Intelligent ship segmentation site visual management system

Abstract

The invention provides an intelligent ship segmented site visual management system, and relates to the field of ship construction digital management. The intelligent ship segmented site visual management system comprises a site grid model module, a site integration model module, a segmented construction period tracking module and a visual decision module: the site grid model module is used for dividing a ship segmented storage site into honeycomb hexagonal grid units, and identifying each grid through a unique code; precise binding of the segments and the grids is realized; and the site integration model module is used for fusing the plant BIM model, the high-precision map and the real-time traffic data, constructing a plant-level three-dimensional map and dynamically optimizing a segmented lightering path based on the real-time data. Through the site grid model module, the site integration model module and the segment construction period tracking module, the problems that traditional segments are not easy to search, lack of planning and difficult to lighten, and segments are easy to retain and the site utilization rate is low due to the fact that the segments are represented by notes are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital management of shipbuilding, in particular to an intelligent ship segment site visual management system. BACKGROUND

[0002] Ship segment construction technology is an important process innovation in modern shipbuilding industry, which divides the whole ship into several modular segments, which are built in parallel in the workshop, and finally assembled and folded by large lifting equipment. This construction method not only greatly improves the production efficiency, but also optimizes the resource utilization, and becomes the mainstream method of large ship manufacturing today.

[0003] The segment is a local structure that makes up the hull, which is large in volume, heavy in weight and irregular in shape, and needs a giant barge for transportation, with a single barge transportation cost of about 25,000 yuan.

[0004] At present, most domestic shipbuilding enterprises still use old methods for segment storage management, using notes to represent hull segments and using note boards to directly transport segments. This traditional management method has the following problems:

[0005] 1. Large site, many segments, and segments are not easy to find, requiring the use of drones, intercoms and manual exploration, resulting in high labor and capital costs.

[0006] 2. Lack of planning of barge transportation routes, barge transportation difficulties, and detours, using note boards to directly transport segments, with an average of 10 additional barge transports per week, increasing transportation costs and carbon emissions.

[0007] 3. Limited storage space, lack of reminders for expired segments, and segments are prone to be stranded, using notes to represent segments, which is a single form, resulting in serious segment retention, low site utilization, and economic losses.

[0008] Therefore, in view of the current pain points of shipbuilding enterprises in segment storage management, the present application provides an intelligent ship segment site visual management system. SUMMARY

[0009] (I) Technical problems solved

[0010] In view of the deficiencies of the prior art, the present application provides an intelligent ship segment site visual management system, which solves the problems raised in the above background art.

[0011] (II) Technical solutions

[0012] To achieve the above purpose, the present application is implemented by the following technical solutions: an intelligent ship segment site visual management system, comprising a site grid model module, a site integration model module, a segment duration tracking module and a visual decision module:

[0013] The site grid model module is used to divide the ship section storage site into honeycomb hexagonal grid units and identify each grid with a unique code to achieve accurate binding between the section and the grid;

[0014] The site integration model module integrates the factory BIM model, high-precision maps and real-time traffic data to build a three-dimensional map of the factory area and dynamically optimize the segmented barge route based on real-time data;

[0015] The segmented construction period tracking module connects to the MES system to collect segmented construction progress data, monitors the construction period status in real time through a three-color early warning mechanism, and links with the resource scheduling engine to generate adjustment plans;

[0016] The visualization decision module integrates the above three modules, renders the three-dimensional scene through the WebGL engine, and provides a three-dimensional visualization interactive interface for the web and mobile terminals.

[0017] Preferably, the site grid model module includes:

[0018] Grid division unit, using hexagonal honeycomb grid to cover the entire site, each grid is assigned a unique ID code;

[0019] The segment binding unit associates the size, weight, and process stage information of the segment with the grid it belongs to through RFID or QR code tags;

[0020] Intelligent retrieval unit supports multi-condition combination query, including segment number, process status, and stacking time;

[0021] Real-time positioning unit, based on UWB technology to achieve dynamic update of segmented positions.

