Land reclamation remote monitoring and visual early warning system

Abstract

The present application relates to the technical field of image detection, in particular to a land reclamation remote monitoring visual early warning system, which can realize the following steps through the mutual cooperation between multiple modules: obtaining the silt accumulation image and the landing splashing image of the current land reclamation in the current to-be-adjusted period, so as to identify the target landing area and the aerial particle group area; determining the current reclamation deviation degree according to the target elevation data corresponding to the center point of the target landing area and the difference between the target landing area and the preset expected landing center, as well as the preset design expected elevation; determining the current particle unevenness degree according to the distribution of the radius of the aerial particle group area; thus determining the current comprehensive risk quantization value; and performing land reclamation remote monitoring visual early warning according to the current comprehensive risk quantization value. The present application realizes the real-time monitoring of land reclamation by detecting the silt accumulation image and the landing splashing image, and improves the timeliness of land reclamation monitoring.

Description

Technical Field

[0001] This invention relates to the field of image detection technology, and more specifically to a remote monitoring and visualization early warning system for land reclamation. Background Technology

[0002] Land reclamation is a foundation treatment and land creation technology that typically involves transporting and spraying a mixture of dredged material from water bodies (such as the seabed or river channels) to a designated land area using high-pressure pumps and pipelines. After natural sedimentation and compaction, new land is formed. This technology is mainly used in port construction, land expansion, and terrain restoration projects. Its core lies in the efficient use of dredged materials to quickly create a foundation platform that meets design requirements.

[0003] In land reclamation, uniformity of the fill is often crucial for ensuring project quality and controlling costs. Uneven fill thickness or significant differences in particle size distribution can lead to uneven settlement after compaction, increasing the workload and time required for subsequent large-scale leveling or backfilling. In severe cases, it may cause safety hazards such as localized ground weakness and insufficient bearing capacity. Current technologies primarily rely on elevation measurements after reclamation for quality assessment. However, this approach often suffers from significant lag and struggles to monitor the uniformity of the fill during the reclamation process, resulting in poor timeliness of land reclamation monitoring and potentially delayed early warning systems. Summary of the Invention

[0004] To address the technical problem of poor timeliness in monitoring land reclamation, this invention proposes a remote monitoring and visualization early warning system for land reclamation.

[0005] In a first aspect, the present invention provides a remote monitoring and visualization early warning system for land reclamation, the system comprising: The image acquisition and region recognition module is used to acquire images of sediment accumulation and splashing points of the current land reclamation during the current adjustment cycle, and to identify the target landing point region from each frame of sediment accumulation image and the airborne particle group region from each frame of splashing points image. The current dredging offset determination module is used to determine the current dredging offset based on the difference between the center point of the target landing area and the preset expected landing center, as well as the difference between the target elevation data corresponding to the center point of the target landing area and the preset design expected elevation. The current particle unevenness determination module is used to determine the current particle unevenness based on the distribution of the radius of the airborne particle swarm region in all impact splash images within the current adjustment period; The current comprehensive risk quantification value determination module is used to determine the current comprehensive risk quantification value based on the elevation distribution at the current adjustment time, as well as the current degree of dredging offset and the current degree of particle unevenness. The current adjustment time is the end time of the current adjustment cycle. The monitoring and visualization early warning module is used for remote monitoring and visualization early warning of land reclamation based on the current comprehensive risk quantification value.

[0006] In conjunction with the first aspect above, in one possible implementation, determining the current reclamation offset based on the difference between the center point of the target landing area and the preset expected landing center, and the difference between the target elevation data corresponding to the center point of the target landing area and the preset design expected elevation, includes: The target reclamation operation area is divided into equal parts to obtain target sub-regions. At the time of acquisition of the sediment deposition image of the target landing point area, the elevation data corresponding to each target sub-region is obtained. The target reclamation operation area includes the target landing point area. The elevation data of the target sub-region to which the center point of the target landing area belongs, acquired at the time of acquisition of the sediment deposition image of the target landing area, is determined as the target elevation data corresponding to the center point of the target landing area. Based on the difference between the center point of the target landing area identified in each frame of sediment deposition image and the center point of the preset expected landing point, and the difference between the target elevation data corresponding to the center point of the target landing area identified in each frame of sediment deposition image and the preset design expected elevation, the effective offset factor corresponding to each frame of sediment deposition image is determined. The current displacement degree is determined based on the effective offset factor corresponding to all sediment deposition images within the current adjustment period of the current land reclamation.

[0007] In conjunction with the first aspect above, in one possible implementation, determining the effective offset factor corresponding to each frame of sediment deposition image based on the difference between the center point of the target landing area identified in each frame of sediment deposition image and the preset expected landing center, and the difference between the target elevation data corresponding to the center point of the target landing area identified in each frame of sediment deposition image and the preset design expected elevation, includes: The sediment deposition image of any frame within the current adjustment period is determined as the marked sediment deposition image. The Euclidean distance between the center point of the target landing point region in the marked sediment deposition image and the center of the preset expected landing point is determined as the position difference factor corresponding to the marked sediment deposition image. Based on the difference between the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image and the preset design expected elevation, the offset correction coefficient corresponding to the marked sediment deposition image is determined; Based on the offset correction coefficient corresponding to the marked sediment deposition image, the position difference factor corresponding to the marked sediment deposition image is corrected to obtain the effective offset factor corresponding to the marked sediment deposition image.

