Power plant construction progress visual management and control system and method

Abstract

The invention relates to the technical field of progress management, and discloses a power plant construction progress visual management and control system and method, which can reflect logic constraints between father and child links more truly through multi-level dependency relationship modeling of power plant construction implementation links and progress consistency detection, thereby improving the accuracy of progress display. And secondly, through combination of a segmented migration rule and a disturbance analysis model, progress correction not only considers the dependence intensity of a construction plan, but also can be dynamically adjusted in combination with real-time environmental disturbance factors, so that a progress result is kept consistent with a field condition. And finally, a visual display link realizes visual comparison of a correction result and an original plan, and reveals a deviation source through a link tracking mode, so that a manager can quickly position an anomaly and perform scheduling. On the whole, the intelligent level and the management practicability of power plant construction progress visualization can be greatly improved.

Description

Technical Field

[0001] This invention relates to the field of progress management technology, and in particular to a visual control system and method for power plant construction progress. Background Technology

[0002] In the field of power plant construction, the project mainly involves multiple stages, including civil construction, installation of large equipment, electrical wiring, and system commissioning. These stages are generally subject to strict dependencies. As the scale of the project continues to expand, construction units typically use progress visualization technology to showcase the construction progress, enabling management personnel to maintain overall control.

[0003] However, most existing visualization methods still rely on progress monitoring based on data collected through the Internet of Things (IoT). While these methods can visually compare planned and actual progress, they suffer from several problems: First, the visualization results are mostly static comparisons, failing to accurately reflect the connections between implementation stages, resulting in low overall progress accuracy. Second, when construction sites are disturbed by external factors, existing technologies often lack effective dynamic correction mechanisms, causing the visualization results to become disconnected from reality, leading to poor progress visualization effectiveness. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a power plant construction progress visualization management system and method to solve the technical problem of poor visualization effect when visualizing the progress of power plant construction projects.

[0005] The first aspect of this invention discloses a power plant construction progress visualization and control system, the system comprising:

[0006] The progress data acquisition unit is used to acquire the planned progress data and actual progress data of each construction stage during the power plant construction process.

[0007] A hierarchical modeling unit is used to establish a multi-level schedule structure model based on the construction stages; the schedule structure model is used to represent the dependency relationship between parent construction stages and child construction stages.

[0008] The consistency detection unit is used to compare the actual progress of each parent construction stage with the planned progress of the child construction stage based on the progress structure model, and identify whether the progress is consistent.

[0009] The compensation calculation unit is used to correct the planned schedule of the child construction stage based on the dependency relationship between the construction stages of the parent and child stages and the lag time of the parent construction stage when a schedule inconsistency is identified, so as to obtain the first corrected schedule.

[0010] The disturbance analysis unit is used to acquire environmental disturbance data at the construction site, and to make a second adjustment to the first revised schedule based on the environmental disturbance data through the disturbance analysis model to obtain the second revised schedule;

[0011] The visualization unit is used to compare and display the second revised progress with the original planned progress in a unified timeline and hierarchical view, generating a visual management interface for the power plant construction progress.

[0012] Furthermore, the process of establishing a multi-level schedule structure model based on the construction stages includes:

[0013] Each construction stage is constructed as a node, and the corresponding planned progress data and actual progress data are associated with each node.

[0014] A directed connection edge is established between the parent construction stage node and the child construction stage node that have a dependency relationship; the directed connection edge records the dependency type and the predecessor constraint condition.

[0015] A multi-level progress structure model is formed based on the directed connecting edges and nodes.

[0016] Furthermore, the process by which the consistency detection unit performs the recognition progress consistency operation specifically includes:

[0017] Based on the actual progress data of the parent construction stage node of the progress structure model, the earliest start time and / or the earliest completion time corresponding to the parent construction stage are derived.

[0018] Compare the earliest possible start time and / or earliest possible completion time with the planned progress data of the sub-level construction stage nodes;

[0019] When the comparison result does not meet the predecessor constraint condition, it is identified as a progress inconsistency.

[0020] Furthermore, the progress correction operation performed by the compensation calculation unit specifically includes:

[0021] The first migration strategy is determined based on the strength of the dependency relationship between the parent and child construction stages.

[0022] The first migration strategy is adjusted based on the response type of the sub-level construction stage to obtain the second migration strategy;

[0023] The planned schedule of the child construction stage is modified according to the second migration strategy and the lag time of the parent construction stage; the migration strategy includes a full migration strategy, a partial migration strategy, and a delayed absorption strategy.

[0024] Furthermore, the response types of the sub-level construction stages are categorized into immediate response, partial response, and inert response types based on the task type, resource dependency, and time sensitivity of the sub-level construction stages; among them,

[0025] For sub-level construction processes that respond immediately, a full migration strategy is preferred when performing corrections; for sub-level construction processes that respond partially, a partial migration strategy is preferred; and for sub-level construction processes that respond lazily, a delayed absorption strategy is preferred.