[0022] Preferably, the site integration model module includes:

[0023] Multi-level-of-detail modeling units enable stepless scaling at the plant level, site level, and equipment level;

[0024] Traffic sensing unit, which embeds real-time traffic data collection nodes in the topological network diagram, collects vehicle locations in real time through RFID and cameras, and dynamically avoids congested areas;

[0025] The dynamic path planning engine introduces a dynamic obstacle avoidance algorithm. When a temporary obstacle is detected, the path is replanned in real time and the detour time cost is calculated.

[0026] Preferably, the segmented duration tracking module includes:

[0027] Data collection unit, connected to the MES system to obtain the planned construction period and actual progress of each section;

[0028] The three-color early warning unit predicts the total construction period deviation rate based on Monte Carlo simulation. When the deviation rate is ≥10%, a three-level early warning is triggered, divided into blue (normal), yellow (halfway through the construction period), and red (serious overdue) according to the degree of delay;

[0029] Resource allocation unit, including adding work teams, adjusting welding sequence or calling prefabricated parts inventory.

[0030] Preferably, the visualization decision module,

[0031] Adopting B / S architecture, rendering 3D scenes based on WebGL, and supporting direct browser access;

[0032] Integrated development of multi-viewport comparison mode to simultaneously display the design model, actual model and deviation analysis results;

[0033] Provides preset observation points for typical process perspectives such as lifting and welding.

[0034] Preferably, the encoding method of the grid division unit includes:

[0035] Establish a two-dimensional coordinate system with the southwest corner of the site as the origin;

[0036] Adopt the three-part coding of "row number-column number-level";

[0037] The spatial hashing algorithm is used to quickly map the grid ID to the segmented object.

[0038] Preferably, the dynamic path planning engine includes:

[0039] The path cost calculation unit comprehensively considers factors such as path length, number of turns, and ground load-bearing grade to generate a multi-objective optimization scoring function: f(n) = α × distance cost + β × turn cost + γ × load-bearing cost, where α, β, and γ are adjustable weight coefficients.

[0040] The real-time update unit refreshes the path planning results every 30 seconds and automatically triggers full path recalculation when it detects that the path interruption time exceeds 5 minutes.

[0041] Preferably, the traffic sensing unit,

[0042] Multi-line lidar scanning is used to generate three-dimensional point cloud data, which is then aligned with the BIM model in real time through the ICP algorithm to construct an obstacle map.

[0043] (3) Beneficial effects

[0044] The present invention provides an intelligent ship segmentation site visualization management system with the following features:

[0045] Beneficial effects:

[0046] 1, The present application realizes segmented accurate positioning and rapid retrieval through honeycomb hexagonal grid coding, combines UWB real-time positioning and space hash algorithm to improve site utilization; based on BIM and laser radar fusion to build a three-dimensional dynamic map, realizes real-time obstacle avoidance and re-planning of barge transportation path through multi-target path scoring function, reduces invalid transportation; integrates MES system data and adopts three-color early warning mechanism (red / yellow / blue) to monitor construction period deviation, triggers automatic resource allocation scheme (such as increasing teams, adjusting welding sequence), shortens construction period recovery time. The system supports design-actual progress comparison through WebGL multi-viewport visualization, finally realizes intelligentization, collaboration and data driving of shipyard segmented management whole process, and comprehensively improves production efficiency and site utilization.

[0047] 2, The present application can well solve the problems of traditional segmentation, difficult to find, using note board to directly barge transportation, lack of planning, barge transportation difficulty and using note to represent segmentation, segmentation easy to stay, low site utilization through three core modules of site grid model module, site integration model module and segmented construction period tracking module. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 is the component block diagram of the present application;

[0049] Figure 2 is the site grid model module effect diagram of the present application;

[0050] Figure 3 is the site integration model module effect diagram of the present application;

[0051] Figure 4 is the segmented construction period tracking module effect diagram of the present application. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0053] Embodiment:

[0054] As Figure 1-4As shown, an embodiment of the present invention provides an intelligent ship segment site visualization management system, comprising a site grid model module, a site integration model module, a segment duration tracking module, and a visualization decision module. The site grid model module is used to divide the ship segment storage site into honeycomb hexagonal grid cells and uniquely identify each grid with a unique code, enabling precise binding between segments, real-time monitoring of segment placement, and easy segment search. The site integration model module integrates the plant site BIM model, high-precision maps, and real-time traffic data to construct a plant-level three-dimensional map. It dynamically optimizes segment transfer routes based on real-time data, reducing the number and distance of transfers and improving transportation efficiency. The segment duration tracking module integrates the MES system to collect segment construction progress data, monitors the construction status in real time through a three-color early warning mechanism, and links with the resource scheduling engine to generate adjustment plans, thereby improving site utilization, enhancing production efficiency, and increasing capacity. The visualization decision module integrates the site grid model module, the site integration model module, and the segment duration tracking module. Using the WebGL engine to render a three-dimensional scene, it provides a three-dimensional visualization interactive interface for web and mobile devices, enhancing management collaboration.

