A cable laying path planning and multi-target collaborative construction management platform

Abstract

The application discloses a cable laying path planning and multi-target cooperative construction management platform and belongs to the technical field of cable engineering construction management. The platform comprises a data modeling and storage module, a core calculation and decision module and an application and display module, and comprises the following steps: firstly, a dynamic multi-layer-state grid model is constructed; the model uniformly integrates an L1 static geometric layer of a path, an L2 engineering physical cost layer and an L3 time-varying management cost layer. In the construction process, the DCCP module dynamically monitors real-time physical parameters of an L4 layer, and when a deviation is detected, automatically carries out causal deduction, and quantitatively propagates the physical deviation to the chain change of the L3 layer management cost. The application solves the technical problem that a static planning cannot respond to dynamic disturbance, and realizes quantitative evaluation of construction risks and data-driven cooperative decision by dynamically associating physical events and management costs.

Description

Technical Field

[0001] This invention relates to the field of cable engineering construction management technology, specifically to a cable laying path planning and multi-objective collaborative construction management platform. Background Technology

[0002] Cable laying is a critical engineering task in the construction of large infrastructure or complex factories. Existing technical solutions typically rely on Building Information Modeling (BIM) or Computer-Aided Design (CAD) software to perform static path planning before construction begins. These planning methods can determine an initial path that avoids physical interference based on a three-dimensional geometric model. However, the construction site is a dynamic and changing environment, and factors such as the progress of other disciplines, the construction of temporary facilities, or unforeseen obstacles often render the planned path infeasible or no longer the optimal choice in actual execution.

[0003] Furthermore, existing technologies often treat physical constraints and management objectives during construction in a fragmented manner. For example, when physical anomalies such as excessive cable tension occur during laying, on-site personnel often rely on experience to respond, lacking a mechanism to dynamically and quantitatively transmit the consequences of this physical event to its impact on work hours, subsequent process coordination, and total project cost. Decision-makers cannot clearly foresee the chain reaction of management costs that a single on-site operational adjustment will trigger.

[0004] Therefore, existing technologies generally suffer from a disconnect between planning and reality, and an inability to dynamically correlate physical events with management costs, resulting in low efficiency in construction collaboration and a lack of objective data support for decision-making when dealing with emergencies. Summary of the Invention

[0005] The technical problem this invention aims to solve is that existing cable laying path planning methods are usually statically generated before construction begins, making it difficult to respond to changes in the physical environment and resource conflicts that occur during construction. They also lack a mechanism to dynamically quantify on-site physical events into management cost consequences, leading to decision-making delays and cost overruns.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] The first aspect of this invention provides a cable laying path planning and multi-objective collaborative construction management platform. This platform constructs a unified dynamic multi-layer-state grid model to uniformly model the static geometric constraints, engineering physical constraints, and dynamic time-varying management constraints in the cable laying problem. Based on this model, a dynamic causal propagation mechanism is established from L4-level physical events on site to L3-level management cost consequences, enabling real-time quantitative assessment of construction disturbances and providing managers with clear, data-driven collaborative decision-making basis.

[0008] In one specific implementation, the platform includes: a data modeling and storage module, a core computing and decision-making module, and an application and display module.

[0009] The data modeling and storage module is used to construct a dynamic multi-layered state-grid model. This model represents the construction environment in graph form, where path "edges" are key units carrying multi-dimensional information. The attributes of an "edge" are organized in at least three logical data layers:

[0010] The L1 static geometry layer defines the fixed spatial properties of the "edges", such as path length and curvature radius.

[0011] The L2 engineering physical cost layer defines the engineering constraint costs related to "edges" and determined by physical specifications, such as the planning tension cost calculated based on the maximum allowable tension and safety margin. And the side pressure cost calculated based on the minimum bending radius. .

[0012] The L3 time-varying cost management layer defines costs related to construction sequence and resource allocation, with time dependence as its key characteristic. This layer includes labor costs. and occupancy costs Among them, the cost of occupation It is a time function whose value is high cost within a specific time window (e.g., when other processes occupy the path) and low cost at other times.

[0013] The core computation and decision-making module is the core of realizing dynamic decision-making. This module includes a path optimization solver, a DCCP module, and a dynamic replanning unit.

[0014] During the initial planning phase, the path optimization solver calculates an initial optimal path with the lowest overall cost based on the dynamic multi-layered state grid model. .

[0015] The DCCP module acts as a bridge connecting the physical world and the management model. During the construction execution phase, this module receives dynamic data from Layer 4 in real time, such as data about a specific "edge" detected by sensors. Real-time tension on When the real-time value is detected to match the planned value stored in the L2 layer... deviation When the preset threshold is exceeded, that is:

[0016] ;

[0017] The DCCP module triggers a causal deduction. Based on preset engineering rules, this deduction converts physical deviations (excessive tension) into management consequences (reducing construction speed to ensure safety), thereby calculating an increase in working hours. The module then propagates this increase in working time to the initial optimal path. All subsequent "edges" in the middle Planned construction start time This creates a chain reaction of delays:

[0018] ;

[0019] Based on the updated start time The DCCP module reassesses the cost of these subsequent "edges". This accurately translates a local physical deviation into an impact on the entire L3 time-varying management cost layer. The dynamic replanning unit is triggered after the DCCP module completes the model cost update. This unit performs two parallel computational tasks: one is to recalculate and continue executing the original initial optimal path based on the updated cost model. The required total cost; secondly, calling the path optimization solver, using the current construction location and time as a new starting point, to re-optimize on the updated cost model and obtain an emergency path. And its total cost. These two cost values ​​are encapsulated into a decision set.

