quality and efficiency. Attached Figure Description
[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0022] Figure 1 This is a schematic diagram showing the connections of the various modules in the system of the present invention.
[0023] Figure 2 This is a schematic diagram illustrating the implementation steps of the method of the present invention.
[0024] Figure 3 This is a schematic diagram of the dynamic monitoring area division corresponding to one embodiment of the present invention.
[0025] Attached reference numerals: 001--Reference position, 002--Monitoring width, 003--Front monitoring distance line, 004--Rear monitoring distance line, 005--River boundary line, 006--Center line. Detailed Implementation
[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0027] Please see Figure 1 As shown, the first aspect of the present invention provides a visualization-based precision excavation guidance and control system, including a geological exploration imaging module, a geological visualization display module, a regional dynamic division monitoring module, a data intelligent acquisition and analysis module, an excavation demand intelligent judgment module, and an excavation path optimization display module. The geological exploration imaging module is connected to the geological visualization display module, the regional dynamic division monitoring module is connected to the data intelligent acquisition and analysis module, the data intelligent acquisition and analysis module is connected to the excavation demand intelligent judgment module, and the excavation demand intelligent judgment module is connected to the excavation path optimization display module.
[0028] The geological exploration imaging module is used to detect the riverbed of the target inland waterway using radar detection equipment to obtain the corresponding geological distribution.
[0029] In a preferred embodiment of the present invention, the specific method for analyzing the geological distribution is as follows: the analysis of the geological distribution requires analyzing the medium type corresponding to each reflected wave and monitoring the reflection distance.
[0030] The radar detection equipment transmits high-frequency electromagnetic waves to the riverbed of the target inland waterway in real time, records the corresponding transmission time and frequency, and simultaneously uses a reflection wave receiving module to receive several corresponding reflection waves in real time, and obtains the reflection wave reception time, reflection wave frequency and reflection wave intensity for each reflection wave.
[0031] The medium type corresponding to each reflected wave is obtained by comparing the reflected wave frequency and intensity with the pre-constructed correspondence between each propagation medium and the reflected wave frequency and intensity.
[0032] It needs to be explained that the principle behind obtaining the medium type corresponding to each reflected wave is as follows: The working vessel travels along the inland waterway according to a planned route, and the radar equipment continuously emits high-frequency electromagnetic waves into the riverbed. When these electromagnetic waves encounter the interface of different geological layers, reflection and scattering occur due to the different dielectric constants of each layer, and some of the reflected waves return to the radar equipment and are received. During the journey, information such as the time and intensity of the received signals at different locations is continuously recorded. Combining the characteristics such as the intensity and frequency changes of the reflected signals, the geological type at different depths, such as clay, sand, or rock, is inferred, and thus the geological distribution of the target inland waterway is mapped.
[0033] Different geological media have different abilities to reflect electromagnetic waves. The intensity of the reflected wave is related to the properties of the geological media. Generally speaking, hard media such as rocks have a stronger ability to reflect electromagnetic waves and a larger reflected wave intensity; while soft media such as clay and sand have a relatively weaker ability to reflect waves and a smaller reflected wave intensity.
[0034] In one feasible embodiment, the intensity of the reflected wave is set to be represented by a voltage value. If the intensity of the reflected wave received from the rock layer is... The intensity of the reflected wave from the adjacent sand is... This allows us to determine that areas with high reflected wave intensity are rock layers, while those with lower intensity are sand layers, and to visually distinguish different geological layers through numerical comparison.
[0035] The reception time of each reflected wave and the transmission time of the high-frequency electromagnetic wave are extracted, and the difference is calculated to obtain the reflection duration of each reflected wave. The formula is then used to... Analysis yielded the monitoring reflection distances corresponding to each reflected wave. ,in Indicates the number of the reflected wave. , Indicates the number of reflected waves. Indicates the first The reflection time corresponding to each reflected wave Indicates the first The propagation speed of the reflected wave corresponds to the medium type. This indicates the reflection time corresponding to the first reflected wave, specifically the propagation time of the reflected wave in the water. This indicates the propagation speed of the reflected wave corresponding to the medium type of the first reflected wave, specifically the propagation speed of the reflected wave in water. .