[0055] The site grid model module uses honeycomb grids for precise positioning, avoiding the space waste of traditional rectangular grids, achieving a compact layout of segmented storage, and improving site utilization. Operators can query the segmented location in real time through the system, reducing manual inspection time and achieving rapid search and scheduling.

[0056] The site integration model module integrates 3D maps, BIM models, high-precision maps and real-time traffic data. The system automatically identifies road congestion or equipment occupancy in the factory area, generates the optimal route for segmented transfer, and reduces transfer costs. It also reduces ineffective transportation mileage and improves transportation efficiency through dynamic obstacle avoidance and route optimization.

[0057] The segmented construction period tracking module can monitor the construction period in real time to ensure production progress. Based on the MES system data, it uses the three colors of "red, yellow and blue" to identify the risk of construction period delay (red for serious delay, yellow for warning, and blue for normal), helping managers to quickly locate the problem segment; when the segmented construction period warning is triggered, the system links the resource scheduling engine and recommends adjustment plans (such as increasing manpower or prioritizing site allocation) to shorten the recovery time of construction period deviation and improve production efficiency.

[0058] The site grid model module includes a grid division unit, a segment binding unit, an intelligent retrieval unit, and a real-time positioning unit. The grid division unit uses a hexagonal honeycomb grid to cover the entire site, and each grid is assigned a unique ID code. Compared with traditional rectangular grids, hexagonal grids can reduce gap waste and improve site utilization, making them particularly suitable for storing irregularly shaped segments. The grid division unit encoding method includes establishing a two-dimensional coordinate system with the southwest corner of the site as the origin, using a three-segment encoding method of "row number-column number-level", and realizing a fast mapping of grid IDs and segment objects through a spatial hash algorithm. The hash algorithm is used to establish key-value pairs between grid IDs and segment objects, reducing the query time complexity and achieving fast response even at a scale of 10,000 grids.

[0059] The use of a three-segment encoding of "row number-column number-level" not only meets the need for unique identification, but also facilitates rapid manual identification. The "level" field enables three-dimensional stacking management (such as distinguishing different heights when stacking in sections), avoiding the limitations of traditional two-dimensional coding.

[0060] The shipyard is divided into sections and fully covered with a hexagonal grid to generate multiple grid units. The southwest corner of the site is the origin (coordinate (0,0)), the east is the positive direction of the X axis, and the north is the positive direction of the Y axis. The grid code of the 3rd row, 5th column, and 1st layer is "R3-C5-L1". The code is mapped to the memory address through the spatial hash algorithm.

[0061] The segment binding unit uses RFID or QR code tags to associate the size, weight, and process stage of the segment with the grid it is located in. When the segment is hoisted, the QR code on the segment is scanned with a handheld terminal to bind it to the grid.

[0062] The intelligent retrieval unit supports multi-condition combination queries, including segment number, process status, and stacking duration. The real-time positioning unit dynamically updates segment locations based on UWB technology. Using ultra-wideband (UWB) technology, it achieves high-precision dynamic tracking of ship segments and works in conjunction with the site grid model module to ensure the real-time and accuracy of segment location information. Users enter query conditions into the intelligent retrieval unit, which displays the grid in which they are located. Combined with UWB positioning, UWB tags are installed on the segment transport carts, automatically updating location data and minimizing positioning errors.