[0008] In conjunction with the first aspect above, in one possible implementation, determining the offset correction coefficient corresponding to the marked sediment deposition image based on the difference between the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image and the preset design expected elevation includes: If the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image is less than the preset design expected elevation, then the ratio between the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image and the preset design expected elevation is determined as the offset correction reference factor corresponding to the marked sediment deposition image, and the maximum value between the offset correction reference factor and the preset correction base coefficient is determined as the offset correction coefficient corresponding to the marked sediment deposition image. If the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image is greater than or equal to the preset design expected elevation, then the offset correction coefficient corresponding to the marked sediment deposition image is set to the preset correction coefficient.

[0009] In conjunction with the first aspect above, in one possible implementation, the step of correcting the positional difference factor corresponding to the marked sediment deposition image based on the offset correction coefficient corresponding to the marked sediment deposition image to obtain the effective offset factor corresponding to the marked sediment deposition image includes: The product of the offset correction coefficient and the position difference factor corresponding to the marked sediment deposition image is determined as the effective offset factor corresponding to the marked sediment deposition image.

[0010] In conjunction with the first aspect above, in one possible implementation, determining the current land reclamation offset degree based on the effective offset factors corresponding to all sediment deposition images within the current adjustment period includes: The mean value of the effective offset factor corresponding to all sediment deposition images within the current adjustment period of the current land reclamation is normalized to obtain the current reclamation offset degree.

[0011] In conjunction with the first aspect above, in one possible implementation, determining the current particle unevenness based on the distribution of radii of airborne particle cluster regions in all impact splash images within the current adjustment period includes: Obtain the radius of the particle swarm region representing the airborne particle swarm region in each frame of the impact splash image, and use it as the target radius corresponding to each frame of the impact splash image. The current particle unevenness is determined based on the coefficient of variation of the target radius corresponding to all splash images of the landing points within the current adjustment period, and the preset upper limit of the coefficient of variation tolerance.

[0012] In conjunction with the first aspect above, in one possible implementation, determining the current particle unevenness based on the coefficient of variation of the target radius corresponding to all splash images of the landing points within the current adjustment period, and a preset upper limit for the tolerance of the coefficient of variation, includes: If the coefficient of variation of the target radius corresponding to all splash images of the landing point in the current adjustment period is greater than or equal to the preset coefficient of variation tolerance limit, then the current particle unevenness is set to the preset maximum unevenness. If the coefficient of variation of the target radius corresponding to all splash images of the landing point in the current adjustment period is less than the preset upper limit of the coefficient of variation tolerance, then the ratio between the coefficient of variation of the target radius corresponding to all splash images of the landing point in the current adjustment period and the preset upper limit of the coefficient of variation tolerance is determined as the current degree of particle inhomogeneity.

[0013] In conjunction with the first aspect above, in one possible implementation, determining the current comprehensive risk quantification value based on the elevation distribution at the current time to be adjusted, as well as the current degree of dredging offset and the current degree of particle unevenness, includes: The target reclamation area is divided into equal parts to obtain target sub-regions, and the average of the elevation data corresponding to all target sub-regions obtained at the current adjustment time is determined as the overall representative data of the current elevation. The characterization factor for the current reclamation stage is determined based on the difference between the current overall representative elevation data and the preset minimum elevation benchmark, and the difference between the preset design expected elevation and the current overall representative elevation data. The current comprehensive risk quantification value is determined based on the current dredging stage characterization factor, the current dredging offset degree, and the current particle unevenness degree.

[0014] In conjunction with the first aspect above, in one possible implementation, the remote monitoring and visualization early warning of land reclamation based on the current comprehensive risk quantification value includes: If the current comprehensive risk quantification value is less than or equal to the preset first risk threshold, information representing low risk is generated and displayed visually. If the current comprehensive risk quantification value is greater than a preset first risk threshold, and the current comprehensive risk quantification value is less than or equal to a preset second risk threshold, then information representing the risk is generated and visualized. If the current comprehensive risk quantification value is greater than the preset second risk threshold, information representing high risk is generated and displayed visually.

[0015] Secondly, this invention provides a method for remote monitoring and visualization early warning of land reclamation implemented by a land reclamation remote monitoring and visualization early warning system, the method comprising: Acquire images of sediment accumulation and splashing points during the current land reclamation period, identify the target landing area from each sediment accumulation image, and identify the airborne particle cluster area from each splashing point image. The current degree of dredging offset is determined based on the difference between the center point of the target landing area and the preset expected landing center, as well as the difference between the target elevation data corresponding to the center point of the target landing area and the preset design expected elevation. The current degree of particle unevenness is determined based on the distribution of the radius of the airborne particle swarm region in all impact splash images within the current adjustment period; Based on the elevation distribution at the current time to be adjusted, as well as the current degree of dredged fill offset and the current degree of particle unevenness, determine the current comprehensive risk quantification value; Remote monitoring and visual early warning of land reclamation are conducted based on the current comprehensive risk quantification value.

[0016] Thirdly, a server is provided, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, enabling the device to execute the aforementioned method for remote monitoring and visualization early warning of land reclamation.

[0017] Fourthly, a computer program product is provided, comprising: computer program code, which, when run on a computer, causes the computer to execute the aforementioned method for remote monitoring and visualization of land reclamation.

