Full life cycle management method of water conservancy projects based on BIM and big data

Abstract

The present invention discloses a full life cycle management method for water conservancy projects based on BIM and big data, which specifically relates to the field of project scheduling management, including: extracting the water inlet and outlet attributes, geographic information and elevation of water conservancy structures, establishing a set of structural nodes with water-passing semantics, and analyzing their execution order to form functional dependency edges; combining historical construction records with typical plateau meteorological data, extracting construction offset nodes and constructing meteorological response offset attributes; fusing structural nodes, functional dependency edges and response attributes to construct a multi-dimensional construction management and control map, and subsequently dynamically adjusting the node order and accessibility status in the map according to the construction log and real-time meteorological conditions after the project is started; finally, embedding the dynamic map into the BIM plan task chain, and generating a construction task scheduling path re-arrangement plan through the linkage adjustment channel, so as to realize the active response and automatic planning capabilities of construction scheduling to meteorological conditions, and improve the construction coordination and task execution efficiency of plateau water diversion projects.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering scheduling management, and more specifically, to a full life cycle management method for water conservancy projects based on BIM and big data. Background Art

[0002] Water diversion and water diversion projects in plateau regions are widely deployed at high altitudes and in areas subject to dramatic seasonal climate change. These areas often experience a brief construction window, characterized by only a few months each year when ground is free of frozen soil and water levels are low. To advance construction within a limited timeframe, multiple operations are often carried out in parallel, attempting to minimize time costs. However, this construction strategy can easily lead to missequencing of construction paths. For example, construction of downstream surge tanks, spillways, or open channel linings can commence before the upstream water source or diversion tunnel sections have been completed and anti-seepage treatment has been completed. This missequencing of "structural advancement" and "hydraulic logic lag" often results in structural rework, material waste, and even irreversible engineering system defects. While existing BIM systems offer progress visualization and construction node management capabilities, they generally lack the ability to dynamically embed seasonal construction windows within specific regions and fail to identify discrepancies between node execution order and hydraulic logic within a multi-path water diversion chain.

[0003] Therefore, there is an urgent need to build an integrated solution with seasonal constraint modeling capabilities, path logic difference identification mechanism and out-of-sequence correction strategy generation function to support the collaborative management of the entire construction process of plateau water diversion projects under complex geographical and climatic conditions. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a full life cycle management method for water conservancy projects based on BIM and big data to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The full life cycle management method for water conservancy projects based on BIM and big data includes the following steps:

[0007] S1: Obtain the water inlet and outlet properties, geographical location and elevation information of the water conservancy project structure, and establish a set of structural nodes with water flow function semantics;

[0008] S2: Extract the semantic logical relationship between structural nodes and form the functional dependency edge of the node execution order;

[0009] S3: Combine historical construction data with plateau meteorological conditions to extract structural nodes where actual construction deviates from pre-planned construction times, and analyze the corresponding meteorological response deviation attributes;

[0010] S4: Fusion of structural node sets, functional dependency edges, and meteorological response offset attributes to construct a multivariate construction control graph structure;

[0011] S5: Based on the construction log and meteorological data after the project starts, adjust the order and accessibility status of the structural nodes in the multi-dimensional construction control map structure to establish a dynamic construction control map;

[0012] S6: Build a linkage adjustment channel between the BIM scheduling path and the dynamic construction control map, embed the construction control map into the BIM planning task chain, and generate a scheduling path rescheduling plan for the construction task.

[0013] In a preferred embodiment, in S1, obtaining the water inlet and outlet properties, geographical location and elevation information of the water conservancy project structure and establishing a structure node set with water flow function semantics specifically includes:

[0014] Mark all structures with water diversion or drainage design objectives in the water conservancy project design drawings, and determine the scope of the structural entities with water flow diversion functions;

[0015] Compare the water flow direction arrows in the design drawing with the port connection directions of the structural entities to obtain and mark the water flow channel structural entity groups with spatial connectivity;

[0016] Collect the terrain elevations at both ends of the geographical locations of the structural entities in the structural entity group and eliminate structural entities with backflow risks;

[0017] Combining the functions of structural entities, connectivity annotations and elevation difference judgment results, the structural entities that can form effective water flow chains in the engineering layout are identified, and based on the functional description keywords of the structural entities, the corresponding structural entities are marked as water flow function semantic structure nodes.

[0018] In a preferred embodiment, in S2, extracting the semantic logical relationship between the structural nodes to form the functional dependency edge of the node execution order specifically includes:

[0019] Extract the structural nodes with water flow connectivity annotations from the structural node set, and annotate the functions of each structural node according to the corresponding functional description keywords;

[0020] Based on the semantic logical relationship of the functions, the relative positions of all structural nodes in the functional process design are calibrated to establish construction sequence execution constraints;

[0021] The construction sequence execution constraints between structural nodes are converted into a unidirectional sequence relationship, which stipulates that the start condition of downstream node construction depends on the completion of upstream node construction.

