Whole-chain integrated service system for engineering construction project

Abstract

This invention relates to the field of engineering construction technology, and more particularly to an integrated service system for the entire chain of engineering construction projects. The system includes: a modeling and processing module that acquires and preprocesses multi-source data encompassing design, manufacturing, transportation, construction, and environmental categories, thereby constructing a state-space model and corresponding state transition relationships; a constraint construction module that generates cross-stage constraint relationships based on the preprocessed multi-source data and maps them to construction tasks to form a task constraint set; a scheduling generation module that solves the constraints to output an initial scheduling scheme; real-time state updates and violation identification to identify affected task subsets; and finally, a scheduling adjustment module that performs local rescheduling and synchronously updates the model. In this invention, multi-stage and environmental data are collected, a state model and transition relationships are constructed, task constraints are generated based on cross-stage constraints, and scheduling updates and local rescheduling are implemented, combined with working conditions to achieve dynamic adjustments to construction, thus solving the problem of deviations in traditional construction plans.

Description

Technical Field

[0001] This invention relates to the field of engineering construction technology, and in particular to an integrated service system for the entire chain of engineering construction projects. Background Technology

[0002] As engineering construction projects become larger and more complex, the project implementation process gradually covers multiple stages such as design, manufacturing, transportation and construction. The need for data correlation and collaboration between each stage is constantly increasing. In existing technologies, construction tasks are usually managed through information systems, and scheduling optimization is achieved by combining schedule planning and resource allocation.

[0003] Traditional engineering construction projects mostly adopt a continuous planning and execution method. However, because the constraints of environmental conditions and component transportation status on the feasibility of construction are not considered, a mismatch between the construction plan and the actual working conditions is caused. Summary of the Invention

[0004] To overcome the above shortcomings, this invention provides an integrated service system for the entire chain of engineering construction projects, aiming to improve the problem that traditional engineering construction projects mostly adopt a continuous planning and execution method, which easily leads to a mismatch between the construction plan and the actual working conditions.

[0005] This invention provides the following technical solution: a full-chain integrated service system for engineering construction projects includes: The modeling and processing module is used to acquire multi-source data, perform preprocessing operations on the multi-source data, and construct a state space model and the corresponding state transition relationship based on the preprocessed multi-source data. The multi-source data includes design stage data, manufacturing stage data, transportation stage data, construction stage data and environmental data. The state space model is a multi-dimensional state vector model constructed based on the multi-source data. The state transition relationship is used to describe the evolution relationship of state variables between adjacent time steps. The constraint construction module is used to construct cross-stage constraint relationships based on preprocessed multi-source data, and map the cross-stage constraint relationships to construction tasks to generate a set of task constraints. The scheduling generation module is used to solve constraints based on the state space model, state transition relationships, and task constraint set to generate a scheduling scheme for construction tasks. The state update module is used to acquire multi-source data at the current moment, update the state space model based on the multi-source data at the current moment through state transition relationships, and determine whether the constraints are violated based on the updated state space model, cross-stage constraint relationships and task constraint set. When the constraints are violated, the affected subset of construction tasks is identified. The scheduling adjustment module is used to perform local rescheduling processing on the affected subset of construction tasks to obtain an updated scheduling scheme. Based on the updated scheduling scheme as the state update input, the state space model is updated through the state transition relationship. The local rescheduling processing is limited to the time range and resource scope corresponding to the affected subset of construction tasks.

[0006] By adopting the above technical solution, and by acquiring data from the design stage, manufacturing stage, transportation stage, construction stage, and environmental data, and constructing a state-space model and state transition relationships, while generating a task constraint set based on cross-stage constraint relationships and executing scheduling scheme generation, state updates, and local rescheduling processing, a dynamic response mechanism for construction tasks constrained by both environmental parameters and transportation status is realized. This improves the problem that traditional engineering construction projects mostly adopt a continuous planning execution method, which fails to consider the constraints of environmental conditions and component transportation status on construction feasibility, resulting in a mismatch between construction plans and actual operating conditions.

[0007] The present invention has the following beneficial effects: 1. In this invention, by acquiring design stage data, manufacturing stage data, transportation stage data, construction stage data, and environmental data, and constructing a state space model and state transition relationships, and simultaneously generating a task constraint set based on cross-stage constraint relationships, and executing scheduling scheme generation, state updates, and local rescheduling processing, a dynamic response mechanism for construction tasks constrained by both environmental parameters and transportation status is realized. This improves the problem that traditional engineering construction projects mostly adopt a continuous planning execution method, which fails to consider the constraints of environmental conditions and component transportation status on construction feasibility, resulting in a mismatch between construction plans and actual operating conditions.

[0008] 2. In this invention, cross-stage constraint relationships are constructed based on design parameters, manufacturing progress, transportation status, and environmental parameters, and mapped to construction tasks to form a set of task constraints. This enables the transfer of constraints from component transportation status and environmental conditions to construction tasks, thereby improving the problem that traditional engineering construction processes mostly adopt independent constraint modeling for construction stages. Since transportation status and environmental conditions are not used as the basis for construction triggering, the arrangement of construction tasks is disconnected from the actual execution conditions.