[0018] Fifthly, a computer-readable storage medium is provided, which stores computer program code that, when executed on a computer, causes the computer to perform the aforementioned method for remote monitoring and visualization of land reclamation.

[0019] The present invention has the following beneficial effects: This invention discloses a remote monitoring and visualization early warning system for land reclamation. By detecting images of sediment accumulation and splashing at impact points, it achieves real-time monitoring of land reclamation, solving the technical problem of poor timeliness in land reclamation monitoring and improving its timeliness. Specifically, this invention identifies the target impact point area and the aerial particle group area by analyzing sediment accumulation and splashing images. Based on the difference between the center point of the target impact point area and the preset expected impact point center, and the difference between the target elevation data corresponding to the center point of the target impact point area and the preset design expected elevation, it quantifies the current reclamation deviation, which characterizes the position control accuracy. Based on the radius distribution of the aerial particle group area, it quantifies the current particle unevenness, which characterizes the uniformity of material particles. Combined with the elevation distribution at the current adjustment time, it obtains the current comprehensive risk quantification value. Based on the current comprehensive risk quantification value, it performs remote monitoring and visualization early warning for land reclamation, achieving real-time monitoring of land reclamation and improving its timeliness, while reducing monitoring and early warning delays to a certain extent. Attached Figure Description

[0020] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art 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.

[0021] Figure 1 This is a schematic diagram of the structure of a remote monitoring and visualization early warning system for land reclamation according to the present invention; Figure 2 This is a flowchart of a remote monitoring and visualization early warning method for land reclamation according to the present invention; Figure 3 This is a schematic diagram of the structure of a computer device according to the present invention. Detailed Implementation

[0022] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the specific implementation methods, structures, features, and effects of the technical solution proposed according to the present invention are described in detail below with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0024] Land reclamation often involves using high-pressure pumps and pipelines to pump silt and sand from the seabed, river channels, or depressions to designated land areas. After sedimentation and compaction, the land area is expanded, the site is leveled, and the terrain is restored.

[0025] In the process of dredging, in order to make the filling area uniform and reduce the amount of leveling work in the later stage, dredging is usually carried out based on preset ideal parameters. However, due to the deviation of the mud and sand landing point and the unevenness of mud and sand particles, the actual dredging process usually deviates from the ideal working conditions, resulting in uneven dredging.

[0026] These deviations often lead to uneven filling in the system. Therefore, to avoid this situation, the deviation between the actual working conditions and the ideal working conditions can be monitored, the degree of deviation can be quantified and corrected in a timely manner to avoid uneven filling.

[0027] refer to Figure 1 A schematic diagram of a remote monitoring and visualization early warning system for land reclamation according to the present invention is shown. The remote monitoring and visualization early warning system for land reclamation includes: The image acquisition and region recognition module 101 is used to acquire images of sediment accumulation and splashing points of the current land reclamation during the current adjustment period, and to identify the target landing point region from each frame of sediment accumulation image and the airborne particle group region from each frame of splashing points image.

[0028] Here, "current land reclamation" refers to ongoing land reclamation. "Current adjustment cycle" refers to the adjustment cycle for which monitoring and early warning judgments are pending, and its duration can be set according to actual conditions. In practice, monitoring and early warning judgments can be performed every minute, in which case the corresponding adjustment cycle duration can be 1 minute. In practice, land reclamation often uses high-pressure pumps and pipelines to pump sediment from the seabed, river channels, or depressions to designated land areas. After sedimentation and compaction, the land area is expanded, the site is leveled, and the terrain is restored.

[0029] Images of sediment deposition can be images of the area where the target impact point is located. Images of impact splash can be images of the area where aerial particle clusters are located. The target impact point area can be the region formed by the deposition and splash core area after the sediment stream ejected from the pipe nozzle impacts the deposition surface (ground / mud surface). The area of ​​aerial particle clusters can be the region where the sediment stream is in a free-flying or diffused state after leaving the pipe nozzle and before landing.

[0030] In practice, the target impact area, or the landing area, is often the focus of attention regarding where the sediment lands, i.e., the landing point. The airborne particle cluster area, or the airborne area, is often the focus of attention regarding how the sediment flies down, i.e., its flight pattern.

[0031] As an example, the image acquisition and region recognition module 101 can specifically implement the following steps: The first step is to use a camera to collect images of sediment accumulation and splashing at each moment during the current adjustment period of the land reclamation.

[0032] The second step is to identify the target impact area from each frame of sediment accumulation image and the airborne particle cluster area from each frame of impact splash image.

[0033] For example, for each frame of sediment deposition image, a dynamic foreground extraction algorithm based on inter-frame difference or Gaussian mixture background modeling (GMM) can be used to separate the high-speed motion characteristics of the ejected sediment from the relatively static background mud. Morphological filtering is then combined to remove splash noise and obtain the complete landing area, denoted as the target landing area. For each frame of landing splash image, an aerial particle group region can be identified based on edge detection and contour extraction algorithms. Specifically, aerial particle groups often have a significant grayscale difference from the background sky / distant scene; therefore, grayscale conversion and noise reduction can be performed first, then the edge contour of the stream can be extracted, and finally, the circumscribed ellipse can be fitted to calculate the diffusion radius.