[0063] The site integration model module includes a multi-level-of-detail modeling unit, a traffic perception unit, and a dynamic path planning engine. The multi-level-of-detail modeling unit enables stepless scaling at the factory level, site level, and equipment level. A real-scene model is generated through oblique drone photography and semantically matched with the BIM model established in Revit. The traffic perception unit embeds real-time traffic data collection nodes in the topological network diagram, collects vehicle positions in real time through RFID and cameras, and dynamically avoids congested areas. The traffic perception unit uses multi-line lidar scanning to generate three-dimensional point cloud data, which is aligned with the BIM model in real time through the ICP algorithm to construct an obstacle map. The segmented yard is scanned for point clouds (using the Velodyne VLP-16 lidar), and aligned with the BIM through the ICP algorithm, resulting in a small alignment error.

[0064] The dynamic path planning engine incorporates a dynamic obstacle avoidance algorithm. When temporary obstacles are detected, the route is replanned in real time, and the detour time cost is calculated. The dynamic path planning engine includes a path cost calculation unit that comprehensively considers path length, number of turns, and ground load-bearing grade to generate a multi-objective optimization scoring function: f(n) = α × distance cost + β × turn cost + γ × load-bearing cost, where α, β, and γ are adjustable weight coefficients. A real-time update unit refreshes the path planning results every 30 seconds and automatically triggers full path recalculation if a path interruption lasts for more than 5 minutes.

[0065] Path cost calculation: Set weights α = 0.6 (distance), β = 0.2 (turns), and γ = 0.2 (load bearing) to score the barge path:

[0066] Path A: distance 120m, 3 turns, ground load-bearing grade B → f(n) = 0.6 × 120 + 0.2 × 3 × 10 + 0.2 × 20 = 92

[0067] Path B: Distance 150m, 1 turn, Ground load-bearing grade A → f(n) = 0.6 × 150 + 0.2 × 1 × 10 + 0.2 × 10 = 94

[0068] The system gives priority to path A.

[0069] When the lidar detects temporary piles of objects on path A, the system generates a detour path C (f(n) = 89) within 30 seconds and sends it to the AGV controller via the 5G network to achieve real-time obstacle avoidance.

[0070] The segmented duration tracking module includes a data acquisition unit, a three-color early warning unit, and a resource allocation unit. The data acquisition unit connects to the MES system to obtain segmented planned durations and actual progress. The three-color early warning unit uses Monte Carlo simulation to predict the total duration deviation rate. When the deviation rate is ≥10%, a three-level early warning is triggered, categorized by the degree of delay as blue (normal), yellow (halfway through the deadline), and red (severely overdue). The resource allocation unit includes dispatching additional teams, adjusting welding sequences, or accessing prefabricated parts inventory.

[0071] The planned construction period for a certain section is 60 days. The MES reports the current progress:

[0072] On the 30th day, the actual completion rate was 40% → deviation rate = (40-50) / 50 = -20% → yellow warning was triggered (half of the construction period was completed).

[0073] On the 50th day, the actual completion rate was 65% → deviation rate = (65-83) / 83 = -22% → a red alert was triggered, and the system suggested: adding 2 welding teams or adjusting the welding sequence (giving priority to completing the critical path segmentation).

[0074] The Visual Decision Module utilizes a client / server architecture, rendering 3D scenes based on WebGL. It supports direct browser access, builds backend services, and implements browser-side 3D rendering on the front end. It supports plugin-free access on mainstream browsers like Chrome and Edge. The module also integrates a multi-viewport comparison mode, allowing for simultaneous display of the design model, actual model, and deviation analysis results. The interface is divided into three independent viewports to showcase the analysis results. The module also provides preset observation points for typical process perspectives, such as lifting and welding.

[0075] In summary, the present invention uses honeycomb hexagonal grid coding to achieve precise segment positioning and rapid retrieval, and combines UWB real-time positioning and spatial hashing algorithms to improve site utilization; constructs a three-dimensional dynamic map based on the fusion of BIM and lidar, and realizes real-time obstacle avoidance and re-planning of the barge path through a multi-target path scoring function, reducing ineffective transportation; integrates MES system data and adopts a three-color early warning mechanism (red / yellow / blue) to monitor construction period deviations, triggering automatic resource allocation plans (such as adding teams, adjusting welding sequences), and shortening construction period recovery time. The system supports design-actual progress comparison through WebGL multi-viewport visualization, and ultimately realizes the intelligence, collaboration and data-driven management of the entire process of shipyard segmentation, comprehensively improving production efficiency and site utilization. The present invention uses the three core modules of site grid model module, site integration model module, and segmentation construction period tracking module to effectively solve the problems of traditional segmentation that is difficult to find, direct bargeing of segments using sticky notes, lack of planning, difficulty in bargeing, and easy retention of segments using sticky notes to represent segments, and low site utilization.