[0022] Draw unidirectional connection edges for structural node pairs with unidirectional sequential relationships and mark them as functional dependency edges;

[0023] Bind the functional dependency edges with the corresponding structural node numbers, and output a set of functional dependency edges with functional order constraint attributes.

[0024] In a preferred embodiment, in S3, combining historical construction data with plateau meteorological conditions, extracting structural nodes whose actual construction time deviates from the pre-planned construction time, and analyzing the corresponding meteorological response deviation attributes specifically include:

[0025] The planned construction time and actual construction time corresponding to all semantic structure nodes with water supply function are extracted from the historical construction data set, and the interval between the planned construction time and the actual construction time is marked as the construction time offset segment.

[0026] According to the location of the structural nodes and the planned and actual construction time, the historical meteorological observation data of the plateau construction area is matched. The historical meteorological observation data at least includes the time of the occurrence of frozen soil, the time of the dry period, the time of the main rainy season, and the corresponding duration;

[0027] Overlapping classification processing is performed on the construction time data and meteorological observation data of the structural nodes to divide the historical construction response structural nodes with similar meteorological-driven response behaviors;

[0028] The classification processing results are associated with the functional type labels of the historical construction structure nodes, and the meteorological response offset attributes corresponding to different functional structure nodes are marked.

[0029] In a preferred embodiment, the overlapping classification processing of the construction time data and the meteorological observation data of the structural nodes to divide the historical construction response structural nodes with similar meteorological driven response behaviors specifically includes:

[0030] The structural nodes in the historical construction dataset are classified into corresponding construction projects according to their geographical locations;

[0031] Extract the construction time offset segments of the construction project during the entire construction period and synchronize them with the occurrence times of different meteorological types in the historical meteorological observation data of the corresponding area on the time axis;

[0032] The overlap index is calculated based on the intersection ratio of the construction time offset segment and the time windows of different meteorological conditions, and the overlap indexes of different meteorological conditions are integrated into a joint feature.

[0033] Based on the feature similarity of the joint features, the response behavior of the joint features is classified, and the mean value of the joint features of the structural nodes of different categories in all construction projects after classification is calculated as the response offset weight of the corresponding meteorological conditions, and the response offset weight is used as the meteorological response offset attribute of the structural nodes of the corresponding category.

[0034] In a preferred embodiment, in S4, the fusion of the structural node set, the functional dependency edge and the meteorological response offset attribute to construct the multivariate construction control graph structure specifically includes:

[0035] The unidirectional sequence recorded in the functional dependency edge is mapped into a directed semantic path structure between nodes, and the scheduling trigger sequence is marked. At the same time, based on the functional label carried by each structural node in the structural node set, the response offset attribute is assigned to the corresponding structural node, and a construction control map structure that includes water supply conditions, meteorological responses and construction constraints is constructed.

[0036] In a preferred embodiment, in S5, based on the construction log and meteorological data after the project starts, the order and accessibility status of the structural nodes in the multi-dimensional construction control map structure are adjusted to establish a dynamic construction control map, which specifically includes:

[0037] After the target project is launched, the construction log records of each structural node are extracted, and the construction progress time sequence records are generated for the structural nodes in the multi-dimensional construction control map structure;

[0038] In the construction progress time series records of the monitoring structure nodes, if there is an event of a change in the function description keyword or a change in the terrain parameters at the corresponding location, the dependent edges of the structure nodes will be adjusted sequentially;

[0039] Obtain the real-time meteorological conditions of the construction area, and based on the response offset weight in the meteorological response offset attribute of the structure node, determine whether the construction of the corresponding structure node is blocked by the current meteorological conditions according to the preset weight threshold;

[0040] If so, the structural node blocked by construction and all subsequent nodes associated with the corresponding dependency edges will be marked as unreachable in the construction control map until the construction blockage is lifted and restored.

[0041] In a preferred embodiment, in S6, a linkage adjustment channel between the BIM scheduling path and the dynamic construction control map is constructed, the construction control map is embedded in the BIM planning task chain, and the scheduling path rescheduling plan for the construction task is generated, specifically including:

[0042] Mark the structural node index corresponding to each task component in the BIM planning task chain and establish the corresponding relationship between the dynamic graph and the BIM scheduling logic;

[0043] Set the information transmission rules triggered when the status of the structural nodes in the diagram changes, and adjust the BIM task progress status accordingly according to the node status changes;

[0044] Locate the structural nodes marked as unreachable in the current BIM plan task chain, extract the broken task chain segments and search for local alternative paths, build a new continuous advancement path and generate an updated plan;

[0045] When the unreachable structure node is restored to an executable state, the restored structure node is dynamically inserted into the accommodating section of the current task chain.