[0026] Furthermore, the process of constructing the disturbance analysis model includes:

[0027] The collected historical environmental disturbance data is constructed into a multidimensional disturbance factor time series; the environmental disturbance data includes climate data, equipment delivery data, and construction personnel attendance data;

[0028] Trend features, mutation features, and fluctuation amplitude features are extracted from the time series of the disturbance factor, and a feature vector of the disturbance factor is generated based on the extracted features;

[0029] The disturbance factor feature vector is fitted with the corresponding historical progress deviation data to obtain the disturbance analysis model; the historical progress deviation data represents the degree of deviation of the disturbance factor change from the actual construction progress.

[0030] Furthermore, the process of making a secondary adjustment to the first correction progress based on environmental disturbance data using a disturbance analysis model specifically includes:

[0031] Based on the real-time collected environmental disturbance data, a real-time disturbance factor feature vector is generated;

[0032] The real-time disturbance factor feature vector is input into the disturbance analysis model to calculate the corresponding schedule deviation correction value;

[0033] The schedule deviation correction value is applied to the first corrected schedule to obtain the second corrected schedule.

[0034] Furthermore, the disturbance analysis model is dynamically updated through a rolling time window, specifically including:

[0035] Within the time window, when the detected mutation features of the combination of perturbation factors exceed a preset threshold, local model refitting is triggered.

[0036] Within the time window, when the difference between the predicted schedule deviation and the actual schedule deviation exceeds the preset tolerance, the time sensitivity parameter and factor coupling parameter in the disturbance analysis model are iteratively corrected based on the latest actual schedule deviation value. The time sensitivity parameter represents the degree of influence of each disturbance factor on the schedule at different time scales, and the factor coupling parameter represents the nonlinear coupling effect when multiple disturbance factors act together.

[0037] Furthermore, the visualization display unit is specifically used for:

[0038] Map the second revised schedule to the corresponding construction component positions in the 3D construction model;

[0039] Based on the multi-level schedule structure model, the progress transmission path between the parent and child construction stages is displayed in a link tracing manner, highlighting nodes with schedule anomalies and / or delays.

[0040] The second aspect of this invention discloses a method for visually controlling the construction progress of a power plant, which is applied to the system disclosed in the first aspect. The method includes:

[0041] Obtain planned and actual progress data for each construction phase during the power plant construction process;

[0042] A multi-level schedule structure model is established based on the construction stages; the schedule structure model is used to represent the dependency relationship between parent and child construction stages.

[0043] Based on the aforementioned schedule structure model, the actual progress of each parent construction stage is compared with the planned progress of the child construction stage to identify whether the progress is consistent.

[0044] When a schedule inconsistency is identified, the planned schedule of the child construction stage is adjusted based on the dependency relationship between the parent and child construction stages and the lag time of the parent construction stage, resulting in the first adjusted schedule.

[0045] The environmental disturbance data of the construction site is obtained, and the first revised schedule is adjusted a second time based on the environmental disturbance data through the disturbance analysis model to obtain the second revised schedule;

[0046] The revised schedule is compared and displayed with the original schedule on a unified timeline and in a hierarchical view, generating a visual management interface for the power plant construction progress.

[0047] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0048] This invention, through multi-level dependency modeling of power plant construction implementation stages and schedule consistency detection, can more realistically reflect the logical constraints between parent and child stages, thereby improving the accuracy of schedule display. Secondly, the combination of segmented migration rules and disturbance analysis models ensures that schedule corrections not only consider the dependence strength of the construction plan but also dynamically adjust based on real-time environmental disturbances, guaranteeing consistency between the schedule results and the actual site conditions. Finally, the visualization stage enables a direct comparison between the corrected results and the original plan, and reveals the source of deviations through link tracing, allowing managers to quickly locate anomalies and make adjustments. Overall, this invention can significantly improve the intelligence level and management practicality of power plant construction schedule visualization. Attached Figure Description

[0049] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and form part of this application, do not constitute a limitation thereof. In the drawings:

[0050] Figure 1 This is a schematic diagram of the structure of a power plant construction progress visualization and control system disclosed in Embodiment 1 of the present invention. Detailed Implementation

[0051] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0052] Example 1

[0053] The first aspect of this invention discloses a power plant construction progress visualization and control system, which relates to the field of progress management technology. Please refer to... Figure 1 , Figure 1 This is a schematic diagram of a power plant construction progress visualization and control system disclosed in an embodiment of the present invention. The system includes:

[0054] The progress data acquisition unit is used to acquire the planned progress data and actual progress data of each construction stage during the power plant construction process.

[0055] A hierarchical modeling unit is used to establish a multi-level schedule structure model based on the construction stages; the schedule structure model is used to represent the dependency relationship between parent construction stages and child construction stages.

[0056] The consistency detection unit is used to compare the actual progress of each parent construction stage with the planned progress of the child construction stage based on the progress structure model, and identify whether the progress is consistent.