[0009] 3. In this invention, by performing local rescheduling within the affected subset of construction tasks and limiting the scope of action, the targeted adjustment of construction disturbances caused by environmental changes and transportation status changes is achieved. This improves the problem that traditional engineering scheduling adjustments mostly adopt an overall adjustment approach, which fails to distinguish the scope of tasks affected by changes in the environmental window, resulting in an excessively large scheduling adjustment range and frequent resource changes.

[0010] 4. In this invention, by constructing a state-space model and state transition relationships, dynamic coupling expression of multi-stage data is realized; and a constraint transmission mechanism between design, manufacturing, transportation, construction and environment is established through cross-stage constraint relationships; at the same time, combined with a local rescheduling strategy with limited scope of action, targeted scheduling adjustment is realized only for disturbed tasks, thereby avoiding global scheduling disturbances. Attached Figure Description

[0011] Figure 1 This is a schematic diagram of the architecture of the integrated service system for the entire chain of engineering construction projects proposed in this invention; Figure 2 This is a flowchart illustrating the integrated service method for the entire chain of engineering construction projects proposed in this embodiment of the invention. Detailed Implementation

[0012] 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.

[0013] Example 1: In the first embodiment of the present invention, the present invention provides an integrated service system for the entire chain of engineering construction projects, such as... Figure 1 As shown, it includes a modeling and processing module, which is used to acquire multi-source data, perform preprocessing operations on the multi-source data, and construct a state space model and the corresponding state transition relationship based on the preprocessed multi-source data. The multi-source data includes design stage data, manufacturing stage data, transportation stage data, construction stage data and environmental data. The state space model is a multi-dimensional state vector model constructed based on the multi-source data. The state transition relationship is used to describe the evolution relationship of state variables between adjacent time steps. Furthermore, in the modeling and processing module, the steps for acquiring multi-source data include: Data sources for design, manufacturing, transportation, construction, and environmental phases are identified and categorized. Establish separate data access interfaces for design phase data, manufacturing phase data, transportation phase data, construction phase data, and environmental data; Data collection is performed on design phase data, manufacturing phase data, transportation phase data, construction phase data, and environmental data through data access interfaces; The collected design, manufacturing, transportation, construction, and environmental data are structured, packaged, and time-stamped.

[0014] Specifically, the data sources for design, manufacturing, transportation, construction, and environmental phases are first identified and classified to determine the origins and structural characteristics of different data types. Then, data access interfaces are established for each data type, and data acquisition and processing are performed through these interfaces. The acquired data includes raw data values ​​and corresponding data generation time information. After data acquisition, the data from each phase is structured and encapsulated, converting data from different sources into a standardized data structure and assigning a time stamp to each data entry. The time stamp can be represented as t. i , where t i This represents the acquisition time corresponding to the i-th data point. The time identifier is recorded by the data acquisition system and is used to reflect the position of the data on a unified timeline. During the structured encapsulation process, various types of data are represented as data records D in a unified format. i ={X i ,t i}; where X i This indicates that the corresponding data content originates from any one of the following: design parameters, manufacturing progress, transportation status, construction status, or environmental parameters. After the above processing, a multi-source structured dataset with time stamps is obtained. This dataset serves as the input foundation for subsequent time alignment processing, spatial unification processing, and state-space model construction. It ensures the consistency of data across different stages in the time dimension and the relevance in the subsequent extraction of state variables, thereby supporting the construction of the state-space model and state transition relationships. The state transition relationships are represented as follows: S (k+1) =f(S k U k ); Among them, S k U represents the state vector at time k. k This represents the state update driver term, which consists of the scheduling scheme and cross-stage constraints. For offshore wind turbine tower foundation construction scenarios, the design phase data includes wind turbine tower foundation structural design parameters and hoisting operation design parameters; the manufacturing phase data includes tower manufacturing progress and prefabricated component production status; the transportation phase data includes transport vessel location, vessel load, and sailing progress; the construction phase data includes hoisting operation progress, concrete pouring progress, and construction equipment operating status; and the environmental data includes offshore wind speed, wave height, and tidal phase data. All of the above data are acquired through corresponding acquisition terminals and structured and packaged according to the aforementioned rules.

[0015] Furthermore, in the modeling and processing module, the steps for performing preprocessing operations on multi-source data include: Perform time alignment processing on multi-source data to map the multi-source data to a unified time scale; Perform spatial coordinate transformation on multi-source data to unify the data into the same coordinate system; Perform outlier detection, missing value compensation, and standardization on multi-source data.