[0020] The application and display module is used to visualize the decision set, for example, by displaying the quantified costs and path maps of two options side by side on a collaborative management interface, so that managers can make the final decision.

[0021] A second aspect of this invention provides a method for cable laying path planning and multi-objective collaborative construction management, which realizes the functions of the aforementioned platform. The method includes the following steps:

[0022] First, a dynamic multi-layered state-grid model is constructed, in which the path "edges" include an L1 static geometry layer, an L2 engineering physical cost layer, and an L3 time-varying management cost layer.

[0023] Secondly, an initial optimal path is calculated based on this model.

[0024] During construction, real-time physical parameters at layer L4 are dynamically monitored. When a deviation is detected between these parameters and the planned values ​​at layer L2, a causal propagation mechanism is triggered. This mechanism first converts the physical deviation into an increase in labor costs, then propagates this increase to a chain of delays in the planned start times of subsequent path "edges," and reassesses the occupancy costs of subsequent path "edges" based on the delayed times, ultimately completing the update of the time-varying management cost layer at layer L3.

[0025] After the L3 layer cost data is updated, dynamic replanning is performed to quantitatively calculate the estimated total cost of sticking to the original optimal path and the total cost of switching to a newly calculated emergency path, forming a decision set.

[0026] Finally, the decision set is visualized to assist managers in making construction decisions.

[0027] This invention provides a cable laying path planning and multi-objective collaborative construction management platform. It has the following beneficial effects:

[0028] 1. This invention integrates the L1 static geometry layer, L2 engineering physical cost layer, and L3 time-varying management cost layer of cable laying paths by constructing a dynamic multi-layered state grid model. This multi-dimensional modeling approach merges the originally scattered geometric, physical, and time-series management data into a unified data structure, providing a complete and consistent data foundation for subsequent multi-objective path optimization and dynamic causal analysis, overcoming the shortcomings of traditional methods that are difficult to comprehensively evaluate due to data isolation.

[0029] 2. This invention establishes a dynamic causal propagation mechanism from L4-level physical deviations to L3-level management cost consequences by setting up a DCCP module. When a physical anomaly occurs on-site, this mechanism can automatically deduce its chain reaction on subsequent work hours, work process plans, and resource utilization, and quantify it into specific cost changes to update the model. This allows managers to grasp the global impact of a local physical event on the overall project management cost in real time and accurately, achieving dynamic quantitative assessment of construction risks.

[0030] 3. This invention generates a decision set containing quantified cost comparisons through dynamic replanning units, changing the traditional emergency response model that relies on personal experience. After an anomaly occurs, the platform can simultaneously provide estimated total costs for both adhering to the original path and switching to the emergency path, transforming complex decision-making problems into a clear comparison of two cost values. This provides managers with direct data support, making their decision-making process more objective and efficient, thereby achieving dynamic optimization of the construction process. Attached Figure Description

[0031] Figure 1 This is a system architecture diagram of the collaborative construction management platform according to an embodiment of the present invention;

[0032] Figure 2 This is a flowchart illustrating the collaborative construction management method according to an embodiment of the present invention.

[0033] Figure 3 This is a schematic diagram of the concept of a dynamic multilayer state grid (MSG) model according to an embodiment of the present invention;

[0034] Figure 4 This is a flowchart of the dynamic causal propagation process of the DCCP module in an embodiment of the present invention;

[0035] Figure 5 This is a flowchart of the decision-making process for the dynamic replanning unit in an embodiment of the present invention. Detailed Implementation

[0036] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Example:

[0038] Please see the appendix Figure 1 -Appendix Figure 5 This invention provides a cable laying path planning and multi-objective collaborative construction management platform, which includes: a data acquisition and interface module, a data modeling and storage module, a core calculation and decision-making module, and an application and display module.

[0039] The core calculation and decision-making module may further include: a C3F (multi-objective collaborative construction cost function) configuration unit, a path optimization solver, a DCCP (dynamic causal propagation) module, and a dynamic replanning unit.

[0040] The following section will describe a complete workflow of the method of this invention in conjunction with the system architecture.

[0041] S101: Before construction, the platform performs model initialization. The data acquisition and interface module is responsible for connecting to and acquiring the static data required to build the model. In one implementation, this module acquires the following through the data interface: building geometry information from the BIM system (such as the three-dimensional coordinates, dimensions, and bending radius of shafts and cable trays), construction plans from the PM project management software (such as work schedules and space occupancy information for other trades), and physical parameters from the cable specification database (such as cable mass per unit length, minimum allowable bending radius, and maximum allowable tension).

[0042] The data modeling and storage module receives the aforementioned static data and processes it in its core database to construct an initial dynamic multilayer-state grid (MSG) model. Specifically, the MSG model transforms physical construction space (e.g., a section of shaft or cable tray in BIM) into "edges" in graph theory and quantifies cable physical parameters into the L2-level physical risk cost (e.g., tension cost) of that "edge". Side pressure cost Cost of violations At the same time, the PM software's plans (e.g., resource usage) are mapped to the L3 layer time-varying management costs (e.g., occupancy costs) of this "edge". Labor cost ).