[0034] Alternatively, neural network technology can be used to identify the target impact area and the area of ​​airborne particle clusters.

[0035] The current filling offset determination module 102 is used to determine the current filling offset based on the difference between the center point of the target landing area and the preset expected landing center, and the difference between the target elevation data corresponding to the center point of the target landing area and the preset design expected elevation.

[0036] The preset expected landing point center can be a desired sediment landing point center set based on actual conditions. For example, it can be an ideal landing point center set manually, or it can be calculated using dredging design parameters such as the initial angle of the dredging pipeline, injection pressure, and preset movement path. The preset expected landing point center can be located on the sediment accumulation image. The preset design expected elevation can be the top surface elevation that needs to be achieved upon completion.

[0037] It should be noted that during land reclamation, sediment is injected directionally into the reclamation area via pipelines. Only by injecting sediment along a specific trajectory can it fall into the predetermined area, thus achieving uniform reclamation. The greater the deviation between the sediment's landing point and the ideal predetermined landing point, the higher the probability of uneven reclamation.

[0038] As an example, determining the current fill offset may include the following steps: The first step is to divide the target reclamation area into equal parts to obtain target sub-regions, and to acquire the elevation data corresponding to each target sub-region at the time of acquiring the sediment deposition image of the target landing area.

[0039] The target reclamation area can include the target landing point area. Elevation data can be obtained using a laser rangefinder. The target sub-region can be a square with sides of 1 meter. The elevation data corresponding to the target sub-region can be equal to the height of the center point of that sub-region.

[0040] The second step is to determine the elevation data of the target sub-region to which the center point of the target landing area belongs at the time when the image of the sediment deposition in the target landing area is acquired, as the target elevation data corresponding to the center point of the target landing area.

[0041] Among them, the target elevation data corresponding to the center point of the target landing area is the elevation data of the target sub-area to which the center point of the target landing area belongs, collected at the time of collection of the target landing area.

[0042] In practice, a laser rangefinder can be used to collect elevation data of each target sub-area in the target reclamation operation area in real time.

[0043] The third step, determining the effective offset factor for each frame of sediment deposition image based on the difference between the center point of the identified target landing area in each frame and the preset expected landing center, and the difference between the target elevation data corresponding to the center point of the identified target landing area in each frame and the preset design expected elevation, may include the following sub-steps: The first sub-step is to identify any frame of sediment deposition image within the current adjustment period as the marked sediment deposition image.

[0044] The second sub-step is to determine the Euclidean distance between the center point of the target landing area in the marked sediment deposition image and the center of the preset expected landing point as the positional difference factor corresponding to the marked sediment deposition image.

[0045] It should be noted that during the dredging process, continuous dredging often forms a series of landing areas. Since the sediment concentration is usually high and uniform at the center of the landing area, the geometric center of each landing area is often the core position of sediment accumulation in that landing area within a corresponding time period. Therefore, when the actual landing area center deviates from the design center, it often leads to uneven dredging to a certain extent.

[0046] The third sub-step involves determining the offset correction coefficient corresponding to the marked sediment deposition image based on the difference between the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image and the preset design expectation elevation.

[0047] It should be noted that in the process of land reclamation, the core of uniformity of reclamation is often the consistency of elevation of the target reclamation area, and the goal is often to ensure that each target sub-area reaches the design elevation. During the reclamation process, different filling elevations often have different tolerances for the deviation of the landing point. For example, slight deviation in low-lying areas is often effective filling, while slight deviation in high-lying areas is often ineffective accumulation, and the deviation often needs to be adjusted by a correction coefficient.

[0048] For example, determining the offset correction coefficient corresponding to a marked image of sediment deposition may include the following steps: First, if the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image is less than the preset design expectation elevation, then the ratio between the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image and the preset design expectation elevation is determined as the offset correction reference factor corresponding to the marked sediment deposition image, and the maximum value between the offset correction reference factor and the preset correction base coefficient is determined as the offset correction coefficient corresponding to the marked sediment deposition image.

[0049] The preset correction base coefficient can be a base value of the offset correction coefficient set in advance according to the actual situation. It is mainly used to avoid the situation where the offset correction coefficient is close to 0 when the initial target elevation data is close to 0, so that no alarm is triggered no matter how far the deviation is. For example, the preset correction base coefficient can be 0.1.

[0050] It should be noted that when the target elevation data corresponding to the center point of the target landing area is smaller than the preset design expectation elevation, it often indicates that the area is more likely to be in a low-lying area, and the thickness that can be filled may still be large. In this case, the tolerance for landing point deviation is often higher, the ratio between the target elevation data and the aforementioned preset design expectation elevation is often smaller, and the corresponding deviation correction coefficient is often smaller.

[0051] Next, if the target elevation data corresponding to the center point of the target landing area in the above-mentioned marked sediment deposition image is greater than or equal to the preset design expected elevation, then the offset correction coefficient corresponding to the above-mentioned marked sediment deposition image is set as the preset correction coefficient.

[0052] It should be noted that the preset correction coefficient can be a correction coefficient set in advance based on the actual situation, and it can be greater than the constant 1, such as 1.2.

[0053] It should be noted that when the target elevation data corresponding to the center point of the target landing area is greater than the preset design expectation elevation, it often indicates that the current filling is more likely to be excessive. At this time, piling mud and sand here is often "adding trouble", which is an ineffective accumulation or even a negative work (it will have to be dug up later). The project risk is often greater at this time, and a larger coefficient is often needed to amplify the calculated value of the offset, making it easier for the system to issue an alarm.