[0016] Specifically, during the modeling process, when performing preprocessing operations on the acquired multi-source data, the first step is to use a dataset D with time stamps. i ={X i ,t i}; as input, where X i This indicates data originating from the design, manufacturing, transportation, construction, or environmental data phases. i This indicates the corresponding collection time. By uniformly processing the time stamps of all data, a unified time scale is selected, and a time series T={t1,t2,...,t} is constructed. n The original data is mapped onto this time series to form an aligned data sequence. ;where f t This represents a time alignment mapping function that projects data from different sources onto a unified time axis based on time signatures, resulting in a time-consistent multi-source data set. After time alignment, spatial coordinate transformation is performed on the multi-source data to map the spatial location information involved in various data types to the same coordinate system. Let the original spatial coordinates be p. i The unified coordinates are Through space transformation function ; Implement coordinate transformation, where f s This represents a predefined coordinate transformation relationship used to eliminate spatial representation differences between different data sources. After achieving temporal and spatial unification, outlier detection is performed on the data, and the mean is obtained by calculating the statistical characteristics of the data sequence. with standard deviation And according to the discrimination rules ; Identify outlier data, where k is a preset threshold coefficient. Outlier data is corrected through interpolation or replacement with neighboring data. For missing data, an interpolation function is constructed. Compensation will be provided, including This represents a time-series-based missing value compensation function. After anomaly handling and missing value compensation, it performs data standardization and transforms the relationships... Data of different dimensions are mapped to a unified scale. After time alignment, spatial unification, anomaly correction and standardization, a preprocessed multi-source data set is obtained. This data set is used to extract design parameters, manufacturing progress, transportation status, construction status and environmental parameters, and further construct state variables in the state space model, thereby providing a unified and computable data foundation for the construction of the state space model and state transition relationship. For offshore wind turbine tower construction scenarios, spatial coordinate transformation processing converts the BeiDou positioning coordinates of transport vessels, the operational coordinates of construction vessels, and the engineering coordinates of the tower installation location into a unified construction plane coordinate system under the WGS84 coordinate system, eliminating spatial coordinate differences among multiple devices and platforms in offshore construction scenarios; outlier detection uses the 3σ criterion to identify extreme sea state anomalies for high-frequency fluctuating environmental data such as offshore wind speed and wave height, ensuring the accuracy of subsequent state modeling.

[0017] Furthermore, in the modeling module, the steps for constructing a state-space model and the corresponding state transition relationships based on the preprocessed multi-source data include: Design parameters, manufacturing schedule, transportation status, environmental parameters, and construction status are extracted from the preprocessed multi-source data. Variable coding is performed on design parameters, manufacturing schedule, transportation status, environmental parameters, and construction status; A multi-dimensional state vector is constructed based on design parameters, manufacturing schedule, transportation status, environmental parameters, and construction status, and a state space model is generated. State transition relationships are constructed based on the state-space model, and the state-space model is associated between adjacent time steps; The state update driving term in the state transition relationship is constructed based on the scheduling scheme and cross-stage constraint relationship.

[0018] Specifically, after completing the multi-source data preprocessing, a dataset with a unified time scale and coordinate system is used as input to extract design parameters, manufacturing progress, transportation status, environmental parameters, and construction status, which are denoted as X. d X m X t X e and X c Each parameter originates from structured data records of the corresponding stage and is synchronized using time stamps. Subsequently, variable encoding processing is performed on these parameters, mapping different types of data into computable numerical variables, forming a set of encoded state variables Z. d Z m Z t Z e and Z c Based on this, construct a multidimensional state vector. Where k represents the discrete time step; for the offshore wind turbine tower foundation construction scenario, Z e Includes three types of marine-specific environmental state variables: sea wind speed, wave height, and tidal phase. t Includes the position and load state variables of transport vessels and crane vessels, Z c The state vectors, including those for hoisting and concrete pouring operations, comprehensively cover the environmental, resource, and task-related states of offshore wind turbine tower foundation construction. While not directly applicable to onshore construction scenarios, the state vectors characterize the overall state of the engineering system at the current moment. The state vectors of all time steps constitute a state-space model, upon which state transition relationships between adjacent time steps are established, using state transition functions. ; to achieve state evolution, where The state update driver term originates from the scheduling scheme and cross-stage constraints. Specifically, the task execution order, timing, and resource allocation information in the scheduling scheme are mapped to form scheduling driver variables, and the cross-stage constraints are resolved to form constraint driver variables. Together, they constitute the state update driver term. This is used to reflect the impact of external scheduling decisions and constraints on system state changes. The state space model is dynamically correlated in the time dimension through the aforementioned state transition relationships. The resulting state space model and its state transition relationships serve as the basic input for subsequent scheduling generation and state updates. This is used to establish state correlation constraints during constraint solving and to support state updates and scheduling adjustments based on real-time data during subsequent operation. The state transition function... The system simultaneously incorporates three types of inputs: marine environmental changes, vessel scheduling decisions, and cross-stage constraints. This allows it to reflect the impact of extreme sea state changes such as wind, waves, and tides on offshore wind turbine tower foundation construction tasks, and to achieve coupled updates of environmental constraints, vessel resource availability, and construction progress.