[0036] In one feasible embodiment, the propagation speed of electromagnetic waves in water is known to be... The propagation speed in sandy soil is If, after the radar transmits a signal, the reflected wave received from a certain reflecting interface of the riverbed has a reflection time of... It is known that the electromagnetic wave traveling from the water surface to the riverbed through the two media of water and sand takes a time of [time missing] to propagate in the water. Time of propagation in sandy soil In water, according to the formula The distance from the water surface to the top of the sand can be obtained. In sandy soil, the distance from the top surface of the sand to the reflecting interface. Therefore, the total distance from the water surface to the reflective interface is... That is, the monitoring reflection distance corresponding to the reflected wave is 9 meters.
[0037] It should be noted that in practice, when ships sail above waterways where water exists, the radar detection equipment directly contacts water as the first medium it contacts when emitting high-frequency electromagnetic waves; it does not propagate through the air.
[0038] The geological visualization module is used to construct a geological distribution cross-sectional map of the target inland waterway based on the geological distribution, and to visualize and display it.
[0039] In a preferred embodiment of the present invention, the specific method for constructing the geological distribution cross-sectional map of the target inland waterway is as follows: the medium type and the width of each reflection layer at the current location are determined based on the medium type corresponding to each reflected wave and the monitoring reflection distance.
[0040] For example, if there are two reflected waves, and the medium type corresponding to the first reflected wave is water, and the medium type corresponding to the second reflected wave is sand, and the monitoring reflection distance corresponding to the first reflected wave is 4.5m, and the monitoring reflection distance corresponding to the second reflected wave is 9m, then there are two reflective layers at the current location. The distance from the first reflective layer to the bottom of the ship is 4.5m, and the distance from the second reflective layer to the ship is 9m. The medium type between the first reflective layer and the ship is water, and the medium type between the second reflective layer and the first reflective layer is sand.
[0041] A geological distribution profile map of the current location is generated based on the medium type and width of each reflective layer. The geological distribution profile map consists of several geological layers, with different geological layers corresponding to different medium types, and different medium types are represented by different colors.
[0042] For example, when the medium type is water, the corresponding geological distribution cross-section is blue, and when the medium type is sand, the corresponding geological distribution cross-section is yellow.
[0043] It should be noted that this invention obtains the corresponding geological distribution by detecting the riverbed of the target inland waterway and constructs a geological distribution cross-sectional map of the target inland waterway. This allows for a clear understanding of the geological composition at different locations of the riverbed, providing operators with real-time geological information for reference and facilitating comparison between the actual excavation and the cross-sectional map to control quality.
[0044] The dynamic regional division monitoring module is used to dynamically divide the monitoring area in real time based on the location of the target vessel to obtain several monitoring areas and generate a unique code.
[0045] In a preferred embodiment of the present invention, the specific method for real-time dynamic monitoring area division is as follows: Please refer to... Figure 3 As shown, the location of the target vessel is recorded as the reference position 001, and the monitoring range is determined based on the pre-set monitoring range setting rules. The monitoring range is then divided into several monitoring areas 002 by gridding.
[0046] The monitoring range setting rules specifically include determining the width of the monitoring range based on the pre-set monitoring width 003 to obtain the front monitoring far line 004 and the rear monitoring far line 005. Specifically, the reference position is located on the center line 007 corresponding to the monitoring width along the river channel direction. The monitoring range is composed of the area enclosed by the front monitoring far line, the rear monitoring far line and the river channel boundary line 006.
[0047] The intelligent data acquisition and analysis module is used to acquire three-dimensional distribution data of each monitoring area of the target inland waterway in real time using lidar and total station, and to calculate elevation deviation and slope deviation.
[0048] In a preferred embodiment of the present invention, the specific calculation method of the elevation deviation is as follows: extract the three-dimensional distribution data of each monitoring area of the target inland waterway, uniformly distribute the monitoring points in each monitoring area to obtain a number of monitoring points, obtain the actual measured elevation of each monitoring point, and at the same time obtain the design elevation of each monitoring point based on the construction plan.
[0049] The elevation deviation of each monitoring point is obtained by calculating the difference between the actual measured elevation and the corresponding design elevation.