[0046] The technical effects and advantages of the water conservancy project full life cycle management method based on BIM and big data of the present invention are as follows:

[0047] Focusing on the seasonal water diversion construction characteristics of water conservancy projects in plateau regions, a multi-faceted construction control map was constructed, integrating the semantics of water diversion functions, structural execution sequences, and meteorological response offset attributes. The map was dynamically updated using real-time construction logs and meteorological data, and the updated map structure was embedded in the planned task chain of the BIM system, enabling intelligent rescheduling of construction task scheduling paths. Compared to traditional BIM planning methods based on static logic and fixed node sequences, this solution can develop a dynamic response mechanism for typical meteorological factors such as plateau permafrost, dry zones, and the main rainy season window, proactively predicting the risk of construction node obstructions and adjusting dependencies. By aggregating the offset behaviors of multiple projects under different meteorological conditions, a transferable meteorological response attribute model was established, enabling the BIM system to possess regional adaptability and automatic adjustment capabilities. This solution effectively addresses the disconnect between construction plans and the actual environment in plateau water diversion projects, improving the timeliness, continuity, and resource matching efficiency of construction scheduling, and possessing strong project adaptability and promotional value. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a schematic diagram of the full life cycle management method of water conservancy projects based on BIM and big data in the present invention. DETAILED DESCRIPTION

[0049] The following will provide a clear and complete description of the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0050] Example 1, Figure 1 The present invention provides a full life cycle management method for water conservancy projects based on BIM and big data, which includes the following steps:

[0051] S1: Obtain the water inlet and outlet properties, geographical location and elevation information of the water conservancy project structure, and establish a set of structural nodes with water flow function semantics;

[0052] S2: Extract the semantic logical relationship between structural nodes and form the functional dependency edge of the node execution order;

[0053] S3: Combine historical construction data with plateau meteorological conditions to extract structural nodes where actual construction deviates from pre-planned construction times, and analyze the corresponding meteorological response deviation attributes;

[0054] S4: Fusion of structural node sets, functional dependency edges, and meteorological response offset attributes to construct a multivariate construction control graph structure;

[0055] S5: Based on the construction log and meteorological data after the project starts, adjust the order and accessibility status of the structural nodes in the multi-dimensional construction control map structure to establish a dynamic construction control map;

[0056] S6: Build a linkage adjustment channel between the BIM scheduling path and the dynamic construction control map, embed the construction control map into the BIM planning task chain, and generate a scheduling path rescheduling plan for the construction task.

[0057] In S1, the water inlet and outlet properties, geographical location and elevation information of the water conservancy project structure are obtained, and a set of structural nodes with water flow function semantics is established.

[0058] Comprehensively extract and classify structural entities from water conservancy project design drawings. Design drawings are in 2D CAD format or BIM component hierarchical views and contain structural information such as gates, culverts, diversion channels, spillways, discharge tunnels, and grit chambers. In practice, by analyzing the name fields, functional descriptions, or legends of each structure in the drawings, we systematically identify structures with a clear design objective of "water diversion" or "water drainage." These structures are typically indicated in the drawings by specific symbols or textual descriptions of their flow management function. For example, keywords such as "diversion culvert," "spillway," and "surge tank" can serve as explicit identifiers of structural functions. The selected structures are uniformly categorized as structural entities with "water flow diversion function." This scope serves as a set of objects for semantic structure node identification. After extracting functional structural components, we further determine the connectivity of these structures in physical space. The dominant water flow direction is indicated in the engineering design drawings by flow arrows. The structural entities themselves also include explicit information on water inlet and outlet ports, such as the two ports of the culvert and the upstream and downstream water surface connections of the gate. During implementation, the ports of each structural entity should be vectorized, including their position coordinates, orientation angles, and corresponding arrow lines. The specific processing method is to perform image segmentation and vector tracking operations on the arrow marks in the drawing to identify the arrow's starting and ending points. Then, through spatial geometric matching, the arrow's direction is compared with the direction of the structure's port to determine whether a continuous water flow path is formed. If the arrow's end point coincides with a structure's inlet and the directional consistency is within ±15° (the default judgment threshold can be flexibly set according to the actual construction scenario), the structure is determined to be part of the water flow channel. All structural entities that meet the above spatial connectivity relationships are aggregated into a water flow channel structural entity group. The structure of the entity group must ensure that at least one end is physically accessible to other structures through arrows to ensure logical connectivity and practical feasibility of hydraulic design. Structural entities not in a continuous water flow path do not need to rely on functional sequence for construction constraints and are therefore not included in the automated construction task allocation.

[0059] To eliminate potential reverse slope or backflow risks in the design, elevation data is sampled for each component in the identified connected structural entity group. Terrain elevation information can be obtained from contour lines included in the design drawings, structural cross-sections, or 3D terrain datasets. During sampling, the geometric centers of the water inflow and outflow ends of the structural entities are used as sampling points, and their corresponding elevation values ​​(in meters) are extracted. If this data is not directly indicated in the design drawings, it can be obtained by converting the drawing scale at the intersection with the terrain cross-section. After sampling, an elevation difference determination is performed for each structural entity. If the elevation of the water inflow end is lower than the elevation of the outflow end, and the elevation difference exceeds a set reverse slope threshold (set at 0.5 meters), the structure is flagged as a potential backflow risk and must be removed from the subsequent water flow path. The 0.5-meter threshold is based on the minimum head loss allowed in the design of small-scale water diversion structures in conventional projects and is combined with a safety margin for storage and buffer volume. It can be flexibly adjusted based on actual construction conditions. The purpose is to exclude the construction of risky structural entities from the automated construction task allocation and have their task allocation determined manually.