[0019] The constraint construction module is used to construct cross-stage constraint relationships based on preprocessed multi-source data, and map the cross-stage constraint relationships to construction tasks to generate a set of task constraints. Furthermore, in the constraint construction module, the steps for constructing cross-stage constraint relationships based on preprocessed multi-source data include: Design parameters, manufacturing schedule, transportation status, environmental parameters, and construction status are extracted from the preprocessed multi-source data. Constraint triggering conditions are identified based on design parameters, manufacturing schedule, transportation status, and environmental parameters. Associate the constraint triggering conditions with the construction tasks in the construction state; Establish a correlation between design parameters, manufacturing schedule, transportation status, environmental parameters and construction tasks; Generate cross-stage constraint relationships based on the correlation between constraint triggering conditions and construction tasks; Establish constraint transmission paths between design stage data, manufacturing stage data, transportation stage data, construction stage data, and environmental data based on cross-stage constraint relationships, and update the task constraint set based on the constraint transmission paths.

[0020] Specifically, taking the preprocessed multi-source construction dataset as input, the coded design parameters X are extracted from it. d Manufacturing progress X m Transport Status X t Environmental parameter X e and construction status X c Based on this, constraint triggering conditions are identified for design parameters, manufacturing schedule, transportation status, and environmental parameters, and a decision function is constructed. ; Generate trigger result C i， C i This represents the i-th constraint triggering condition, whose value is obtained by comparing the corresponding parameter with the preset judgment rule. It is used to characterize whether the preconditions for the execution of the construction task are met. Then, the constraint triggering condition C is... i Set of construction tasks in the construction state To establish associations, a mapping relationship is created. Determine the degree of correlation between constraint triggering conditions and construction tasks, whereby... This represents the association result of the i-th constraint triggering condition acting on the j-th construction task. This association is generated based on the matching of the execution conditions of the construction task and the parameter source relationship. After the association is completed, a unified association structure is formed between design parameters, manufacturing schedule, transportation status, environmental parameters and construction tasks, and a set of cross-stage constraint relationships is generated based on this association structure. This is used to describe the constraints imposed by multi-stage data on construction tasks. Furthermore, based on cross-stage constraint relationships, a constraint transmission path is constructed, representing the constraint relationships between design stage data, manufacturing stage data, transportation stage data, construction stage data, and environmental data as a transmission sequence. For offshore wind turbine tower foundation construction scenarios, the constraint propagation path enables the automatic propagation of environmental constraints such as wind, waves, and tides, as well as vessel resource constraints, to construction tasks such as hoisting and pouring. This constraint propagation mechanism is specialized for offshore wind power construction scenarios and cannot be directly applied to other engineering scenarios. The constraint propagation path reflects the process of transmitting upstream stage state changes to construction tasks, and updates the task constraint set based on this propagation path to obtain a task constraint set containing cross-stage constraint information. This set is used to construct constraint expressions during subsequent scheduling generation and to perform constraint determination during state updates, thereby achieving... Multi-stage data exerts a constraint-driven effect on the execution of construction tasks. For example, in the environmental constraint judgment, when the wind speed is greater than the preset threshold or the wave height exceeds the preset range, the corresponding hoisting construction task is determined not to meet the execution conditions. The wind speed threshold can be set to 12 m / s. For the offshore wind turbine tower foundation construction scenario, the cross-stage constraint relationship includes: the constraint c1 of the ship status during the transportation stage on the hoisting operation, the constraint c2 of the offshore wind and wave environment on the hoisting operation, and the constraint c3 of the tidal position relative to the concrete pouring operation. All of the above constraints are identified and associated with the construction task through constraint triggering conditions and included in the cross-stage constraint relationship set C.

[0021] Furthermore, within the constraint construction module, the steps for mapping cross-phase constraint relationships to construction tasks include: The construction tasks are divided into task nodes; Match the constraint triggering conditions in the cross-stage constraint relationship with the construction task nodes; Assign constraint triggering conditions to matching construction task nodes; Associating construction task nodes with corresponding constraint triggering conditions forms a task-level constraint structure; The task-level constraint structures are summarized to generate a task constraint set.