[0076] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent ship segment site visualization management system, comprising a site grid model module, a site integration model module, a segment duration tracking module, and a visualization decision module, characterized by: The site grid model module is used to divide the ship section storage site into honeycomb hexagonal grid units and identify each grid with a unique code to achieve accurate binding between the section and the grid; The site integration model module integrates the factory BIM model, high-precision maps and real-time traffic data to build a three-dimensional map of the factory area and dynamically optimize the segmented barge route based on real-time data; The segmented construction period tracking module connects to the MES system to collect segmented construction progress data, monitors the construction period status in real time through a three-color early warning mechanism, and links with the resource scheduling engine to generate adjustment plans; The visualization decision module integrates the above three modules, renders the three-dimensional scene through the WebGL engine, and provides a three-dimensional visualization interactive interface for the web and mobile terminals.

2. The intelligent ship segmentation site visualization management system according to claim 1, characterized in that: The site grid model module includes: Grid division unit, using hexagonal honeycomb grid to cover the entire site, each grid is assigned a unique ID code; The segment binding unit associates the size, weight, and process stage information of the segment with the grid it belongs to through RFID or QR code tags; Intelligent retrieval unit supports multi-condition combination query, including segment number, process status, and stacking time; Real-time positioning unit, based on UWB technology to achieve dynamic update of segmented positions.

3. The intelligent ship segmentation site visualization management system according to claim 2, characterized in that: The site integration model module includes: Multi-level-of-detail modeling units enable stepless scaling at the plant level, site level, and equipment level; Traffic sensing unit, which embeds real-time traffic data collection nodes in the topological network diagram, collects vehicle locations in real time through RFID and cameras, and dynamically avoids congested areas; The dynamic path planning engine introduces a dynamic obstacle avoidance algorithm. When a temporary obstacle is detected, the path is replanned in real time and the detour time cost is calculated.

4. The intelligent ship segmentation site visualization management system according to claim 3, characterized in that: The segmented duration tracking module includes: Data collection unit, connected to the MES system to obtain the planned construction period and actual progress of each section; The three-color early warning unit predicts the total construction period deviation rate based on Monte Carlo simulation. When the deviation rate is ≥10%, a three-level early warning is triggered, divided into blue (normal), yellow (halfway through the construction period), and red (serious overdue) according to the degree of delay; Resource allocation unit, including adding work teams, adjusting welding sequence or calling prefabricated parts inventory.

5. The intelligent ship segmentation site visualization management system according to claim 4 is characterized by: The visualization decision module, Adopting B / S architecture, rendering 3D scenes based on WebGL, and supporting direct browser access; Integrated development of multi-viewport comparison mode to simultaneously display the design model, actual model and deviation analysis results; Provides preset observation points for typical process perspectives such as lifting and welding.

6. The intelligent ship segmentation site visualization management system according to claim 5, characterized in that: The encoding method of the grid division unit includes: Establish a two-dimensional coordinate system with the southwest corner of the site as the origin; Use "row number-column number-level" three-part coding; The spatial hashing algorithm is used to quickly map the grid ID to the segmented object.

7. The intelligent ship segmentation site visualization management system according to claim 6, characterized in that: The dynamic path planning engine includes: The path cost calculation unit comprehensively considers factors such as path length, number of turns, and ground load-bearing grade to generate a multi-objective optimization scoring function: f(n) = α × distance cost + β × turn cost + γ × load-bearing cost, where α, β, and γ are adjustable weight coefficients. The real-time update unit refreshes the path planning results every 30 seconds and automatically triggers full path recalculation when it detects that the path interruption time exceeds 5 minutes.

8. The intelligent ship segmentation site visualization management system according to claim 3, characterized in that: The traffic sensing unit, Multi-line lidar scanning is used to generate three-dimensional point cloud data, which is then aligned with the BIM model in real time through the ICP algorithm to construct an obstacle map.

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