[0050] It should be added that the elevation refers to the horizontal height of the target position relative to the bottom of the ship. If the sign of the elevation deviation of a monitoring point is positive, it means that the actual measured elevation of the monitoring point is greater than the design elevation. If the sign of the elevation deviation of a monitoring point is negative, it means that the actual measured elevation of the monitoring point is less than the design elevation.
[0051] In a preferred embodiment of the present invention, the specific calculation method of the slope deviation is as follows: extract the three-dimensional distribution data of each monitoring area of the target inland waterway, use the digital elevation model to obtain the actual measured slope of each monitoring point, and at the same time obtain the design slope of each monitoring point based on the construction plan.
[0052] The slope deviation of each monitoring point is calculated by comparing the actual measured slope with the corresponding design slope.
[0053] Specifically, the analysis method for the actual measured slope is as follows: The monitoring area is divided into grids using a Digital Elevation Model (DEM) to obtain several grid points. These grid points are then... The elevation value is recorded as The grid spacing in the x and y directions are respectively and Then the formulas for calculating the slope in the x-direction and the slope in the y-direction are: , Furthermore, the formula obtained based on the Pythagorean theorem and the arctangent function is... Calculate its actual measured slope .
[0054] It should be noted that the design concept of the actual measured slope calculation formula is as follows: 1. Calculate slope by direction: After dividing the monitoring area into grids using a Digital Elevation Model (DEM), each grid point and its elevation value are obtained. By dividing the elevation difference between adjacent grid points in the x and y directions by twice the grid spacing, the elevation change per unit horizontal distance in that direction is approximately obtained, which is the slope in that direction. This calculation method is based on the definition of slope as the ratio of elevation difference to horizontal distance, using the elevation change and spacing of adjacent points to estimate the local slope.
[0055] 2. Synthesize the actual measured slope: Based on the Pythagorean theorem, synthesize the slope in both the x and y directions. , The values are then combined to obtain a comprehensive slope value. This represents the total slope change on the two-dimensional plane at that grid point. However, this value is only a ratio and needs to be calculated using the arctangent function. Convert it to an angle value to obtain the actual measured slope. Such an angle value more intuitively represents the degree of slope of the terrain at that point.
[0056] The intelligent excavation demand identification module is used to dynamically identify over-excavated and under-excavated areas based on the elevation and slope deviations using a machine learning model, and to generate adjustment suggestions.
[0057] In a preferred embodiment of the present invention, the specific method for dynamically identifying over-excavated and under-excavated areas is as follows: extract the elevation deviation and slope deviation of each monitoring point, and calculate the elevation deviation and slope deviation of each monitoring point by taking the absolute value.
[0058] The elevation deviation and slope deviation of each monitoring point are compared with the preset elevation deviation threshold and slope deviation threshold, respectively. If the elevation deviation of a monitoring point is greater than the elevation deviation threshold or the slope deviation is greater than the slope deviation threshold, the monitoring point is identified as an abnormal monitoring point.
[0059] It should be added that the thresholds for elevation deviation and slope deviation are set based on the following: 1. Elevation deviation threshold setting: The elevation deviation threshold setting should consider engineering design standards, such as the design depth of the waterway, as a fundamental basis. The accuracy of the construction equipment is also crucial; higher precision equipment corresponds to a lower threshold. Geological conditions have an impact; the threshold can be relaxed for hard soil layers, while it is stricter for soft soil layers. Past experience can also be referenced.
[0060] 2. Slope Deviation Threshold Setting: The slope deviation threshold should be set according to the slope requirements of the engineering design. It is constrained by the slope control performance of the construction equipment; poor performance results in a higher threshold. Geological conditions also play a role; appropriate adjustments should be made for complex geological conditions. Reference should be made to data from similar past projects.
[0061] For example, the elevation deviation threshold is The slope deviation threshold is .
[0062] Abnormal monitoring points with positive elevation deviations are recorded as under-excavation identification points, and abnormal monitoring points with negative elevation deviations are recorded as over-excavation identification points. The number of under-excavation identification points and over-excavation identification points in each monitoring area are statistically obtained.