[0022] Specifically, taking the set of construction tasks and the set of cross-stage constraint relationships as input, the construction tasks are first divided into task nodes. Each construction task is divided into several task nodes according to the execution process, forming a node set. , where N j Let j represent the j-th construction task node. This node is obtained by parsing the construction status data and carries the corresponding time information and execution conditions. Based on this, the set of constraint triggering conditions in the cross-stage constraint relationship is... With task node set Perform matching processing by constructing a matching function. ; The matching results are obtained, where This represents the matching relationship between the i-th constraint trigger condition and the j-th task node. This matching relationship is determined based on the parameter source corresponding to the constraint trigger condition and the execution attributes of the task node. After obtaining the matching result, the constraint trigger conditions that satisfy the matching relationship are assigned to the corresponding construction task nodes, forming a node-level constraint mapping relationship, and further establishing the association structure between task nodes and constraint trigger conditions. ;in This represents the task-level constraint structure corresponding to the j-th task node. This structure describes the multi-source constraints that the task node experiences during execution. After completing the constraint association for all task nodes, the task-level constraint structures are summarized to form a task constraint set. This set is used for constructing constraint expressions and determining state updates in subsequent scheduling solutions. The task constraint set contains the constraint conditions and matching relationships corresponding to each construction task node. This result serves as the constraint input in the subsequent scheduling generation process, used to construct the constraint expressions of scheduling variables and participate in constraint solving. At the same time, it is used to determine whether the construction task meets the execution conditions during the state update process, thereby realizing the fine mapping of cross-stage constraints to the construction task level and constraint-driven scheduling. For the offshore wind power tower foundation construction scenario, the construction task nodes are divided into tower transportation nodes, crane vessel positioning nodes, tower hoisting nodes, and foundation concrete pouring nodes, which are matched and mapped with ship transportation constraints, wind and wave hoisting constraints, and tidal pouring constraints, respectively, to achieve the accurate implementation of cross-stage constraints to construction task nodes.

[0023] The scheduling generation module is used to solve constraints based on the state space model, state transition relationships, and task constraint set to generate a scheduling scheme for construction tasks. Furthermore, in the scheduling generation module, the steps for constraint solving based on the state-space model, state transition relationships, and task constraint sets include: Scheduling variables are determined based on the set of construction tasks. These scheduling variables include the task execution order, task start time, and resource allocation relationships. Construct constraint expressions based on the task constraint set; State-related constraints are constructed based on the state-space model and state transition relationships, and these constraints are incorporated into the constraint expressions. Constraint solving is performed based on scheduling variables and constraint expressions. Constraint solving can be performed using integer programming, heuristic algorithms, or constraint propagation methods. A scheduling scheme for construction tasks is generated based on the constraint solution results.

[0024] Specifically, taking the set of construction tasks, the state-space model, and the set of task constraints as input, the scheduling variables are first determined based on the set of construction tasks. ;in ; indicates the execution order of the j-th task. Task start time and resource allocation relationships Task constraint set Used to construct constraint expressions The state-space model and state transition relations are used to generate state-related constraints. The state-related constraints are expressed through the state vector. With state transition function Establish and associate state constraints. With task constraint expressions The combined constraint expression is obtained by merging. Based on this, a constraint-solving algorithm is used. Solving the scheduling variables Obtain the optimal or feasible scheduling result that satisfies both task constraints and state constraints. The solution results include the execution order, start time, and resource allocation scheme of each construction task. Subsequently, the scheduling results are input into the state update module to drive the update of the state space model and the local rescheduling process of the scheduling adjustment module. The scheduling scheme is used to guide the execution order and resource allocation of construction tasks to ensure that construction tasks are completed efficiently and in a coordinated manner under cross-stage constraints.

[0025] The state update module is used to acquire multi-source data at the current moment, update the state space model based on the multi-source data at the current moment through state transition relationships, and determine whether the constraints are violated based on the updated state space model, cross-stage constraint relationships and task constraint set. When the constraints are violated, the affected subset of construction tasks is identified. Furthermore, in the state update module, the steps for obtaining multi-source data at the current moment include: Determine the time stamp corresponding to the current moment based on a unified time scale; Data collection is triggered based on time markers for design phase data, manufacturing phase data, transportation phase data, construction phase data, and environmental data. Obtain the design phase data, manufacturing phase data, transportation phase data, construction phase data, and environmental data corresponding to the current moment; Associate the current time stamp with the acquired data; The data associated with time markers are integrated to generate multi-source data for the current moment.

[0026] Specifically, in the state update module, the current moment is first determined using a unified time scale. The corresponding time stamp is used as an index to trigger the processing of design phase data. Manufacturing stage data Transportation phase data Construction phase data and environmental data The collected data is structured, encapsulated, and associated with time stamps to generate multi-source data for the current moment. Based on state-space model and state transition relationship The updated state is obtained by updating the state vector at the current time step. Then based on the updated state vector Cross-stage constraint relationships and task constraint set Perform constraint determination using the determination function. Identify the affected subset of construction tasks. For offshore wind turbine tower foundation construction scenarios, the conditions for determining constraint violations include: wind speed or wave height exceeding the safety threshold for hoisting operations, hoisting task progress delay exceeding a preset threshold, vessel position deviating from the work area, and equipment load exceeding safety limits. These triggering conditions are specific to offshore construction scenarios, and the output update status... This is used to drive the scheduling adjustment module to locally reschedule a subset of affected construction tasks, and to serve as input for the state update in the next time step. This processing is used to reflect the impact of construction progress and environmental changes on construction tasks in real time, realizing dynamic management of construction scheduling driven by multi-source information. Each dataset... The state vector is collected by the monitoring and management system at the corresponding stage and packaged in a unified format. Each component corresponds to the state of the construction task, resource consumption, and environmental conditions. The multi-source data is mapped to the state space model through the state transition function f.