[0043] S201: The platform performs static path planning. Project managers (administrators) access the C3F configuration unit in the core computing and decision-making module through the collaborative management interface provided by the application and presentation module. The C3F configuration unit provides a set of configurable weight parameters. This function is used to define a multi-objective collaborative construction cost function (C3F). This function is used to uniformly quantify the "total cost" of L2-level physical risk and L3-level management cost for any path.

[0044] In one implementation, the C3F function It can be represented as:

[0045] ;

[0046] in: This represents a line consisting of multiple "edges". The complete path; This is the start time of construction; It is calculated based on the construction speed, reaching the "edge". The point in time; It is an "edge". The physical risk costs (e.g., ); It is an "edge". exist Time management costs (e.g., ); and These are set by the C3F configuration unit, representing the priority weights of "physical risk" and "management cost" for managers, respectively.

[0047] After the C3F function is configured, the path optimization solver (e.g., an A* or Dijkstra algorithm implementation) begins computation. This solver uses... Using the cost function, a search is performed on the MSG model (L1, L2, L3 layers) constructed in S101 to find a solution. Lowest initial optimal path .Should The path results are distributed to the construction terminal interface through the application and display module for on-site personnel to execute.

[0048] S301: The platform enters the dynamic execution and monitoring phase. During construction execution, the data acquisition and interface module obtains real-time physical data (such as real-time tension) from on-site IoT sensors (such as tension meters deployed on the winch) at layer L4 through its dynamic data interface. The DCCP module can receive and monitor the above-mentioned dynamic data of the L4 layer in real time, or receive field reports (such as "path blockage") from the construction terminal interface.

[0049] S401: The DCCP module performs dynamic causal propagation. The DCCP module will transfer real-time data from layer L4 (e.g., ...) ) and MSG model L2 planning values ​​corresponding to the path (e.g., planning tension) ) for comparison. When a deviation is detected (e.g. Exceeding the planned tension And reach the preset engineering threshold. When ), the DCCP module initiates causal deduction.

[0050] This deduction translates the L4 physical deviation (excessive tension) into one or more management consequences. For example, it derives "to ensure safety, the actual construction speed..." "must be reduced", and further deduced "current path" Remaining working hours Will increase ".

[0051] The DCCP module will address this consequence (increased working hours). This update automatically propagates and updates back to the MSG model (L3 layer) in the data modeling and storage module. This update has a ripple effect: it will lead to... All subsequent edges on the path Plan start time All were postponed This delay may lead to In the new This can lead to new conflicts with the resource plans of Layer 3 (e.g., other job roles), resulting in... The cost changes from 0 (no conflict) to a high cost (conflict).

[0052] S501: The platform executes collaborative decision-making. In S401, after the DCCP module updates the MSG model (i.e.... Path (In real time due to chain reactions), the core computing and decision-making modules automatically trigger collaborative decision-making processes.

[0053] The dynamic replanning element is activated. This element "commands" the path optimization solver, requiring it to be based on the MSG model that has been "updated by DCCP" and with the "current construction node". Starting from "" and using "current time" as the starting point "for Immediately re-execute the optimization calculation in S201 to find a new emergency path. and its total cost .

[0054] At the same time, the platform recalculates based on the updated MSG model. Estimated total cost of adherence .

[0055] Finally, the application and presentation module provides project managers with two quantifiable decision options on its collaborative management interface: the "Persist" option (displaying costs). ) and the "Toggle" option (display cost) Based on this, the project manager makes collaborative management decisions, forming a closed-loop management system.

[0056] The data acquisition and interface module includes a static data interface, which is used to obtain the static basic data required to build the MSG model (L1, L2, L3 layers) from external, existing enterprise information systems during the S101 model initialization phase, and provide it to the data modeling and storage module 20.

[0057] In one specific implementation, the functionality of the static data interface is achieved through the following sub-interfaces:

[0058] The BIM / CAD interface is used to retrieve the geometric information needed for Level 1 from Building Information Modeling (BIM) systems or CAD drawing files. This interface can be configured to connect to a BIM server via an API (Application Programming Interface) or to parse drawing files in specific formats (such as RVT, DWG, IFC). This interface extracts building components identified as cable routing paths (e.g., cable shafts, cable trays, conduits). For each component (corresponding to an "edge" in the MSG),... This interface obtains its 3D topology information, geometric dimensions, and path length. Bending radius of critical nodes and vertical tilt angle For the file parsing or API call implementation of BIM / CAD data, those skilled in the art can use well-known techniques, which will not be elaborated here.

[0059] A Project Management (PM) interface is used to retrieve the resource timing information required for Layer 3 from a PM software system (such as Oracle Primavera P6 or MS Project). This interface can access the PM system's Work Breakdown Structure (WBS) or task list via database connection or API. This interface also extracts other construction tasks that conflict with resources in the cable laying space (such as Shaft A). For each conflict task This interface retrieves its planned start time. Planned end time And the spatial location identifier it occupies.

[0060] An engineering parameter interface is provided to retrieve the required engineering physical parameters for Layer 2 from a cable specification database, technical specifications, or configuration file. This interface reads parameters corresponding to the cable type used in this laying task. These parameters specifically include: the mass per unit length of the cable. Minimum allowable bending radius of the cable Maximum allowable laying tension of the cable And the coefficient of friction between the cable outer sheath and the material of the laying path (such as cable trays, conduits). .

[0061] The data acquisition and interface module standardizes the geometric information, temporal information, and engineering physical parameters obtained above, and then submits them to the data modeling and storage module for subsequent MSG model construction.