[0054] The fourth sub-step involves correcting the positional difference factor corresponding to the marked sediment deposition image based on the offset correction coefficient, thereby obtaining the effective offset factor corresponding to the marked sediment deposition image.

[0055] For example, the product of the offset correction coefficient and the position difference factor corresponding to the marked sediment deposition image can be determined as the effective offset factor corresponding to the marked sediment deposition image.

[0056] The fourth step is to determine the current displacement degree of the land reclamation based on the effective offset factors corresponding to all sediment deposition images within the current adjustment period.

[0057] For example, the mean of the effective offset factors corresponding to all sediment deposition images within the current adjustment period can be normalized to obtain the current offset degree of land reclamation. Normalization can be achieved using a normalization function, such as... The normalization function performs normalization, and can be replaced with other normalization functions depending on the actual situation.

[0058] The current particle unevenness determination module 103 is used to determine the current particle unevenness based on the distribution of the radius of the airborne particle group region in all impact splash images within the current adjustment period.

[0059] It should be noted that the current offset obtained in the preceding steps represents the deviation between the dredged center and the preset center. This offset is often a potential factor leading to uneven dredged filling in the later stages due to deviations in the landing point's position. During the dredged filling process, in addition to positional deviations, the uniformity of the particle size itself is also a significant factor affecting uneven filling. Ideally, the dredged filling process should maintain a uniform mix of particles of different sizes to ensure even filling of the area. If the particle size is uneven, it often leads to uneven gravity consolidation and settlement in the later stages, resulting in uneven filling and further increasing the difficulty of subsequent leveling. The more severe the particle unevenness, the greater the probability of uneven filling.

[0060] Analysis shows that the aerial diffusion morphology of sediment jets is often significantly positively correlated with the flatness of the deposition point. When the particle size is more uniform, the settling velocity distribution tends to be more concentrated, the consistency of the aerial motion trajectory tends to be higher, and the diffusion range tends to be smaller. Conversely, when the particle size is less uniform, the difference in particle settling velocity tends to be greater, and the trajectory tends to be more dispersed.

[0061] As an example, determining the current degree of particle inhomogeneity may include the following steps: The first step is to obtain the radius of the particle swarm region in the airborne particle swarm region of each frame of the impact splash image, which is used as the target radius corresponding to each frame of the impact splash image.

[0062] The particle cluster represented by the particle cluster region is also known as a sediment flow stream. The radius of the particle cluster represented by the airborne particle cluster region can be expressed as half the average width of the airborne particle cluster region.

[0063] The second step is to determine the current degree of particle unevenness based on the coefficient of variation of the target radius corresponding to all splash images of the landing points within the current adjustment period, as well as the preset upper limit of the coefficient of variation tolerance.

[0064] The coefficient of variation can be the ratio between the standard deviation and the mean, which measures the magnitude of data volatility relative to its average level.

[0065] It should be noted that the smaller the coefficient of variation of the target radius corresponding to all splash images of landing points within the current adjustment period, the more concentrated the particle settling velocity distribution and the higher the trajectory consistency.

[0066] For example, determining the current degree of particle inhomogeneity may include the following sub-steps: The first sub-step is to set the current particle unevenness to the preset maximum unevenness if the coefficient of variation of the target radius corresponding to all the splash images of the landing points in the current adjustment period is greater than or equal to the preset coefficient of variation tolerance limit.

[0067] The preset upper limit of the coefficient of variation, also known as the maximum permissible coefficient of variation, can be determined based on industry standards, sediment material characteristics, and engineering practice experience in land reclamation projects. A value of 0.25 is recommended, but it can be adjusted according to specific engineering scenarios. It represents the upper limit of tolerance for particle size dispersion. The preset maximum degree of inhomogeneity can be set according to actual conditions to characterize the degree of particle inhomogeneity; for example, it can be 1.

[0068] It should be noted that when the coefficient of variation of the target radius corresponding to all splash images of landing points within the current adjustment period is greater than or equal to the preset upper limit of the coefficient of variation tolerance, it often indicates that the particle uniformity is often poor and there may be a significant risk of uneven packing.

[0069] The second sub-step is as follows: if the coefficient of variation of the target radius corresponding to all the splash images of the landing points in the current adjustment period is less than the preset upper limit of the coefficient of variation tolerance, then the ratio between the coefficient of variation of the target radius corresponding to all the splash images of the landing points in the current adjustment period and the preset upper limit of the coefficient of variation tolerance is determined as the current degree of particle inhomogeneity.

[0070] It should be noted that when the coefficient of variation of the target radius corresponding to all splash images of landing points within the current adjustment period is less than the preset upper limit of the coefficient of variation tolerance, it often indicates that the consistency of the diffusion radius of the sediment particle group is better, the particle uniformity is higher, and the probability of uneven filling is lower.

[0071] The current comprehensive risk quantification value determination module 104 is used to determine the current comprehensive risk quantification value based on the elevation distribution at the current time to be adjusted, as well as the current degree of dredging offset and the current degree of particle unevenness.

[0072] The current time to be adjusted can be the end time of the current adjustment period, which is the time when monitoring and early warning judgment are needed.