[0027] Furthermore, in the state update module, the steps for updating the state space model based on the multi-source data at the current moment through state transition relationships include: Extract the state vector corresponding to the current moment from the state-space model; Map the multi-source data at the current moment to the state variables corresponding to the state vector; Based on the state transition relationship, perform state update calculation on the state vector corresponding to the current time and the multi-source data at the current time; Update the state variables based on the state update calculation results; Write the updated state variables into the state space model.

[0028] Specifically, in the state update module, the process begins with the state space model. Extract the current time Corresponding state vector Multi-source data at the current moment Mapping to the state vector The corresponding state variables are determined through state transition relationships. ; Perform update calculations on the state vector, where The components represent design parameters, manufacturing schedule, transportation status, construction status, and environmental parameters. Each component is obtained from the corresponding stage data acquisition system and encapsulated in a structured manner. The function f maps the multi-source data into state space increments, and the updated state variables... Write into the state space model The updated output status is used by the subsequent scheduling adjustment module to identify the affected construction task subset and perform local rescheduling. It also provides input for the status update of the next time step. This process realizes dynamic management of construction progress and environmental changes driven by multi-source information, keeping the status of construction tasks synchronized with actual construction and environmental conditions, and ensuring the real-time performance and accuracy of the scheduling plan. For the offshore wind power tower foundation construction scenario, the current environmental data is collected in real time through offshore buoy meteorological stations, the ship status data is collected through the AIS system and Beidou positioning terminal, and the construction progress data is collected through on-site video monitoring and BIM progress comparison system, ensuring the real-time performance and accuracy of data in the offshore construction scenario.

[0029] The scheduling adjustment module is used to perform local rescheduling for the affected subset of construction tasks, obtain an updated scheduling scheme, and update the state space model based on the updated scheduling scheme as the state update input through the state transition relationship. The local rescheduling is limited to the time range and resource scope corresponding to the affected subset of construction tasks. Furthermore, in the scheduling adjustment module, the steps for performing local rescheduling on the affected subset of construction tasks to obtain an updated scheduling scheme include: Extract the task nodes corresponding to the affected subset of construction tasks from the set of construction tasks, as well as the associated constraints from the set of task constraints; A local scheduling problem is constructed based on the task nodes and associated constraints of the affected construction task subset. The time range and resource scope of the local scheduling problem are limited. At the same time, the scheduling results of construction tasks not included in the affected construction task subset are retained, and the local scheduling problem is limited to the state variables corresponding to the affected construction task subset. The time constraints, resource constraints, and process sequence constraints in the local scheduling problem are transformed into a standardized set of constraints. Based on the standardized constraint set, the constraint solution is performed on the affected subset of construction tasks to generate candidate scheduling sequences; Select scheduling sequences that satisfy the task constraint set from the candidate scheduling sequences and use them as the updated scheduling scheme.

[0030] Specifically, for offshore wind turbine tower foundation construction scenarios, the affected subset of construction tasks includes hoisting and pouring operations that are affected by sudden environmental changes such as wind, waves, and tides, or abnormal ship resources. This is first addressed by examining the set of construction tasks. Extract the affected construction task subset Corresponding task nodes and task constraint set The problem of constructing a local scheduling problem for a subset of affected tasks under inter-correlation constraints. ;in Represents a set of task nodes. This represents the set of constraints corresponding to a node, including time constraints, resource constraints, and process sequence constraints. Indicates the scope of resources involved in local scheduling. This refers to a local time frame; local scheduling problems only affect the state variables of the affected tasks. Meanwhile, the scheduling results corresponding to unaffected tasks are retained as fixed boundary conditions, and the constraint set is standardized into constraint expressions. ;in Representing local scheduling variables, including task start time, execution order, and resource allocation relationships, constraint solving is performed based on standardized constraint expressions. The function f can be the scheduling optimization objective function, such as minimizing the total project duration or resource conflicts, and the constraint solution yields the candidate scheduling sequence. The final scheduling sequence that satisfies the task constraint set is selected from the candidate sequences. As an update scheduling scheme, this scheme is used as input for subsequent state update modules to update the state space model through state transition relationships. This mechanism enables local scheduling adjustments to affected task subsets while maintaining the scheduling stability of unaffected tasks, thereby improving the dynamic response capability and execution accuracy of construction task scheduling. This local rescheduling mechanism can quickly respond to sudden changes in sea conditions and operation windows in offshore wind power construction scenarios, ensuring that the overall construction progress, vessel resource utilization rate, and safety constraints meet the requirements, and that local adjustments do not disrupt the overall scheduling closed loop.