[0063] The number of under-excavation identification points and the number of over-excavation identification points in each monitoring area are compared. If the number of under-excavation identification points in a certain monitoring area is greater than the number of over-excavation identification points, the monitoring area is identified as an under-excavation area. If the number of under-excavation identification points in a certain monitoring area is less than the number of over-excavation identification points, the monitoring area is identified as an over-excavation area.
[0064] In a preferred embodiment of the present invention, the specific method for generating adjustment suggestions is as follows: areas identified as over-excavated and under-excavated are recorded as areas to be constructed.
[0065] Extract the three-dimensional distribution data of each construction area of the target inland waterway, and then obtain the design three-dimensional data of each construction area based on the construction plan. Use three-dimensional data processing software to obtain the actual monitored soil volume and design soil volume of each construction area, and then calculate the difference between the actual monitored soil volume and the design soil volume of each construction area to obtain the soil volume deviation of each construction area.
[0066] It should be noted that this invention dynamically identifies over-excavated and under-excavated areas by calculating elevation and slope deviations. It can determine in real time and accurately which parts of the construction area exceed the design elevation or slope range, and construction personnel can carry out targeted construction operations based on the identification results.
[0067] The excavation path optimization and display module is used to collect data on the medium type, water flow velocity, and reference location of each monitoring area, optimize the excavation path through the ant colony algorithm, generate the optimal operation plan, and display the route in a visual format.
[0068] In a preferred embodiment of the present invention, the specific method for optimizing the excavation path is as follows: extract the instruction manual and historical construction data of the target vessel, obtain the corresponding excavation speed for each medium type, and obtain the travel speed and power consumption of the target vessel under various water flow speeds, and then construct an excavation path optimization model based on the ant colony algorithm.
[0069] It should be explained that the ant colony algorithm refers to a heuristic optimization algorithm that simulates the behavior of ant colonies. When ants are searching for food, they release pheromones along their paths. Paths with higher pheromone concentrations are more likely to be chosen by other ants. Through this process, numerous ants gradually find the shortest path from the anthill to the food source. In this invention, this algorithm is used to construct an excavation path optimization model. The coordinates of the target vessel's current position, the coordinates of each over-excavated area, the coordinates of each under-excavated area, and the soil volume deviation of each area to be constructed are imported into the model to obtain the construction time and power consumption corresponding to each path. By calculating the construction evaluation index, the optimal excavation path is selected to achieve precise planning of inland waterway construction paths and a balanced optimization of construction efficiency and cost.
[0070] It should be noted that the specific construction process of the excavation path optimization model is as follows: 1. Obtain relevant data: Extract the target vessel's instruction manual and historical construction data to obtain the excavation speed for each media type, as well as the target vessel's travel speed and power consumption under various water flow velocities. This data forms the basis for building the model. Different media types affect the excavation speed, and water flow velocities affect the vessel's travel speed and power consumption, thereby affecting the overall construction efficiency and cost.
[0071] 2. Determine the model input parameters: Use the coordinates of the target vessel's current position, the coordinates of each over-excavated area, the coordinates of each under-excavated area, and the soil volume deviation of each area to be constructed as the model input. These parameters represent the actual situation of the construction area and have a significant impact on path planning.
[0072] 3. Model Construction Based on Ant Colony Algorithm: The data and parameters obtained above are integrated into the ant colony algorithm framework. In the model, path selection is based on the transition probability of ants between different nodes, and the transition probability is related to pheromone concentration and heuristic information. For example, paths with shorter distances and lower construction power consumption may have higher pheromone concentrations and are more likely to be selected.
[0073] The coordinates of the target vessel's current position, the coordinates of each over-excavated area, the coordinates of each under-excavated area, and the soil volume deviation of each area to be constructed are imported into the excavation path optimization model, thereby obtaining the construction time and construction power consumption corresponding to each path.
[0074] Based on the analysis of construction time and power consumption for each path, the construction evaluation index of each path is obtained, and then compared. The path with the largest construction evaluation index is selected as the target excavation path.
[0075] It should be added that the specific method for obtaining the construction evaluation index of each path in the analysis is as follows: the construction time corresponding to each path is... and construction power consumption Substitute into the formula The analysis yielded the construction evaluation index for each path. ,in This indicates the preset reference construction time. This indicates the preset reference construction power consumption. Indicates the path number. , Indicates the number of paths. These represent the weighting factors.