[0062] The data acquisition and interface module also includes a dynamic data interface, which is used to establish a real-time communication link from the construction site during the S301 dynamic execution and monitoring phase to obtain the dynamic data stream required to update the MSG model site status layer (L4).

[0063] In one specific implementation, the dynamic data interface achieves the access and standardization of field data in the following way:

[0064] This interface is equipped with an IoT (Internet of Things) gateway communication unit for establishing connections with sensors deployed on critical construction equipment. These sensors include, but are not limited to, a digital tension meter mounted on the traction winch for real-time acquisition of actual traction force values. A rotary encoder mounted on a winch or cable-laying frame is used to collect real-time data on the actual cable laying speed. The system includes the length of the installed network and environmental sensors located at critical path points (such as corners) to collect local ambient temperature or humidity data. The IoT gateway communication unit receives the raw data packets sent by the aforementioned sensors via industrial fieldbus or wireless transmission protocols (such as LoRa, NB-IoT, or 5G private networks).

[0065] The interface is also equipped with a mobile terminal communication unit for data interaction with handheld devices held by construction site personnel. This unit receives unstructured anomaly reports input by on-site personnel through the construction terminal interface, such as "Unrecorded construction waste obstruction found in shaft B".

[0066] The dynamic data interface standardizes the received raw data packets and anomaly reports. This process includes adding a precise timestamp to each data entry. Based on the sensor location identifiers or the locations selected by on-site personnel, the data is mapped to the corresponding "edges" in the MSG model. Convert physical values ​​into standardized units of measurement. Standardized data (e.g., in the form of...) The data tuples are pushed in real time to the core computing and decision-making module and the data modeling and storage module, serving as the input for the DCCP module to trigger causal inference. For the specific communication protocol implementation of the IoT gateway and the data transmission implementation of the mobile terminal, those skilled in the art can use well-known technologies, which will not be elaborated here.

[0067] In the S101 model initialization phase, the data modeling and storage module receives static data from the data acquisition and interface module and performs MSG model construction in the core database. The MSG model is the data foundation for path planning and cost calculation in this invention, and in a preferred embodiment, it is constructed as a multi-dimensional weighted time-varying graph. .

[0068] In this image middle, (Vertices) represents the set of critical nodes in the construction path, such as the entrance, exit, corner, or cable anchor point of a cable shaft. (Edges) represents the set of feasible cable laying path segments (“edges”) that connect these nodes.

[0069] The core function of the data modeling and storage module is to process and quantify the data obtained from BIM, PM software, and cable specifications into the aforementioned diagram. Each "edge" in the middle Multi-layered attributes and cost functions.

[0070] In one specific implementation, the module first constructs an L1-geometry layer and an L2-engineering physical layer. The L1-geometry layer originates from the geometric information obtained from the BIM / CAD interface, and is for each "edge". Assign static geometric properties, including: the length of path segments. Bending radius and vertical tilt angle .

[0071] The L2-Engineering Physical Layer is based on the L1-Geometric Layer and incorporates cable physical parameters (such as minimum allowable bending radius) obtained from the engineering parameter interface. Mass per unit length Maximum permissible tension coefficient of friction ), for each "edge" Calculate its physical risk costs.

[0072] The physical risk costs may include:

[0073] Cost of violation This cost is used to exclude infeasible paths during the planning phase.

[0074] ;

[0075] in It is calculated in advance during the planning process, through this "edge". The estimated tension at that time.

[0076] Tension cost This cost represents the cost of laying the cable through this "edge". The quantified value of the required traction force (tension). It is a physical function. Result:

[0077] ;

[0078] in Is this the "side"? The tension at the input end. The value depends on the previous "edge" in the path. The calculation result (i.e., the outlet tension) is therefore iteratively calculated during path solving. Specific calculations of engineering tension, such as iterative calculations based on friction and gravity components, are well-known techniques in the field and will not be elaborated upon here.

[0079] Side pressure cost This cost represents the cost of the cable at the bent "edge". place (i.e.) The lateral pressure exerted on the cable is used to assess the risk of damage to the cable insulation.

[0080] ;

[0081] The cost Usually with this "edge" Average tension on Proportional to the radius of curvature Inversely proportional.

[0082] Subsequently, the data modeling and storage module constructs the L3-resource time-series layer. This layer maps the resource time-series information obtained from the project management interface into "edges". Management costs.

[0083] The management costs may include:

[0084] Labor cost This cost represents the cost of laying the cable via the "edge". The required costs (such as labor and equipment rental). First, based on the planned laying speed. Calculate the planned working hours Subsequently, labor costs It can be defined as:

[0085] ;

[0086] in It is a configurable unit time cost rate.

[0087] Occupancy cost This is a key time-varying cost used to represent the cost at a specific time. Use "edges" The conflict cost (i.e., physical space). Let... The planned usage space obtained from the PM interface Other construction tasks The set, each With planned start time and the planned end time .

[0088] ;

[0089] in It is the reachable "edge" that the path optimization solver deduces when calculating the path. The point in time.

[0090] The data modeling and storage module stores the attributes and cost functions of each layer (L1, L2, L3). Mount all to map The corresponding "edge" The completed MSG model is then stored in the core database for use by the core computing and decision-making modules.

[0091] The core database, as a component of the data modeling and storage module, is used to process the dynamic multi-layered state grid (MSG) model built in phase S101. Provides persistent storage and data management.