[0073] As an example, determining the current comprehensive risk quantification value may include the following steps: The first step is to divide the target reclamation area into equal parts to obtain target sub-regions, and then determine the average elevation data of all target sub-regions obtained at the current adjustment time as the overall representative data of the current elevation.

[0074] The second step is to determine the characterization factor of the current dredging stage based on the difference between the above-mentioned current overall elevation representative data and the preset minimum elevation benchmark, as well as the difference between the preset design expected elevation and the above-mentioned current overall elevation representative data.

[0075] The preset minimum elevation benchmark, also known as the initial elevation, can be the elevation of the original base slab before reclamation, that is, the initial ground elevation. The preset design desired elevation can be the top surface elevation that needs to be achieved upon completion.

[0076] It should be noted that when the current overall elevation data is greater than the preset design expected elevation, it often indicates that the current filling is likely to have exceeded the limit and is very likely to be in the final stage of dredging. At this time, the current dredging stage characterization factor can be set to the maximum value of the dredging stage characterization factor, such as 1.

[0077] Optionally, when the current overall elevation data is greater than the preset design expected elevation, it often indicates that the current filling is likely to be overfilled. In this case, it can also be directly judged as high risk, so as to realize remote monitoring and early warning of land reclamation.

[0078] For example, when the current overall elevation data is less than or equal to the preset design expected elevation, the formula for determining the characterization factor corresponding to the current reclamation stage can be: ; in, It is a characteristic factor of the current blowing stage. It is a function that takes the minimum value. This is the current overall representative data on elevation. It is the preset minimum elevation benchmark. H It is the preset design expectation elevation. It is an adjustment factor that is preset according to the actual situation, mainly used to prevent the denominator from being 0. For example, it can be 0.0001.

[0079] It should be noted that all variables in the embodiments of the present invention, especially the denominator, can be set with corresponding adjustment factors according to the actual situation to adjust their value range or prevent the denominator from being 0.

[0080] It should be noted that the preceding steps yielded the current degree of dredging offset caused by deviation of the landing point area, and also obtained the current degree of particle unevenness caused by overall particle unevenness. The current degree of dredging offset often reflects spatial position control during the dredging process, while the current degree of particle unevenness often reflects material property control. Both affect the uniformity of dredging, but their influence weights often differ at different stages of dredging. In the early stages of dredging, when the terrain elevation difference is large, the accuracy of the landing point is often more important. In the middle stages of dredging, as the flatness improves, particle uniformity gradually becomes more important, affecting the consistency of settlement. In the later stages, fine leveling is often required, and the importance of both is often equal. It can represent the height of the filled area, and This can represent the remaining height that needs to be filled. When The smaller, and The larger it is, the more likely it is to indicate The smaller the value, the more likely it is to indicate... The smaller the value, the more likely it is to be in the early stages of the filling process. Conversely, the larger the value, the more likely it is to be in the later stages of the filling process.

[0081] The third step is to determine the current comprehensive risk quantification value based on the above-mentioned current dredging stage characterization factors, the above-mentioned current dredging offset degree, and the above-mentioned current particle unevenness degree.

[0082] For example, the formula for determining the current comprehensive risk quantification value can be: ; ; ; in,R This is the current comprehensive risk quantification value. and They are and The weights, and . It indicates the current degree of caving offset. It represents the current degree of particle unevenness. It is a characteristic factor of the current blowing stage.

[0083] It should be noted that in the initial stage of dredging, Close to 0 Approaching 1, When the value approaches zero, the focus should be on controlling the risk of landing point deviation; in the middle stage of reclamation, Close to 0.5 Approaching 0.75, Approaching 0.25, the control weight for particle uniformity is gradually increased; in the later stages of dredging, Approaching 1, Approaching 0.5, When the value approaches 0.5, the accuracy of the landing point and the uniformity of the particles are often equally important. Therefore, when R The larger the value, the higher the overall risk of uneven filling is likely to be.

[0084] The monitoring visualization and early warning module 105 is used to conduct remote monitoring and visualization early warning of land reclamation based on the current comprehensive risk quantification value.

[0085] As an example, remote monitoring and visualization of land reclamation based on the current comprehensive risk quantification value may include the following steps: The first step is to generate information representing low risk if the current comprehensive risk quantification value is less than or equal to the preset first risk threshold, and then display it visually.

[0086] The preset first risk threshold can be a threshold set in advance based on the actual situation, such as 0.3.

[0087] The second step is to generate risk information in the representation of the risk if the current comprehensive risk quantification value is greater than the preset first risk threshold and the current comprehensive risk quantification value is less than or equal to the preset second risk threshold, and then to display the information visually.

[0088] The preset second risk threshold can be a threshold set in advance based on the actual situation, and it can be greater than the preset first risk threshold. For example, the preset second risk threshold can be 0.7.

[0089] The third step is to generate information representing high risk if the current comprehensive risk quantification value is greater than the preset second risk threshold, and then visualize the information.