[0076] It should be noted that the above formula is constructed based on the following principles: 1. Comprehensive consideration of key construction factors: In river excavation projects, construction time and power consumption are key indicators for measuring construction efficiency and cost. Construction time affects project progress and is crucial to whether the project can be completed on schedule; power consumption is directly linked to construction costs, including equipment fuel consumption and power loss. Incorporating these two factors into the evaluation system allows for a comprehensive assessment of the advantages and disadvantages of different excavation paths.
[0077] 2. Establish a relative evaluation benchmark: refer to the construction duration. and reference construction power consumption As evaluation benchmarks, they represent the ideal or expected construction state. This is achieved by measuring the actual construction time of each path. and construction power consumption By comparing with reference values and calculating relative proportions, the performance of each path in terms of time and power consumption compared to the ideal situation can be clearly reflected. For example, if the construction time of a certain path is... Much larger If so, it means that the path is not efficient in terms of time utilization.
[0078] 3. Flexible adjustment of evaluation focus: weighting factors This assigns different levels of importance to construction duration and power consumption. In actual engineering projects, different projects place different emphasis on duration and power consumption. For example, projects with tight schedules may prioritize... The setting is set higher to highlight the importance of construction time in the evaluation; however, for projects with strict cost control, the setting can be increased. The value of focuses more on construction power consumption. By flexibly adjusting the weights, this formula can adapt to diverse engineering needs. For example, .
[0079] 4. Guiding Optimal Decision Making: Ultimately, the construction evaluation index is calculated using a formula. This provides a quantitative basis for selecting the optimal excavation path. The higher the value, the better the path performs after comprehensively considering construction time and power consumption, which helps the construction team make scientific and reasonable decisions and achieve a balance between efficiency and cost optimization in excavation operations.
[0080] In one feasible embodiment, it is assumed that three different excavation paths are simulated, with a pre-set reference construction time. Reference construction power consumption Weighting factors Data simulation calculations were performed based on the construction evaluation index analysis formulas for each path, and the corresponding simulation results were obtained. Some simulation results can be found in Table 1.
[0081] Table 1. Partial Simulation Data and Simulation Results
[0082] Based on the simulation results above, the construction evaluation index comprehensively considers two key factors: construction time and construction power consumption. In this simulation, path 1 has the highest construction evaluation index, at 1.25. This is because its construction time is shorter than the reference time (8h < 10h), and its construction power consumption is also lower than the reference power consumption. It is the best in terms of overall efficiency and cost.
[0083] Route 2 had the lowest construction evaluation index, at 0.83. Its construction time was longer than the reference time (12h > 10h), and its construction power consumption was also higher than the reference value. This resulted in poor performance in the overall evaluation.
[0084] The construction evaluation index for route 3 is 1, and its construction time and power consumption are exactly equal to the reference values, so its overall performance is at a mid-level. The construction evaluation index allows for a direct comparison of the overall performance of different routes in terms of efficiency and cost, thus providing a quantitative basis for selecting the optimal excavation route.
[0085] It should be noted that this invention optimizes the excavation path using the ant colony algorithm to generate the optimal operation plan and displays the route visually, which can help inland waterway construction achieve precise path planning, efficient communication and decision-making, and a comprehensive improvement in quality and efficiency.
[0086] Please see Figure 2 As shown, the second aspect of the present invention provides a visualization-based precise excavation guidance and control method, including: S1, using radar detection equipment to detect the riverbed of the target inland waterway to obtain the corresponding geological distribution.
[0087] S2. Based on the aforementioned geological distribution, construct a geological distribution cross-sectional map of the target inland waterway and visualize it.
[0088] S3. Based on the location of the target vessel, the monitoring area is dynamically divided in real time to obtain several monitoring areas, and a unique code is generated.
[0089] S4. Use lidar and total station to acquire real-time three-dimensional distribution data of each monitoring area of the target inland waterway, and calculate elevation deviation and slope deviation.
[0090] S5. Based on the elevation deviation and slope deviation, a machine learning model is used to dynamically identify over-excavated and under-excavated areas, and adjustment suggestions are generated.