[0060] Combined with the above-mentioned functional attributes, spatial connectivity and elevation judgment results, the structural entities are finally screened to identify the key nodes that can constitute a complete water flow path chain. Specifically, only structural entities that meet the following three conditions at the same time can be included in the set of water flow function semantic structural nodes: first, they have water diversion or drainage design functions; second, they form a directed connection path with other nodes and the direction of water flow is clear; third, the direction of water flow is from high to low without backflow risk. After identifying such structures, their functional description fields (such as "water inlet", "spilling hole", "diversion channel section", "overflow dam section", etc.) are text parsed to extract keywords as semantic tag sources. These keywords are assigned as semantic labels to the corresponding structural entities, and are marked as water flow semantic nodes based on their logical positions in the connection path.

[0061] In S2, the semantic logical relationships between structural nodes are extracted to form functional dependency edges of the node execution order.

[0062] Data extraction is performed on a set of structural nodes that have been identified and confirmed to have flow connectivity annotations. This set of structural nodes meets the requirements for functional identification, flow connectivity, and terrain elevation differences, and possesses actual water flow path logic. Based on this, the functions of each structural node are further semantically annotated. To ensure the accuracy of the functional annotations, the name field, structure type field, and functional description field of each structural node are uniformly parsed, and keywords representing specific engineering tasks are extracted as functional semantics. For example, if a structural node type is "water diversion culvert" and the functional description includes "water diversion to a storage tank," its function is clearly defined as "water transmission"; if it is a "spillway," its function is defined as "flood discharge" or "excessive discharge"; if it is a "sand trap," its function is labeled as "pre-purification," etc. After obtaining the functional annotations of the structural nodes, the functional flow relationships between the structural nodes are further analyzed based on the standard process logic of water conservancy projects. The specific implementation method involves constructing a functional flow sequence, encompassing the water flow functional links of a water conservancy project, such as "water diversion, purification, transmission, distribution, storage, and discharge." Combined with the functional annotations of each node, the sequence of structural nodes in the functional chain is automatically deduced. For example, if node A is a "water inlet" and node B is a "storage reservoir," and they are connected and spatially ordered, then A is assumed to precede B, and a construction sequence constraint is established between A and B. This sequence is based on the actual execution logic of the water flow process. Clear predecessor and successor construction sequence constraints must be established for all logically driven upstream and downstream structural node pairs. During this process, manual intervention is introduced as the final judgment basis for complex functional links in the construction process. The logical precedence relationship between nodes is strictly determined based on the structural function type and its functional sequence logic. Based on the final judgment, the construction sequence is clearly defined as a hard dependency constraint for actual project execution. That is, if node A logically precedes node B, the construction start condition for node B must be defined as requiring the completion of construction on node B. For example, only after the upstream water source section or diversion tunnel section is completed with penetration and anti-seepage treatment can the downstream surge tank, spillway, or open channel be constructed. This sequential relationship must be represented by a unique directionality and maintain the characteristics of no closed loops or cycles in the entire graph structure to ensure topological order in subsequent construction scheduling.

[0063] The generated unidirectional sequential relationship of the structural nodes is specifically graphed and structured to generate a set of functional dependency edges with engineering semantics. Specifically, for each pair of structural nodes A and B that have a construction sequence relationship, a directed edge from A to B is drawn on the structural node numbering graph, and the edge is labeled as a "functional dependency edge". The existence of such an edge indicates that in the functional execution and construction process, the start of node B is controlled by the completion of node A, which is a deterministic sequential dependency. When drawing functional dependency edges, two core pieces of information need to be bound to each edge: one is the start and end node numbers of the edge, which are used for structural identification and scheduling path tracking; the other is the functional flow category to which the edge belongs. All functional dependency edges are uniformly summarized as a set of functional dependency edges, which can be regarded as a path network with scheduling control semantics in the structural graph.

[0064] In S3, historical construction data and plateau meteorological conditions are combined to extract structural nodes whose actual construction time deviates from the pre-planned construction time, and the corresponding meteorological response offset properties are analyzed.

[0065] In the historical construction dataset, each record's structural node information is geographically categorized, and the structural node is assigned to a specific construction project based on its coordinate information. Typically, many large-scale plateau water conservancy projects have multiple construction project zones in different locations. Spatial matching of the structural node's longitude and latitude with the project zone map is performed (to correlate with regional meteorological data) to clearly identify the corresponding construction project number. After spatial attribution, the planned and actual construction times for each structural node are extracted. Both must be expressed as clear timestamps (year-month-day) and include continuity descriptions (such as start and end date segments). The actual and planned construction times are subtracted to generate a construction time offset segment for each node, clearly indicating the offset start and end dates. This offset segment represents the period of time when construction progress was affected by disturbances. After confirming the geographic scope of the construction project, historical meteorological observation data is retrieved for each plateau region where the project is located. The observation data must cover at least three key meteorological event types: permafrost onset, dry spells, and the main rainy season. The onset of permafrost must include the date of the first surface freeze within the year and the duration of the freeze. The dry period refers to the period of dryness in the main hydrological stream or the period of continuous precipitation loss. The main rainy season must indicate the section with concentrated heavy rainfall and the daily cumulative precipitation. Each type of meteorological event should provide quantitative fields such as start and end time, average temperature or precipitation index, and duration, organized in the form of a time window. For years with incomplete data, the nearest year must be supplemented based on regional statistics to ensure that all construction years have corresponding meteorological label windows.