[0090] Optionally, color coding can be used to indicate the risk distribution of the reclamation area, with green, yellow, and red corresponding to low, medium, and high risk levels, respectively, to visually present early warning information. For example, at low risk, the platform can only display a prompt message, which staff can continuously monitor; at medium risk, it can automatically push parameter adjustment suggestions (such as correcting pipe angles and optimizing injection pressure); at high risk, it can immediately trigger an audible and visual alarm and remotely control the reclamation equipment to suspend operations, preventing further uneven reclamation. The system can automatically record data such as early warning trigger time, risk value, and handling measures, generating visual reports to provide a basis for subsequent project optimization, achieving remote real-time monitoring and precise early warning management of land reclamation throughout the entire process.

[0091] refer to Figure 2 Based on the same inventive concept as the above-described method embodiments, the present invention provides a remote monitoring and visualization early warning method for land reclamation, comprising the following steps: Step S1: Obtain images of sediment accumulation and splashing points in the current land reclamation within the current adjustment period, and identify the target landing area from each frame of sediment accumulation image and the airborne particle cluster area from each frame of splashing points image.

[0092] Step S2: Determine the current dredging offset degree based on the difference between the center point of the target landing area and the preset expected landing center, and the difference between the target elevation data corresponding to the center point of the target landing area and the preset design expected elevation.

[0093] Step S3: Determine the current degree of particle unevenness based on the distribution of the radius of the airborne particle swarm region in all impact splash images within the current adjustment period.

[0094] Step S4: Determine the current comprehensive risk quantification value based on the elevation distribution at the current time to be adjusted, as well as the current degree of dredged fill offset and the current degree of particle unevenness.

[0095] Step S5: Conduct remote monitoring and visual early warning of land reclamation based on the current comprehensive risk quantification value.

[0096] Figure 3 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. For example, as shown... Figure 3As shown, the computer device 300 includes: a memory 301, a processor 302, and a computer program 303 stored in the memory 301 and running on the processor 302. When the processor 302 executes the computer program 303, the computer device can execute the aforementioned method for remote monitoring and visualization early warning of land reclamation.

[0097] Based on the same inventive concept as the above-described method embodiments, the present invention provides a server, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, causing the device to execute the above-described method for remote monitoring and visualization early warning of land reclamation.

[0098] Based on the same inventive concept as the above-described method embodiments, the present invention provides a computer program product comprising: computer program code, which, when run on a computer, causes the computer to execute the above-described method for remote monitoring and visualization of land reclamation.

[0099] Based on the same inventive concept as the above-described method embodiments, the present invention provides a computer-readable storage medium storing computer program code, which, when executed on a computer, causes the computer to perform the above-described method for remote monitoring and visualization of land reclamation.

[0100] In summary, this invention identifies the target landing area and the aerial particle cluster area by analyzing images of sediment accumulation and splashing. Based on the difference between the center point of the target landing area and the preset expected landing center, and the difference between the target elevation data corresponding to the center point of the target landing area and the preset design expected elevation, the current filling offset, which characterizes the position control accuracy, is quantified. Based on the radius distribution of the aerial particle cluster area, the current particle unevenness, which characterizes the uniformity of material particles, is quantified. Combined with the elevation distribution at the current adjustment time, the current comprehensive risk quantification value is obtained. Based on the current comprehensive risk quantification value, remote monitoring and visualization early warning of land filling is performed, realizing real-time monitoring of land filling and improving the timeliness of land filling monitoring, thus reducing monitoring and early warning delays to a certain extent.

[0101] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A remote monitoring and visualization early warning system for land reclamation, characterized in that, The system includes: The image acquisition and region recognition module is used to acquire images of sediment accumulation and splashing points of the current land reclamation during the current adjustment cycle, and to identify the target landing point region from each frame of sediment accumulation image and the airborne particle group region from each frame of splashing points image. The current dredging offset determination module is used to determine the current dredging offset based on the difference between the center point of the target landing area and the preset expected landing center, as well as the difference between the target elevation data corresponding to the center point of the target landing area and the preset design expected elevation. The current particle unevenness determination module is used to determine the current particle unevenness based on the distribution of the radius of the airborne particle swarm region in all impact splash images within the current adjustment period; The current comprehensive risk quantification value determination module is used to determine the current comprehensive risk quantification value based on the elevation distribution at the current adjustment time, as well as the current degree of dredging offset and the current degree of particle unevenness. The current adjustment time is the end time of the current adjustment cycle. The monitoring and visualization early warning module is used for remote monitoring and visualization early warning of land reclamation based on the current comprehensive risk quantification value.

2. The land reclamation remote monitoring and visualization early warning system according to claim 1, characterized in that, The determination of the current dredging offset based on the difference between the center point of the target landing area and the preset expected landing center, and the difference between the target elevation data corresponding to the center point of the target landing area and the preset design expected elevation, includes: The target reclamation operation area is divided into equal parts to obtain target sub-regions. At the time of acquisition of the sediment deposition image of the target landing point area, the elevation data corresponding to each target sub-region is obtained. The target reclamation operation area includes the target landing point area. The elevation data of the target sub-region to which the center point of the target landing area belongs, acquired at the time of acquisition of the sediment deposition image of the target landing area, is determined as the target elevation data corresponding to the center point of the target landing area. Based on the difference between the center point of the target landing area identified in each frame of sediment deposition image and the center point of the preset expected landing point, and the difference between the target elevation data corresponding to the center point of the target landing area identified in each frame of sediment deposition image and the preset design expected elevation, the effective offset factor corresponding to each frame of sediment deposition image is determined. The current displacement degree is determined based on the effective offset factor corresponding to all sediment deposition images within the current adjustment period of the current land reclamation.