[0092] In one implementation, the core database may be implemented using a relational database (e.g., an SQL database). In this implementation, the database may include: a node table for storing the MSG graph. Nodes in Its fields may include node ID, node type (such as shaft opening, corner), and 3D coordinates; the edge table is used to store the graph. The "edge" in Its fields may include edge ID, start node ID, and end node ID (which are respectively associated with the node ID in the node table through foreign keys).

[0093] To store the multi-layer attributes of the MSG model, the database may also include one or more edge attribute tables, which are associated with the edge tables via edge IDs. These edge attribute tables are used to store the static geometric attributes of the L1 layer (e.g., path length). Bending radius Vertical tilt angle ), and the engineering physical parameters of the L2 layer (e.g. , , , ).

[0094] To achieve time-varying occupancy cost of L3 layer The database may also include a resource time series table. This resource time series table stores conflict information obtained from the PM interface, and its fields may include information related to "edges". Associated edge ID, conflict task identifier and the planned start time of the conflict mission. and the planned end time .

[0095] In another preferred embodiment, given that the MSG model is essentially a graph... The core database can be implemented using a graph database (such as Neo4j). In this approach, the graph... nodes It can be stored as a "node" object, "edge". It can be stored as a "relationship" object that connects "node" objects.

[0096] The attributes and cost function parameters of each layer (e.g., L1, L2, and L3) Planning working hours ,as well as Corresponding conflict timeline These can be stored directly as properties in the "relationship" object (i.e., "edge"). The implementation using a graph database facilitates efficient graph traversal and path lookup by the path optimization solver.

[0097] The core database provides a data query interface for the core computing and decision-making module, allowing the C3F configuration unit and path optimization solver to read MSG model data in phase S201. Simultaneously, this database supports the DCCP module in phase S401 accessing attributes of the L3 layer in the MSG model (e.g., ...). or The database (state) is written and updated in real time. For the specific selection, deployment, and access of relational or graph databases, those skilled in the art can use well-known techniques, which will not be elaborated here.

[0098] The C3F configuration unit is invoked during the S201 static planning phase. In one implementation, the function of this C3F configuration unit is provided to administrators (e.g., project managers) through the collaborative management interface in the application and display module.

[0099] The C3F configuration unit provides a configurable set of weight parameters, which allows managers to customize the cost function used by the path optimization solver based on the current project management objectives (e.g., prioritizing "timeliness" in the early stages of the project, or prioritizing "safety" in specific high-risk sections).

[0100] The objective function configured by the C3F configuration unit is the multi-objective collaborative construction cost function (C3F). Used to quantitatively evaluate any complete path in the MSG model. (composed of multiple "edges") Composition) from The total cost of departing at any given time.

[0101] In one specific implementation, the A function can be defined as:

[0102] ;

[0103] in: It is a line composed of multiple "edges" The complete path;

[0104] This is the start time of construction for this route;

[0105] It is an "edge". The physical risk cost of Layer 2;

[0106] It is based on and path middle The cumulative planned working hours of the previous "edge" The calculated reach of the "edge" The point in time;

[0107] It is an "edge". In The L3 management cost at any given time (this cost is time-varying because...) depending on );

[0108] and It is a primary weight set by the administrator through this unit.

[0109] The physical risk cost of the L2 layer It can be further defined as:

[0110] ;

[0111] The L3 management cost It can be further defined as:

[0112] ;

[0113] in: , , They are respectively "edges" The tension cost, lateral pressure cost, and violation cost (all from the L2 layer of the MSG model). , They are respectively "edges" exist The time-occupancy cost and labor cost (both from the L3 layer of the MSG model).

[0114] The core function of the C3F configuration unit is to provide administrators with interface elements (such as numerical input boxes, drop-down menus, or preset scenario mode buttons) to set the weight parameter values ​​in the above formula.

[0115] The weighting parameters include: first-level weights. (Prioritization for adjusting physical risks) and (Priority used to adjust management costs); and secondary weights. (Tension weight) (Side pressure weight) (Occupying conflict weights) and (Work hour weighting).

[0116] For example, when administrators configure the C3F unit... and , Setting it to a relatively high value indicates that the management objective focuses on construction safety and physical risk avoidance. The path optimization solver calculates... When, will be the first choice and Lower path.

[0117] For example, when managers will and Setting the value to a relatively high value indicates that the management objective focuses on ensuring project schedule and avoiding resource conflicts. The solver will then prioritize selecting... A path with zero cost (i.e., no conflict).

[0118] The C3F configuration unit receives the set of weight parameters set by the administrator. , , , , , Afterwards, the parameter set is stored in the core database or system configuration file. This set of weight parameters is then read by the path optimization solver in the core calculation and decision module in stage S201, serving as the configuration basis for its "cost function" to perform path optimization calculation.

[0119] For the specific implementation of the graphical interface elements (such as forms and numerical input controls) used to implement the above weight parameter configuration in the collaborative management interface, those skilled in the art can use well-known techniques, which will not be elaborated here.

[0120] The path optimization solver, serving as the computational engine of the core calculation and decision-making module, is invoked during the S201 static planning phase and the S501 dynamic replanning phase. Its function is to calculate the multi-objective collaborative construction cost function (C3F) configured by the C3F configuration unit. The MSG model constructed in the data modeling and storage module The algorithm searches and calculates the path with the lowest total cost.

[0121] In a preferred embodiment, the path optimization solver is implemented using the A* (A-star) search algorithm. The reason for using the A* algorithm is that the C3F cost function... Includes time-varying costs ,in particular (Occupancy cost). "Edge" The management cost depends on the time point at which the solver arrives at the edge, as calculated by the solver. This is a time-dependent shortest path problem.