[0066] The construction time offset segment of each structural node is time-overlaid with the time windows of the three types of meteorological events within the corresponding project area. Specifically, using the day as the minimum time unit, the construction offset segment is intersected with the time window of each meteorological type, and the proportion of time overlap within the construction offset segment is calculated. A joint feature vector is constructed using three indicators: frozen soil overlap, dryness overlap, and main rainy season overlap to represent the potential correlation strength between the construction disturbance and meteorological factors at the current node. The overlap is calculated by dividing the intersection by the total length of the offset segment to generate a ratio value. For example, if the offset period is 10 days and 6 of them overlap with the frozen soil window, the frozen soil overlap is set to 0.6. The joint feature vectors of all structural nodes are input into the classification process to perform feature similarity clustering. Here, the K-means clustering algorithm based on Euclidean distance is used to classify all joint feature vectors. The classification goal is to group structural nodes with similar meteorological response patterns into the same category. Each type of construction response represents a group of structural nodes that exhibit similar shift characteristics when faced with meteorological disturbances. For example, some nodes exhibit significant shifts during the rainy season, while others exhibit a delay only during the frozen ground period. After clustering, the mean overlap of each type of node under each meteorological condition was calculated and used as the meteorological response shift weight for that response pattern. For example, the mean overlap for frozen ground, 0.1 for dry ground, 0.2 for dry ground, and 0.9 for the main rainy season, indicating that this type of node is highly sensitive to rainy season disturbances.

[0067] Each structural node is assigned a functional type label (e.g., "water intake," "sand trap," "culvert," etc.). Cluster categories are statistically associated with structural functional types to form a mapping relationship between functional types and meteorological response patterns. For each structural function, its distribution ratio across cluster categories is calculated to identify common meteorological response attributes for that structural function. For example, if "sand trap" type structural nodes are concentrated in cluster categories with high overlap with the main rainy season, their meteorological response offset attribute should be labeled "Main Rainy Season Offset Sensitive." Finally, each functional type is labeled with an offset attribute representing its primary meteorological response behavior. This will be used for meteorological response prediction and sequence adjustment in the subsequent dynamic construction map construction. This attribute labeling result should be directly bound to the structural node number and functional type fields, and a response weight parameter field can be added (e.g., offset weight: 0.3 for frozen soil, 0.2 for dry soil, 0.7 for rainy season).

[0068] In S4, the structural node set, functional dependency edge and meteorological response offset attributes are integrated to construct a multivariate construction control graph structure.

[0069] After completing the functional annotation of the structural nodes and the construction of the functional dependency edges, it is first necessary to perform a structural mapping of the established functional dependency edges, clarify the control order relationship between the structural nodes, and construct a complete directed semantic path structure. While completing the drawing of the path structure, all structural nodes are topologically sorted according to their depth level in the path structure, and each structural node is given a clear "scheduling trigger sequence". The scheduling trigger sequence is expressed in the form of a natural number. For example, the sequence number "1" represents the node at the starting position in the entire path diagram, that is, the first structural unit to start construction; the larger the number, the longer the upstream path that the node construction depends on, and the longer the corresponding construction sequence is. This sequence number will be used in the subsequent formulation of construction scheduling strategies and the generation of construction schedules as a basis for critical time control.

[0070] After constructing a complete directed semantic path structure, the meteorological response offset attributes extracted in the previous step must be associated with each structural node, thereby enabling differentiated weighting of the effects of meteorological disturbances on the structures within the control map. This binding process is performed based on the functional type annotated for each structural node in the identification step. For example, if a structural node is clearly labeled as a "high-level surge tank" functional unit in the design drawing and is classified as a "frozen soil-dominated response category" in historical construction offset data, the offset attribute value corresponding to this response category (e.g., a frozen soil disturbance weight of 0.7) is directly bound to the node's attribute field, forming the structural node's response offset label. Through this weighting mechanism, each node not only possesses static functional identification and connectivity logic but also carries dynamic environmental sensitivity information, providing a decision-making basis for subsequent dynamic scheduling adjustments and risk warnings. Ultimately, all of this information is integrated to construct a composite graph structure encompassing five elements: structural nodes, functional dependency edges, directed path structure, scheduling priority number, and response offset attributes. This structure is named the "construction control map structure." This graph structure fully expresses core information such as the logical position of structural nodes in the water supply functional chain, hydraulic connectivity constraints, construction execution sequence, and environmental response characteristics, forming an association channel that runs through design semantics, construction constraints, and environmental dynamics.