[0091] S6. Collect data on medium type, water flow velocity and reference location in each monitoring area, optimize the excavation path using ant colony algorithm, generate the optimal operation plan, and display the route visually.
[0092] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.
Claims
1. A visualization-based precision excavation guidance and control system, characterized in that, include: The geological exploration imaging module uses radar detection equipment to detect the riverbed of the target inland waterway and obtain the corresponding geological distribution. The geological visualization module constructs a geological distribution cross-sectional map of the target inland waterway based on the aforementioned geological distribution and displays it visually. The regional dynamic division monitoring module divides the monitoring area into several monitoring areas in real time based on the location of the target vessel, and generates a unique code; The intelligent data acquisition and analysis module uses lidar and total station to acquire real-time three-dimensional distribution data of each monitoring area of the target inland waterway, and calculates elevation deviation and slope deviation. The intelligent excavation demand identification module dynamically identifies over-excavated and under-excavated areas based on the aforementioned elevation and slope deviations, and generates adjustment suggestions. The excavation path optimization and display module collects data on the medium type, water flow velocity, and reference location of each monitoring area, optimizes the excavation path through an ant colony algorithm, generates the optimal operation plan, and displays the route visually.
2. The visualization-based precision excavation guidance and control system as described in claim 1, characterized in that: The specific analysis method for the geological distribution is as follows: The analysis of geological distribution requires analyzing the medium type corresponding to each reflected wave and monitoring the reflection distance; The radar detection equipment is used to transmit high-frequency electromagnetic waves to the riverbed of the target inland waterway in real time, and the corresponding transmission time and frequency are recorded. At the same time, the reflection wave receiving module is used to receive several corresponding reflection waves in real time, and the reflection wave reception time, reflection wave frequency and reflection wave intensity of each reflection wave are obtained. The media type corresponding to each reflected wave is obtained by comparing the reflected wave frequency and intensity corresponding to each reflected wave with the pre-constructed correspondence between each propagation medium and the reflected wave frequency and intensity. The reception time of each reflected wave and the transmission time of the high-frequency electromagnetic wave are extracted, and the difference is calculated to obtain the reflection duration of each reflected wave. The formula is then used to... Analysis yielded the monitoring reflection distances corresponding to each reflected wave. ,in Indicates the number of the reflected wave. , Indicates the number of reflected waves. Indicates the first The reflection time corresponding to each reflected wave Indicates the first The propagation speed of the reflected wave corresponds to the medium type. This indicates the reflection time corresponding to the first reflected wave, specifically the propagation time of the reflected wave in the water. This indicates the propagation speed of the reflected wave corresponding to the medium type of the first reflected wave, specifically the propagation speed of the reflected wave in water. .
3. The visualization-based precision excavation guidance and control system as described in claim 2, characterized in that: The specific method for constructing the geological distribution cross-sectional map of the target inland waterway is as follows: The medium type and width of each reflection layer at the current location are determined based on the medium type corresponding to each reflected wave and the monitored reflection distance. A geological distribution profile map of the current location is generated based on the medium type and width of each reflective layer. The geological distribution profile map consists of several geological layers, with different geological layers corresponding to different medium types, and different medium types are represented by different colors.
4. The visualization-based precision excavation guidance and control system as described in claim 1, characterized in that: The specific method for real-time dynamic monitoring area division is as follows: The location of the target vessel is recorded as the reference position, and the monitoring range is determined based on the pre-set monitoring range setting rules. The monitoring range is then divided into several monitoring areas by gridding. The monitoring range setting rules specifically include determining the width of the monitoring range based on a pre-set monitoring width to obtain the front monitoring far line and the rear monitoring far line. Specifically, the reference position is located on the center line corresponding to the monitoring width along the river channel direction, and the monitoring range is composed of the area enclosed by the front monitoring far line, the rear monitoring far line, and the river channel boundary line.
5. The visualization-based precision excavation guidance control system as described in claim 1, characterized in that: The specific calculation method for the elevation deviation is as follows: Extract the three-dimensional distribution data of each monitoring area of the target inland waterway, evenly distribute the monitoring points in each monitoring area to obtain a number of monitoring points, obtain the actual measured elevation of each monitoring point, and at the same time obtain the design elevation of each monitoring point based on the construction plan. The elevation deviation of each monitoring point is obtained by calculating the difference between the actual measured elevation and the corresponding design elevation.