[0122] When the path optimization solver executes the A* algorithm, for the graph... any node in Its evaluation function Defined as:

[0123] ;

[0124] in: From the starting node Passing through the node To the target node The estimated total cost; From To the node The actual total cost (i.e.) (cumulative value) From node arrive The estimated cost (heuristic function).

[0125] The path optimization solver calculates... At that time, it follows the time-varying accumulation rule of the C3F function. When the algorithm starts from node... Extend to adjacent nodes (via "edge") )hour:

[0126] S421: Solver Acquisition (Right now Accumulated to (cost) and (arrive (Time point).

[0127] S422: The solver reads "edges" from the MSG model. Planning working hours (From L3).

[0128] S423: Calculate the reachable node Time point .

[0129] S424: The solver calls the C3F function to calculate this "edge". exist The cost of time .

[0130] ;

[0131] in It is the physical cost of layer L2. It is the cost of L3 level management, and Include That is, the algorithm checks at this moment Whether it falls within a conflict period.

[0132] S425: Update node actual cost .

[0133] The path optimization solver calculates... When using heuristic functions, this ensures the "admissibility" (i.e., guaranteeing that the optimal solution will be found) of the A* algorithm. The valuation shall not exceed that from arrive The actual cost. In one implementation, Can be designed as a node arrive The L1 layer geometric straight-line distance (Euclidean distance), multiplied by a configurable minimum unit cost (e.g., considering only...). And without considering any conflicting minimum labor costs.

[0134] In the S201 static programming phase, the solver uses (Path start point) and Using the planned start time as input, execute the A* algorithm described above on the complete MSG model (L1, L2, L3 layers) to calculate the initial optimal path. .

[0135] During the S501 dynamic replanning phase, the path optimization solver is invoked again by the dynamic replanning unit. At this time, the solver... (Current construction node) is ,by (Current time) is And in "has been updated by DCCP module" (i.e., L3 cost) or The same A algorithm was performed on the MSG model (which has changed) to calculate the emergency path. The implementation of queue management and node expansion in the A search algorithm itself can be carried out using well-known techniques, and will not be elaborated here.

[0136] The DCCP (Dynamic Causal Propagation) module, as a key component of the core calculation and decision-making module, is activated and runs continuously during the S301 dynamic execution and monitoring phase. The core function of this DCCP module is to establish a dynamic causal relationship between the L4 layer (site status) and the L3 layer (resource timing), translating and propagating L4-level physical events at the construction site into L3-level management cost consequences in real time, thereby achieving the dynamic transmission of "physical risk" to "management cost".

[0137] In one specific implementation, the steps for implementing the DCCP module are as follows:

[0138] S431: Deviation Detection. The DCCP module receives L4 layer dynamic data in real time from the data acquisition and interface module. This dynamic data includes, for example, the "edge" being laid. Real-time tension on Or anomalies reported by on-site personnel through the construction terminal interface (such as "obstacles").

[0139] S432: The DCCP module reads this "edge" from the MSG model in the core database. The corresponding L2 planning value, such as planning tension cost. (This value can be considered as the planning tension benchmark for this "edge"). The DCCP module calculates the deviation between the real-time value at level L4 and the planned value at level L2. :

[0140] ;

[0141] in This is the current time.

[0142] S433: Trigger judgment, the DCCP module will determine the deviation. With a configurable engineering tolerance threshold (For example Compare with a certain percentage. When Causal inference is triggered when the tension exceeds the threshold or when a specific anomaly is reported (such as "obstacle").

[0143] S434: Causal deduction; the DCCP module calls an internally configured "engineering-management causal rule base". This rule base stores the functional relationships or logical rules between L4 layer physical deviations and L3 layer management consequences.

[0144] S435: Cost propagation. The DCCP module immediately updates the MSG model (L3 layer) of the data modeling and storage module with the consequences deduced from S434. This update is the starting point of a chain reaction.

[0145] S436: The DCCP module first updates the current "edge". The cost. Taking the above-mentioned tension exceeding the limit rule as an example (S434), the DCCP module, based on the deduced... Recalculate Remaining planned working hours :

[0146] ;

[0147] in yes The remaining path length. This calculation yields an increase in working hours. (in Is according to (Calculated original remaining working hours). The DCCP module will... of Attributes updated to .

[0148] S437: Chain reaction, the DCCP module will increase the working time by [amount]. propagation to the original path All subsequent "edges" in the middle. (in ).

[0149] The DCCP module updates these subsequent "edges". Plan start time :

[0150] ;

[0151] in yes The original planned start time. This update is written to the L3 layer of the MSG model.

[0152] S438: Cost recalculation, DCCP module based on updated start time. Immediately (or notify the solver) re-evaluate all subsequent edges. Time-varying occupancy cost One in Paths with zero time cost (no conflict) ,exist The timing (due to delays) may conflict with L3 layer resource planning (e.g., other tasks occupying resources). A conflict occurred, leading to its Become a high-cost (e.g.) ).

[0153] Through steps S435 to S438, a physical deviation (tension overrun) in layer L4 is successfully "translated" by the DCCP module and propagated into the total cost of layer L3 in the MSG model. The chain reaction continues. After the DCCP module completes the update of the L3 layer of the MSG model, it triggers the dynamic replanning unit in the core computation and decision module to execute the S501 decision process.