[0071] In S5, based on the construction log and meteorological data after the project starts, the order and accessibility status of the structural nodes in the multi-dimensional construction control map structure are adjusted to establish a dynamic construction control map.

[0072] Extract and analyze construction logs for each structural node in the multi-dimensional construction control map. After construction begins, a construction progress timeline record corresponding to the node's number should be generated. This record should include the construction start time, stage identifier, task completion mark, and descriptions of any abnormal conditions recorded during construction. This timeline record is extracted by collecting construction execution status change events from on-site construction management archives or electronic construction equipment on a daily or predefined construction cycle basis. After time alignment, these events are written into the construction timeline record set for each structural node. The construction progress timeline record indicates the node's progress in the construction task chain and whether it meets the conditions for advancing to the next stage. During this process, pay special attention to changes in functional description keywords in the construction log (e.g., from "caisson foundation" to "modified reinforced caisson") or significant deviations between measured terrain parameters and those in the design drawings (e.g., excavation face elevation deviation exceeding ±0.5 meters). Once such a change event is discovered, the dependent edges directly connected to the structural node should be adjusted sequentially. The adjustment logic is as follows: if the function adjustment of a node causes a change in the execution order of its functional role in the graph, the start and end node configurations of the dependent edge need to be updated; if the terrain change causes the originally planned node to be unable to be constructed on schedule, the sequential binding of the node also needs to be temporarily suspended until its reachability is recalibrated.

[0073] During the dynamic stage of construction scheduling, it is necessary to monitor the meteorological conditions in the construction area in real time to determine whether there are meteorological factors that affect the progress of construction. Establish a real-time meteorological observation channel corresponding to the geographical coordinates of the current construction location, and collect at least the following key meteorological elements: surface moisture, ground freezing depth, effective rainfall, etc. Subsequently, based on the meteorological response offset attributes of each structural node that have been marked in the previous step, retrieve its response offset weight for different meteorological types. Each response offset weight should be a numerical weight value obtained by calculating the pre-classified clustering model, ranging from 0 to 1. The higher the value, the higher the sensitivity of the node to this type of meteorological interference. To accurately determine whether a construction blockage has occurred, it is necessary to set a threshold for the meteorological response weight. For example, when the offset weight of a node's frozen soil response exceeds 0.65 and the currently observed surface freezing depth exceeds the set construction tolerance (e.g., 0.25 meters), the node is deemed unconstructable under the current meteorological conditions. The "threshold" here should be derived from statistical data on blockage conditions in historical construction projects. For example, by combining the offset weights of frozen soil construction failure nodes in 30 plateau projects with meteorological records, the point with the minimum average error can be selected as the basis for setting the weight threshold.

[0074] If a structural node is identified as unreachable under current weather conditions, its node status in the multi-dimensional construction control map structure must be modified to "unreachable." At the same time, to prevent the scheduling system from continuing to advance construction tasks for subsequent nodes that depend on this node, the system should recursively propagate downward along the dependency edge, automatically marking all subsequent structural nodes that depend on this node as unreachable, forming a recursive blocking propagation process. This marking must be maintained until the blocking condition is lifted, that is, the weather conditions return to the threshold range, or the node is restored to a constructible state through technical means (such as construction heating or anti-freeze treatment). After that, the system will automatically restore its status to "reachable" and perform status recovery and scheduling unlocking operations on all downstream nodes marked as unreachable due to the blocking.

[0075] In S6, a linkage adjustment channel between the BIM scheduling path and the dynamic construction control map is constructed, and the construction control map is embedded in the BIM planning task chain to generate a scheduling path rescheduling plan for construction tasks. Specifically, the following are included:

[0076] The linkage mechanism of the dynamic construction control map is embedded in the BIM planning task chain, and the correspondence between the task components and the structural nodes in the task chain is established. The specific approach is: for each structure or component with a construction task definition in the water conservancy project design drawing, a unique structural node index number must be assigned, and the index is recorded as a unique identifier in the task entry field of the task chain. The structural node index of the task component comes from the structural node set established in the aforementioned water flow semantic structure node extraction process. The index should be solidified together with the task scheduling template during the construction drawing annotation stage to ensure traceability during subsequent map linkage. The structural node index carries the geographical location information and functional semantic information of the structure, and synchronously binds its semantic path and dependent edge information in the multi-dimensional construction control map. After establishing this correspondence, each task component in the BIM task chain has a traceable map node mapping path, thus forming a structural linkage basis between the BIM scheduling logic and the dynamic map.