6. The visualization-based precision excavation guidance and control system as described in claim 5, characterized in that: The specific calculation method for the slope deviation is as follows: Extract the three-dimensional distribution data of each monitoring area of the target inland waterway, use the digital elevation model to obtain the actual measured slope of each monitoring point, and obtain the design slope of each monitoring point based on the construction plan. The slope deviation of each monitoring point is calculated by comparing the actual measured slope with the corresponding design slope.
7. The visualization-based precision excavation guidance and control system as described in claim 6, characterized in that: The specific method for dynamically identifying over-excavated and under-excavated areas is as follows: Extract the elevation deviation and slope deviation of each monitoring point, and calculate the elevation deviation and slope deviation of each monitoring point by taking the absolute value; The elevation deviation and slope deviation of each monitoring point are compared with the preset elevation deviation threshold and slope deviation threshold, respectively. If the elevation deviation of a monitoring point is greater than the elevation deviation threshold or the slope deviation is greater than the slope deviation threshold, the monitoring point is identified as an abnormal monitoring point. Abnormal monitoring points with positive elevation deviations are recorded as under-excavation identification points, and abnormal monitoring points with negative elevation deviations are recorded as over-excavation identification points. The number of under-excavation identification points and over-excavation identification points in each monitoring area are statistically obtained. The number of under-excavation identification points and the number of over-excavation identification points in each monitoring area are compared. If the number of under-excavation identification points in a certain monitoring area is greater than the number of over-excavation identification points, the monitoring area is identified as an under-excavation area. If the number of under-excavation identification points in a certain monitoring area is less than the number of over-excavation identification points, the monitoring area is identified as an over-excavation area.
8. The visualization-based precision excavation guidance and control system as described in claim 7, characterized in that: The specific method for generating adjustment suggestions is as follows: Areas identified as over-excavated and under-excavated will be designated as areas awaiting construction. Extract the three-dimensional distribution data of each construction area of the target inland waterway, and then obtain the design three-dimensional data of each construction area based on the construction plan. Use three-dimensional data processing software to obtain the actual monitored soil volume and design soil volume of each construction area, and then calculate the difference between the actual monitored soil volume and the design soil volume of each construction area to obtain the soil volume deviation of each construction area.
9. A visualization-based precision excavation guidance and control system as described in claim 8, characterized in that: The specific method for optimizing the excavation path is as follows: Extract the target vessel's instruction manual and historical construction data to obtain the corresponding excavation speed for each medium type, and obtain the target vessel's travel speed and power consumption under various water flow speeds. Then, construct an excavation path optimization model based on the ant colony algorithm. The coordinates of the target vessel’s current position, the coordinates of each over-excavated area, the coordinates of each under-excavated area, and the soil volume deviation of each area to be constructed are imported into the excavation path optimization model, thereby obtaining the construction time and construction power consumption corresponding to each path. Based on the analysis of construction time and power consumption for each path, the construction evaluation index of each path is obtained, and then compared. The path with the largest construction evaluation index is selected as the target excavation path.
10. A visualization-based method for precise excavation guidance and control, characterized in that: include: S1. Use radar detection equipment to detect the riverbed of the target inland waterway to obtain the corresponding geological distribution; S2. Based on the aforementioned geological distribution, construct a geological distribution cross-sectional map of the target inland waterway and visualize it. S3. Based on the location of the target vessel, the monitoring area is dynamically divided in real time to obtain several monitoring areas, and a unique code is generated; S4. Use lidar and total station to acquire real-time three-dimensional distribution data of each monitoring area of the target inland waterway, and calculate elevation deviation and slope deviation. S5. Based on the aforementioned elevation and slope deviations, a machine learning model is used to dynamically identify over-excavated and under-excavated areas, and adjustment suggestions are generated. S6. Collect data on medium type, water flow velocity and reference location in each monitoring area, optimize the excavation path using ant colony algorithm, generate the optimal operation plan, and display the route visually.