[0154] The dynamic replanning unit, as a component of the core computation and decision-making module, is triggered in the collaborative decision-making phase of S501. In one implementation, the trigger condition for this unit is that the DCCP module completes the update of the L3 layer cost of the MSG model (as described in S438). This update indicates that the originally optimal path has been corrected. The cost-time baseline has changed.

[0155] Once the dynamic replanning unit is triggered, the collaborative decision-making process is executed:

[0156] S511: This unit first recalculates the original execution path based on the MSG model that has been updated by the DCCP module. Estimated total cost required This calculation is cumulative. Current construction node on the path Then all remaining "edges" The cost. Because the DCCP module has updated these "edges". Plan start time This estimated total cost will include all newly generated cascading costs (e.g., From 0 to ).

[0157] S512: At the same time, the dynamic replanning unit calls the path optimization solver in the core calculation and decision module.

[0158] S513: This unit issues a replanning instruction to the path optimization solver and provides a new set of calculation start-point parameters. The start-point parameters include: the current construction node. (as a replanning) ); Current time (as a replanning) ).

[0159] S514: After receiving this instruction, the path optimization solver (such as the A* algorithm) will, on the MSG model that has been updated by the DCCP module (which reflects the latest L3 cost state), use... and Starting from the current state, the optimization calculation in phase S201 is executed again. The goal of this calculation is to find an emergency path with the lowest total cost, starting from the current state. .

[0160] S515: The path optimization solver will calculate the emergency path. and its total cost Return to the dynamic replanning unit.

[0161] S516: The dynamic reprogramming unit quantifies and encapsulates the decision options. This unit calculates the cost of the "stick" option in S511. Cost of the "Toggle" option returned in S515 Combine them into a decision set.

[0162] S517: The dynamic replanning unit sends the decision set (containing two quantified cost options) to the application and presentation module for displaying the decision to the project manager on the collaborative management interface, thereby achieving a closed loop of collaborative management.

[0163] In one implementation, the collaborative management interface can be a graphical user interface (GUI) deployed on the computer terminal (e.g., PC, tablet) of the administrator (e.g., project manager). This collaborative management interface is the main entry point for administrators to interact with the core computing and decision-making modules of the platform. For the specific implementation of this GUI, such as development using Web technologies or client application frameworks, those skilled in the art can employ well-known techniques, which will not be elaborated upon here.

[0164] One function of this collaborative management interface is to receive and display the decision set encapsulated by the dynamic replanning unit in S516 during the S501 collaborative decision-making phase. This interface visualizes the quantified cost data within the decision set to assist managers in making collaborative management decisions.

[0165] In one specific implementation, after receiving the decision set, the interface can be presented to the administrator:

[0166] A primary cost display area is provided to clearly show the estimated total cost of the "Persist" option calculated in S511. .

[0167] A second cost display area is provided to clearly show the total emergency path cost of the "switchover" option calculated in S515. .

[0168] The interface also provides a path visualization area. This area can access BIM model data or L1 layer geometry data, highlighting the original path on a 3D view or 2D path map using different identifiers (e.g., different colors or line types). The remaining part and the newly calculated emergency routes .

[0169] The interface also includes decision input controls. For example, there is a "Confirm Insist" button and a "Confirm Switch" button. After comparing the two cost values ​​and the path visualization results, the manager selects a decision by acting on one of the buttons (e.g., clicking). This decision instruction is then sent back to the core calculation and decision module (e.g., to trigger the issuance of a new path instruction to the construction terminal interface), thus forming a management loop.

[0170] Another function of this collaborative management interface is to serve as the human-computer interaction entry point for the C3F configuration unit during the S201 static planning phase. As mentioned earlier, administrators can use the interface elements provided by this interface (such as numerical input boxes, weight adjustment sliders, or scenario mode buttons) to adjust the weight parameters (e.g., ...) in the C3F function. ) to make settings and adjustments.

[0171] The construction terminal interface, as a component of the application and display module, can, in one embodiment, be a graphical user interface (GUI) running on a mobile handheld device (such as an industrial-grade tablet or smartphone) held by personnel at the construction site. This interface serves as the execution terminal for information interaction between on-site construction personnel and the platform. For the specific application development of this GUI on mobile devices, those skilled in the art can employ well-known techniques, which will not be elaborated upon here.

[0172] The construction terminal interface has the functions of receiving path instructions and reporting L4 layer field data.

[0173] Regarding the path instruction receiving function, this interface is used to receive and display path instructions issued by the core computing and decision-making module to on-site personnel.

[0174] S521: After the static planning phase in S201 is completed, this interface receives and displays the initial optimal path calculated by the path optimization solver. .

[0175] S522: During the S501 dynamic replanning phase, if the administrator makes a "confirm switch" decision through the collaborative management interface, the interface will receive and display the new emergency path issued by the dynamic replanning unit. .

[0176] In one specific implementation, this path instruction receiving function is implemented through a "path guidance unit". This path guidance unit receives the path (… or It can provide visualizations. For example, based on the L1 layer geometry data of the MSG model, it can highlight the "edges" contained in the path in a simplified 2D or 3D view. The sequence is clearly marked, and the "edge" that should be constructed at the current time is clearly identified. This guidance unit can also display information related to the current "edge". Relevant key engineering parameters of L2 layer, such as planning tension or maximum permissible tension To guide on-site safe construction.