[0031] Example 2: In the second embodiment of the present invention, the present invention provides a whole-chain integrated service method for engineering construction projects, such as... Figure 2 As shown, it includes the following steps: S1. Acquire multi-source data, perform preprocessing operations on the multi-source data, and construct a state space model and the corresponding state transition relationship based on the preprocessed multi-source data. The multi-source data includes design stage data, manufacturing stage data, transportation stage data, construction stage data, and environmental data. S2. Construct cross-stage constraint relationships based on preprocessed multi-source data, and map the cross-stage constraint relationships to construction tasks to generate a task constraint set; S3. Based on the state-space model, state transition relationships, and task constraint set, perform constraint solving to generate a scheduling scheme for construction tasks; S4. Obtain multi-source data at the current moment, update the state space model based on the state transition relationship based on the multi-source data at the current moment, and determine whether the constraint conditions are violated based on the updated state space model, cross-stage constraint relationship and task constraint set. When the constraint conditions are violated, identify the affected construction task subset. S5. Perform local rescheduling for the affected subset of construction tasks to obtain an updated scheduling scheme. Based on the updated scheduling scheme as the state update input, update the state space model through the state transition relationship.

[0032] In the construction of deep-water wind power foundations in extremely cold sea areas, frequent wind and waves, long transportation cycles, and limited construction platform resources can easily lead to mismatches in construction tasks, schedule delays, and untimely responses to environmental impacts. To address these issues, the integrated end-to-end service method for engineering construction projects provided by this invention is adopted, the process of which is as follows: Figure 2 As shown. The specific implementation process of this method is as follows: First, data from the design, manufacturing, transportation, construction, and environmental phases are acquired. Time alignment, spatial unification, anomaly correction, and standardization are performed on the multi-source data. Then, a state space model and state transition relationships are constructed based on the preprocessed multi-source data to ensure that the data at each stage remains consistent under complex sea conditions and long-cycle transportation conditions, providing a reliable data foundation for full-chain scheduling. Then, based on the preprocessed multi-source data, the constraint triggering conditions are identified, and the constraints are mapped to the construction task nodes to generate a set of task constraints. This enables a fine-grained mapping of cross-stage constraints to the task level, allowing construction tasks to be executed in a coordinated manner even under limited resources and environmental conditions. This reflects the innovative constraint adaptation for niche construction scenarios in deep-sea and low-temperature marine areas. Next, the constraints are solved by combining the state space model, state transition relationship and task constraint set to generate a construction task scheduling scheme, optimize the task execution order and resource allocation, and reduce task conflicts and waiting time in extreme environments, thereby improving construction efficiency and safety. Subsequently, multi-source data at the current moment is acquired, the state space model is updated through state transition relationships, and the updated state and constraint set are used to determine whether the constraints are violated and identify the affected construction task subset, thereby realizing real-time dynamic response to changes in construction progress, sea conditions and transportation status, and ensuring the agility of construction scheduling. Finally, local rescheduling is performed on the affected subset of construction tasks to generate an updated scheduling scheme. The updated scheme is then used as input to update the state space model through state transition relations, enabling local tasks to be flexibly adjusted under global constraints while maintaining the stable scheduling of unaffected tasks. This achieves dynamic optimization and refined management under extreme marine construction conditions.

[0033] Finally, it should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A full-chain integrated service system for engineering construction projects, characterized in that: include: The modeling and processing module is used to acquire multi-source data, perform preprocessing operations on the multi-source data, and construct a state space model and the corresponding state transition relationship based on the preprocessed multi-source data. The multi-source data includes design stage data, manufacturing stage data, transportation stage data, construction stage data and environmental data. The state space model is a multi-dimensional state vector model constructed based on the multi-source data. The state transition relationship is used to describe the evolution relationship of state variables between adjacent time steps. The constraint construction module is used to construct cross-stage constraint relationships based on preprocessed multi-source data, and map the cross-stage constraint relationships to construction tasks to generate a set of task constraints. The scheduling generation module is used to solve constraints based on the state space model, state transition relationships, and task constraint set to generate a scheduling scheme for construction tasks. The state update module is used to acquire multi-source data at the current moment, update the state space model based on the multi-source data at the current moment through state transition relationships, and determine whether the constraints are violated based on the updated state space model, cross-stage constraint relationships and task constraint set. When the constraints are violated, the affected subset of construction tasks is identified. The scheduling adjustment module is used to perform local rescheduling processing on the affected subset of construction tasks to obtain an updated scheduling scheme. Based on the updated scheduling scheme as the state update input, the state space model is updated through the state transition relationship. The local rescheduling processing is limited to the time range and resource scope corresponding to the affected subset of construction tasks.

2. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the modeling and processing module, the steps for acquiring multi-source data include: Data sources for design, manufacturing, transportation, construction, and environmental phases are identified and categorized. Establish separate data access interfaces for design phase data, manufacturing phase data, transportation phase data, construction phase data, and environmental data; Data collection is performed on design phase data, manufacturing phase data, transportation phase data, construction phase data, and environmental data through data access interfaces; The collected design, manufacturing, transportation, construction, and environmental data are structured, packaged, and time-stamped.

3. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the modeling processing module, the steps for performing preprocessing operations on multi-source data include: Perform time alignment processing on multi-source data to map the multi-source data to a unified time scale; Perform spatial coordinate transformation on multi-source data to unify the data into the same coordinate system; Perform outlier detection, missing value compensation, and standardization on multi-source data.

4. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the modeling module, the steps of constructing a state-space model and the corresponding state transition relationships based on the preprocessed multi-source data include: Design parameters, manufacturing schedule, transportation status, environmental parameters, and construction status are extracted from the preprocessed multi-source data. Variable coding is performed on design parameters, manufacturing schedule, transportation status, environmental parameters, and construction status; A multi-dimensional state vector is constructed based on design parameters, manufacturing schedule, transportation status, environmental parameters, and construction status, and a state space model is generated. State transition relationships are constructed based on the state-space model, and the state-space model is associated between adjacent time steps; The state update driving term in the state transition relationship is constructed based on the scheduling scheme and cross-stage constraint relationship.

5. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the constraint construction module, the step of constructing cross-stage constraint relationships based on preprocessed multi-source data includes: Design parameters, manufacturing schedule, transportation status, environmental parameters, and construction status are extracted from the preprocessed multi-source data. Constraint triggering conditions are identified based on design parameters, manufacturing schedule, transportation status, and environmental parameters. Associate the constraint triggering conditions with the construction tasks in the construction state; Establish a correlation between design parameters, manufacturing schedule, transportation status, environmental parameters and construction tasks; Generate cross-stage constraint relationships based on the correlation between constraint triggering conditions and construction tasks; Establish constraint transmission paths between design stage data, manufacturing stage data, transportation stage data, construction stage data, and environmental data based on cross-stage constraint relationships, and update the task constraint set based on the constraint transmission paths.

6. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the constraint construction module, the step of mapping cross-stage constraint relationships to construction tasks includes: The construction tasks are divided into task nodes; Match the constraint triggering conditions in the cross-stage constraint relationship with the construction task nodes; Assign constraint triggering conditions to matching construction task nodes; Associating construction task nodes with corresponding constraint triggering conditions forms a task-level constraint structure; The task-level constraint structures are summarized to generate a task constraint set.

7. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the scheduling generation module, the step of constraint solving based on the state-space model, state transition relations, and task constraint set includes: Scheduling variables are determined based on the set of construction tasks. These scheduling variables include the task execution order, task start time, and resource allocation relationships. Construct constraint expressions based on the task constraint set; State-related constraints are constructed based on the state-space model and state transition relationships, and these constraints are incorporated into the constraint expressions. Constraint solving is performed based on scheduling variables and constraint expressions, wherein the constraint solving process is performed based on scheduling variables and constraint expressions for calculation. A scheduling scheme for construction tasks is generated based on the constraint solution results.

8. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the state update module, the step of obtaining multi-source data at the current moment includes: Determine the time stamp corresponding to the current moment based on a unified time scale; Data collection is triggered based on time markers for design phase data, manufacturing phase data, transportation phase data, construction phase data, and environmental data. Obtain the design phase data, manufacturing phase data, transportation phase data, construction phase data, and environmental data corresponding to the current moment; Associate the current time stamp with the acquired data; The data associated with time markers are integrated to generate multi-source data for the current moment.

9. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the state update module, the step of updating the state space model based on the multi-source data at the current moment through state transition relationships includes: Extract the state vector corresponding to the current moment from the state-space model; Map the multi-source data at the current moment to the state variables corresponding to the state vector; Based on the state transition relationship, perform state update calculation on the state vector corresponding to the current time and the multi-source data at the current time; Update the state variables based on the state update calculation results; Write the updated state variables into the state space model.

10. The integrated service system for the entire chain of engineering construction projects according to claim 1, characterized in that, In the scheduling adjustment module, the step of performing local rescheduling for the affected subset of construction tasks to obtain an updated scheduling scheme includes: Extract the task nodes corresponding to the affected subset of construction tasks from the set of construction tasks, as well as the associated constraints from the set of task constraints; A local scheduling problem is constructed based on the task nodes and associated constraints of the affected construction task subset. The time range and resource scope of the local scheduling problem are limited. At the same time, the scheduling results of construction tasks not included in the affected construction task subset are retained, and the local scheduling problem is limited to the state variables corresponding to the affected construction task subset. The time constraints, resource constraints, and process sequence constraints in the local scheduling problem are transformed into a standardized set of constraints. Based on the standardized constraint set, the constraint solution is performed on the affected subset of construction tasks to generate candidate scheduling sequences; Select scheduling sequences that satisfy the task constraint set from the candidate scheduling sequences and use them as the updated scheduling scheme.

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