3. The land reclamation remote monitoring and visualization early warning system according to claim 2, characterized in that, The determination of the effective offset factor for each frame of sediment deposition image based on the difference between the center point of the target landing area identified in each frame of sediment deposition image and the preset expected landing center, and the difference between the target elevation data corresponding to the center point of the target landing area identified in each frame of sediment deposition image and the preset design expected elevation, includes: The sediment deposition image of any frame within the current adjustment period is determined as the marked sediment deposition image. The Euclidean distance between the center point of the target landing point region in the marked sediment deposition image and the center of the preset expected landing point is determined as the position difference factor corresponding to the marked sediment deposition image. Based on the difference between the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image and the preset design expected elevation, the offset correction coefficient corresponding to the marked sediment deposition image is determined; Based on the offset correction coefficient corresponding to the marked sediment deposition image, the position difference factor corresponding to the marked sediment deposition image is corrected to obtain the effective offset factor corresponding to the marked sediment deposition image.

4. The land reclamation remote monitoring and visualization early warning system according to claim 3, characterized in that, The step of determining the offset correction coefficient corresponding to the marked sediment deposition image based on the difference between the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image and the preset design expected elevation includes: If the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image is less than the preset design expected elevation, then the ratio between the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image and the preset design expected elevation is determined as the offset correction reference factor corresponding to the marked sediment deposition image, and the maximum value between the offset correction reference factor and the preset correction base coefficient is determined as the offset correction coefficient corresponding to the marked sediment deposition image. If the target elevation data corresponding to the center point of the target landing area in the marked sediment deposition image is greater than or equal to the preset design expected elevation, then the offset correction coefficient corresponding to the marked sediment deposition image is set to the preset correction coefficient.

5. The land reclamation remote monitoring and visualization early warning system according to claim 3, characterized in that, The step of correcting the positional difference factor corresponding to the marked sediment deposition image based on the offset correction coefficient to obtain the effective offset factor corresponding to the marked sediment deposition image includes: The product of the offset correction coefficient and the position difference factor corresponding to the marked sediment deposition image is determined as the effective offset factor corresponding to the marked sediment deposition image.

6. The land reclamation remote monitoring and visualization early warning system according to claim 2, characterized in that, The step of determining the current dredging offset degree based on the effective offset factors corresponding to all sediment deposition images within the current adjustment period includes: The mean value of the effective offset factor corresponding to all sediment deposition images within the current adjustment period of the current land reclamation is normalized to obtain the current reclamation offset degree.

7. The land reclamation remote monitoring and visualization early warning system according to claim 1, characterized in that, The step of determining the current degree of particle unevenness based on the distribution of radii of airborne particle cluster regions in all impact splash images within the current adjustment period includes: Obtain the radius of the particle swarm region representing the airborne particle swarm region in each frame of the impact splash image, and use it as the target radius corresponding to each frame of the impact splash image. The current particle unevenness is determined based on the coefficient of variation of the target radius corresponding to all splash images of the landing points within the current adjustment period, and the preset upper limit of the coefficient of variation tolerance.

8. The land reclamation remote monitoring and visualization early warning system according to claim 7, characterized in that, The step of determining the current particle unevenness based on the coefficient of variation of the target radius corresponding to all splash images of the landing points within the current adjustment period, and a preset upper limit for the tolerance of the coefficient of variation, includes: If the coefficient of variation of the target radius corresponding to all splash images of the landing point in the current adjustment period is greater than or equal to the preset coefficient of variation tolerance limit, then the current particle unevenness is set to the preset maximum unevenness. If the coefficient of variation of the target radius corresponding to all splash images of the landing point in the current adjustment period is less than the preset upper limit of the coefficient of variation tolerance, then the ratio between the coefficient of variation of the target radius corresponding to all splash images of the landing point in the current adjustment period and the preset upper limit of the coefficient of variation tolerance is determined as the current degree of particle inhomogeneity.

9. The land reclamation remote monitoring and visualization early warning system according to claim 1, characterized in that, The determination of the current comprehensive risk quantification value based on the current elevation distribution at the time of adjustment, as well as the current degree of dredged fill offset and the current degree of particle unevenness, includes: The target reclamation area is divided into equal parts to obtain target sub-regions, and the average of the elevation data corresponding to all target sub-regions obtained at the current adjustment time is determined as the overall representative data of the current elevation. The characterization factor for the current reclamation stage is determined based on the difference between the current overall representative elevation data and the preset minimum elevation benchmark, and the difference between the preset design expected elevation and the current overall representative elevation data. The current comprehensive risk quantification value is determined based on the current dredging stage characterization factor, the current dredging offset degree, and the current particle unevenness degree.

10. A remote monitoring and visualization early warning system for land reclamation according to claim 1, characterized in that, The remote monitoring and visualization early warning system for land reclamation based on the current comprehensive risk quantification value includes: If the current comprehensive risk quantification value is less than or equal to the preset first risk threshold, information representing low risk is generated and displayed visually. If the current comprehensive risk quantification value is greater than a preset first risk threshold, and the current comprehensive risk quantification value is less than or equal to a preset second risk threshold, then information representing the risk is generated and visualized. If the current comprehensive risk quantification value is greater than the preset second risk threshold, information representing high risk is generated and displayed visually.

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