[0177] Regarding the L4 layer field data reporting function, this interface serves as a data source input terminal for the dynamic data interface in the data acquisition and interface module.

[0178] S523: This interface provides data input controls for on-site construction personnel to report anomalies that are not covered by IoT sensors and are discovered during the S301 dynamic monitoring phase.

[0179] In one specific implementation, the data reporting function is implemented through an "anomaly reporting unit". This unit can provide a set of predefined event buttons (e.g., obstacle detection, water accumulation in the path, equipment failure) and a text description box.

[0180] S524: When on-site personnel submit a report through this unit, the interface will display the reported content (e.g., "obstacles") and the current time. Current location (e.g.) The data is bound and sent to the DCCP module in the core computing and decision-making module through the mobile terminal communication unit in the data acquisition and interface module, as input for S431 deviation detection and S434 causal inference.

[0181] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A cable laying path planning and multi-objective collaborative construction management platform, characterized in that, include: The data modeling and storage module is used to construct a dynamic multi-layer state grid model, wherein the path "edge" in the dynamic multi-layer state grid model contains at least three data layers: L1 static geometry layer, L2 engineering physical cost layer and L3 time-varying management cost layer; The core computing and decision-making module is coupled to the data modeling and storage module, and the core computing and decision-making module includes: A path optimization solver is used to calculate an initial optimal path based on the dynamic multi-layer-state grid model. The DCCP module is used to dynamically monitor the real-time physical parameters of the L4 layer. When a deviation is detected between the real-time physical parameters and the planned values ​​in the L2 engineering physical cost layer, the cost data in the L3 time-varying management cost layer is updated based on a preset causal relationship. The dynamic replanning unit is triggered when the cost data in the L3 time-varying management cost layer is updated by the DCCP module to call the path optimization solver, calculate an emergency path, and quantify the estimated total cost of sticking to the initial optimal path and the total cost of switching to the emergency path to form a decision set. The application and display module is used to receive and visualize the decision set for managers to make decisions.

2. The cable laying path planning and multi-objective collaborative construction management platform according to claim 1, characterized in that, The core computing and decision-making module also includes: The C3F configuration unit provides a configurable set of weight parameters. The path optimization solver, based on the set of weight parameters, performs a weighted summation of the costs in the L2 engineering physical cost layer and the L3 time-varying management cost layer to form a multi-objective collaborative construction cost function, and performs path optimization based on this function.

3. The cable laying path planning and multi-objective collaborative construction management platform according to claim 1, characterized in that, The L2 engineering physical cost layer includes at least one of tension cost and lateral pressure cost; the L3 time-varying management cost layer includes labor cost and occupancy cost.

4. The cable laying path planning and multi-objective collaborative construction management platform according to claim 3, characterized in that, The specific function of the DCCP module is as follows: The deviation of the real-time physical parameters of the L4 layer is first extrapolated to the increase in the time cost, and the time cost of the corresponding path "edge" in the dynamic multi-layer-state mesh model is updated.

5. The cable laying path planning and multi-objective collaborative construction management platform according to claim 4, characterized in that, The DCCP module is also used for: The increase in the labor cost is further propagated to the planned construction start time of all subsequent path "edges" in the initial optimal path, resulting in a chain reaction of delays in the planned construction start time.

6. The cable laying path planning and multi-objective collaborative construction management platform according to claim 5, characterized in that, The DCCP module is also used for: Based on the planned construction start time after the chain delay, the occupancy cost of all subsequent path "edges" is reassessed to determine whether new resource occupancy conflicts arise due to the time delay, and the occupancy cost is updated.

7. The cable laying path planning and multi-objective collaborative construction management platform according to claim 1, characterized in that, The dynamic replanning unit, when quantifying the decision set, specifically includes: Based on the updated L3 time-varying management cost layer, calculate the estimated total cost of continuing to execute the remaining part of the initial optimal path; Starting from the current construction node and the current time, calculate the total cost of the emergency path on the updated dynamic multi-layer-state grid model.

8. The cable laying path planning and multi-objective collaborative construction management platform according to claim 7, characterized in that, The application and display module includes: The collaborative management interface is used to display the estimated total cost and the total cost of the emergency route side by side, and provides decision input controls to receive route instructions selected by the manager.

9. The cable laying path planning and multi-objective collaborative construction management platform according to claim 1, characterized in that, The application and display module includes: The construction terminal interface is used to receive and visually display the selected path instructions to on-site construction personnel. The construction terminal interface is also used to receive anomalies reported by on-site construction personnel and provide the anomalies as part of the real-time physical parameters of the L4 layer to the DCCP module.

10. A method based on the platform of claim 1, characterized in that, Includes the following steps: Construct a dynamic multi-level state-grid model, wherein the path "edge" in the dynamic multi-level state-grid model contains at least three data layers: L1 static geometry layer, L2 engineering physical cost layer and L3 time-varying management cost layer; Based on the dynamic multi-layer-state grid model, an initial optimal path is calculated; During construction along the initial optimal path, the real-time physical parameters of layer L4 are dynamically monitored; When a deviation is detected between the real-time physical parameters and the planned values ​​in the L2 engineering physical cost layer, the cost data in the L3 time-varying management cost layer is updated based on a preset causal relationship. When the cost data in the L3 time-varying management cost layer is updated, replanning is triggered, an emergency path is calculated, and the estimated total cost of sticking to the initial optimal path and the total cost of switching to the emergency path are quantified to form a decision set. The decision set is visualized to facilitate decision-making by managers.

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