[0077] After building the mapping, it is necessary to set the linkage triggering rules for the state changes of the graph nodes. The state of each structural node in the graph may be in states such as "reachable", "unreachable", "in execution", "execution completed", etc. During the project advancement, when the state of the structural node changes from "reachable" to "unreachable" or vice versa, the state adjustment of the corresponding BIM plan task item needs to be triggered. For example: If the structural node A changes from "reachable" to "unreachable", and its corresponding task item ABC is in the "pending" state, ABC should be immediately marked as "blocked for scheduling", and the advancement authority and resource allocation logic of the task should be frozen. At the same time, in order to ensure the consistency of information transmission, a state-triggered cascading update mechanism should be set, that is, all downstream nodes in the graph that have a dependent edge connection relationship with the node will synchronously transmit the "unreachable" state and freeze the corresponding task items in turn. This transmission rule needs to be solidified as a logical operation module in the scheduling process, and a node state change log recording interface should be provided for project backtracking and scheduling re-evaluation. When a "task chain break" occurs in a BIM-planned task chain due to a blocked structural node status, local chain break identification and path replacement strategies should be immediately implemented. Path break segments are identified by searching the BIM task chain for all task entries with a "blocked pending scheduling" status. Based on their structural node indexes, the control graph is then tracked to see if there are consecutive interrupted nodes along their semantic paths. If so, the segment is identified as a "chain break." For each end of the chain break (a completed node at the front end and a reachable but unconnected node at the back end), a local path search is performed within the graph structure. The path search strategy should be based on the functional flow logic and spatial accessibility constraints between graph nodes, prioritizing geographically adjacent, functionally interchangeable, and currently reachable structural node combinations to reconstruct a new path connecting the nodes before and after the original chain break. Once the alternative path is confirmed, it is mapped back into the BIM task chain and appended to the original planned path as a new task chain. An updated plan is generated, clarifying the timelines, resource requirements, and construction sequence of each task.

[0078] When a structural node in the "unreachable" state returns to the "reachable" state due to factors such as weather recovery or human intervention, a state recovery insertion mechanism is executed to insert it into an available segment in the current BIM planned task chain. The criteria for segment insertion are: within the current task chain progress state, a time window that does not cause path logic conflicts, resource scheduling overlaps, and satisfies the start conditions of the dependent edge. For example, if structural node B returns to the "reachable" state and its predecessor node A has completed construction, it can be inserted into the available construction period between node CD and its successor node. If the segment is currently occupied by an alternative path, priority rules determine whether to roll back the alternative path or proceed with the restoration node task in parallel. Finally, after the insertion is complete, the construction drawing status, BIM task scheduling status, and construction progress log are synchronously updated to ensure consistency, ensuring the continuity, flexibility, and reliability of construction scheduling. This process is repeated based on real-time data, ultimately forming a dynamic, adaptive adjustment system for the BIM task scheduling chain driven by structural node status. This effectively supports real-time adjustment of construction task chains and the implementation of multi-path substitution strategies in complex environments such as plateau water conservancy projects.

[0079] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters and thresholds in the formulas are set by technicians in this field according to actual conditions.

[0080] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When loaded or executed on a computer, the processes or functions described in the embodiments of this application are fully or partially performed. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired means (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0081] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0082] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0083] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0084] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0085] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0086] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0087] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0088] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A full life cycle management method for water conservancy projects based on BIM and big data, characterized by: The steps include: S1: Obtain the water inlet and outlet properties, geographical location and elevation information of the water conservancy project structure, and establish a set of structural nodes with water flow function semantics; S2: Extract the semantic logical relationship between structural nodes and form the functional dependency edge of the node execution order; S3: Combine historical construction data with plateau meteorological conditions to extract structural nodes where actual construction deviates from pre-planned construction times, and analyze the corresponding meteorological response deviation attributes; S4: Fusion of structural node sets, functional dependency edges, and meteorological response offset attributes to construct a multivariate construction control graph structure; S5: Based on the construction log and meteorological data after the project starts, adjust the order and accessibility status of the structural nodes in the multi-dimensional construction control map structure to establish a dynamic construction control map; S6: Build a linkage adjustment channel between the BIM scheduling path and the dynamic construction control map, embed the construction control map into the BIM planning task chain, and generate a scheduling path rescheduling plan for construction tasks; In S4, the structural node set, functional dependency edge and meteorological response offset attributes are integrated to construct a multi-dimensional construction control graph structure, which specifically includes: The unidirectional sequence recorded in the functional dependency edge is mapped into a directed semantic path structure between nodes, and the scheduling trigger sequence is annotated. At the same time, based on the functional annotations carried by each structural node in the structural node set, the response offset attributes are assigned to the corresponding structural nodes, and a construction control map structure that includes water supply conditions, meteorological responses, and construction constraints is constructed. In S5, based on the construction log and meteorological data after the project starts, the order and accessibility status of the structural nodes in the multi-dimensional construction control map structure are adjusted to establish a dynamic construction control map. Specifically, the following steps are involved: After the target project is launched, the construction log records of each structural node are extracted, and the construction progress time sequence records are generated for the structural nodes in the multi-dimensional construction control map structure; In the construction progress time series records of the monitoring structure nodes, if there is an event of a change in the function description keyword or a change in the terrain parameters at the corresponding location, the dependent edges of the structure nodes will be adjusted sequentially; Obtain the real-time meteorological conditions of the construction area, and based on the response offset weight in the meteorological response offset attribute of the structure node, determine whether the construction of the corresponding structure node is blocked by the current meteorological conditions according to the preset weight threshold; If so, the blocked structural node and all subsequent nodes associated with the corresponding dependency edges will be marked as unreachable in the construction control graph until the construction blockage is resolved; In S6, a linkage adjustment channel between the BIM scheduling path and the dynamic construction control map is constructed, and the construction control map is embedded in the BIM planning task chain to generate a scheduling path rescheduling plan for construction tasks. Specifically, the following are included: Mark the structural node index corresponding to each task component in the BIM planning task chain and establish the corresponding relationship between the dynamic graph and the BIM scheduling logic; Set the information transmission rules triggered when the status of the structural nodes in the diagram changes, and adjust the BIM task progress status accordingly according to the node status changes; Locate the structural nodes marked as unreachable in the current BIM plan task chain, extract the broken task chain segments and search for local alternative paths, build a new continuous advancement path and generate an updated plan; When the unreachable structure node is restored to an executable state, the restored structure node is dynamically inserted into the accommodating section of the current task chain.

2. The method for managing the entire life cycle of a water conservancy project based on BIM and big data according to claim 1 is characterized in that: In S1, the water inlet and outlet properties, geographical location, and elevation information of the water conservancy project structure are obtained, and a set of structural nodes with water flow function semantics is established, specifically including: Mark all structures with water diversion or drainage design objectives in the water conservancy project design drawings, and determine the scope of the structural entities with water flow diversion functions; Compare the water flow direction arrows in the design drawing with the port connection directions of the structural entities to obtain and mark the water flow channel structural entity groups with spatial connectivity; Collect the terrain elevations at both ends of the geographical locations of the structural entities in the structural entity group and eliminate structural entities with backflow risks; Combining the functions, connectivity annotations and elevation difference judgment results of the structural entities, the structural entities that can form effective water flow chains in the engineering layout are identified, and based on the functional description keywords of the structural entities, the corresponding structural entities are marked as water flow function semantic structure nodes.

3. The method for managing the entire life cycle of a water conservancy project based on BIM and big data according to claim 1 is characterized in that: In S2, the semantic logical relationship between the structural nodes is extracted to form the functional dependency edges of the node execution order, which specifically include: Extract the structural nodes with water flow connectivity annotations from the structural node set, and annotate the functions of each structural node according to the corresponding functional description keywords; Based on the semantic logical relationship of the functions, the relative positions of all structural nodes in the functional process design are calibrated to establish construction sequence execution constraints; The construction sequence execution constraints between structural nodes are converted into a unidirectional sequence relationship, which stipulates that the start condition of downstream node construction depends on the completion of upstream node construction. Draw unidirectional connection edges for structural node pairs with unidirectional sequential relationships and mark them as functional dependency edges; Bind the functional dependency edges with the corresponding structural node numbers, and output a set of functional dependency edges with functional order constraint attributes.

4. The method for managing the entire life cycle of a water conservancy project based on BIM and big data according to claim 1 is characterized in that: In S3, historical construction data and plateau meteorological conditions are combined to extract structural nodes where actual construction deviates from the pre-planned construction time. The corresponding meteorological response deviation attributes are analyzed, including: The planned construction time and actual construction time corresponding to all semantic structure nodes with water supply function are extracted from the historical construction data set, and the interval between the planned construction time and the actual construction time is marked as the construction time offset segment. According to the location of the structural nodes and the planned and actual construction time, the historical meteorological observation data of the plateau construction area is matched. The historical meteorological observation data at least includes the time of the occurrence of frozen soil, the time of the dry period, the time of the main rainy season, and the corresponding duration; Overlapping classification processing is performed on the construction time data and meteorological observation data of the structural nodes to divide the historical construction response structural nodes with similar meteorological-driven response behaviors; The classification processing results are associated with the functional type labels of the historical construction structure nodes, and the meteorological response offset attributes corresponding to different functional structure nodes are marked.

5. The method for managing the entire life cycle of a water conservancy project based on BIM and big data according to claim 4 is characterized in that: The overlapping classification process of the construction time data and meteorological observation data of the structural nodes is performed to divide the historical construction response structural nodes with similar meteorological driven response behaviors into: The structural nodes in the historical construction dataset are classified into corresponding construction projects according to their geographical locations; Extract the construction time offset segments of the construction project during the entire construction period and synchronize them with the occurrence times of different meteorological types in the historical meteorological observation data of the corresponding area on the time axis; The overlap index is calculated based on the intersection ratio of the construction time offset segment and the time windows of different meteorological conditions, and the overlap indexes of different meteorological conditions are integrated into a joint feature. According to the feature similarity of the joint features, the response behavior of the joint features is classified, and the mean value of the joint features of the structural nodes of different categories in all construction projects after classification is calculated as the response offset weight of the corresponding meteorological conditions, and the response offset weight is used as the meteorological response offset attribute of the structural nodes of the corresponding category.

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