[0057] The compensation calculation unit is used to correct the planned schedule of the child construction stage based on the dependency relationship between the construction stages of the parent and child stages and the lag time of the parent construction stage when a schedule inconsistency is identified, so as to obtain the first corrected schedule.

[0058] The disturbance analysis unit is used to acquire environmental disturbance data at the construction site, and to make a second adjustment to the first revised schedule based on the environmental disturbance data through the disturbance analysis model to obtain the second revised schedule;

[0059] The visualization unit is used to compare and display the second revised progress with the original planned progress in a unified timeline and hierarchical view, generating a visual management interface for the power plant construction progress.

[0060] Furthermore, the process of establishing a multi-level schedule structure model based on the aforementioned construction stages includes:

[0061] Each construction stage is constructed as a node, and the corresponding planned progress data and actual progress data are associated with each node.

[0062] A directed connection edge is established between the parent construction stage node and the child construction stage node that have a dependency relationship; the directed connection edge records the dependency type and the predecessor constraint condition.

[0063] A multi-level progress structure model is formed based on the directed connecting edges and nodes.

[0064] Specifically, in constructing the multi-level schedule structure model in this embodiment of the invention, the first step is to abstract each construction stage in the power plant construction into nodes in the model, and associate each node with its corresponding planned schedule data and actual schedule data. The planned schedule data refers to the construction stage plan formulated during the construction planning phase, including but not limited to the planned start time, planned completion time, planned duration, and planned completion percentage for each stage. Actual schedule data refers to the real-time construction status obtained through manual reporting or on-site sensor data collection during construction, including the actual start time, actual completion time, actual duration, and actual completion percentage of each stage. By simultaneously storing planned and actual schedule data at the node level, a data foundation can be provided for subsequent schedule comparison and deviation analysis.

[0065] After establishing nodes, for construction stages with pre- and post-dependent relationships, directed connections need to be established between parent and child construction stage nodes. Here, dependency refers to the requirement that the execution of a child stage must meet the prerequisites of its parent stage in terms of time. Dependencies are typically expressed as different types of predecessor constraints, such as complete-start, start-start, complete-complete, or start-complete. The dependency type is used to identify the specific predecessor constraint method used between parent and child stages. The predecessor constraint further specifies whether, under this constraint method, the child stage must start immediately after the parent stage completes, or start only after a certain delay. Therefore, the dependency type and predecessor constraint in this embodiment of the invention are both specific descriptions of dependency relationships.

[0066] When establishing directed connections, each connection points from the parent node to the child node, and records the corresponding dependency type and its constraints on the edge. For example, if equipment installation can only proceed after civil construction is completed, a completion-start connection is established between the civil construction node and the equipment installation node, with the constraint "start upon completion" recorded on this edge. Similarly, if electrical wiring and equipment installation need to be carried out simultaneously, a start-start connection is established, with the constraint "maximum delay time must not exceed 2 days." Directed connections established in this way can intuitively express the temporal dependencies between parent and child construction stages.

[0067] After the nodes and directed edges are constructed, the resulting multi-level schedule structure model can be considered a type of directed graph structure with attribute annotations. This model can not only represent the sequence and hierarchical relationship of construction stages, but also clearly describe the logical dependencies and constraints between different construction stages through the attributes of the edges.

[0068] By constructing the aforementioned multi-level schedule structure model, schedule inconsistencies can be accurately identified in the subsequent schedule consistency detection stage. In other words, the model provides a data structure framework that can uniformly manage planned and actual schedules and explicitly represent the dependency logic of each stage, making the schedule detection and correction process operable and accurate, thus laying the technical foundation for achieving precise and visualized control of power plant construction progress.

[0069] Furthermore, the process by which the consistency detection unit performs the recognition progress consistency operation specifically includes:

[0070] Based on the actual progress data of the parent construction stage node of the progress structure model, the earliest start time and / or the earliest completion time corresponding to the parent construction stage are derived.

[0071] Compare the earliest possible start time and / or earliest possible completion time with the planned progress data of the sub-level construction stage nodes;

[0072] When the comparison result does not meet the predecessor constraint condition, it is identified as a progress inconsistency.

[0073] Specifically, in this embodiment of the invention, when identifying progress consistency, the earliest possible start time and / or earliest possible completion time corresponding to the parent construction stage is first derived based on the actual progress data of the parent construction stage nodes in the progress structure model. For example, when the actual completion rate of the parent construction stage reaches 100% and the actual completion time is recorded, the earliest possible start time of the child stage can be derived; when the parent construction stage is not fully completed but has reached the critical progress, a corresponding earliest possible start time node can be derived; if the actual completion time of the parent stage has been determined, the corresponding earliest possible completion time can be further derived. The purpose of this step is to derive the constraint time for downstream stages using the actual progress status of the parent stage, ensuring that the detection is based on the objective state of the construction site.

[0074] Subsequently, the parent constraint times derived above are compared with the planned schedule data recorded in the child construction stage nodes. The planned schedule data for child construction stages typically includes information such as the planned start time, planned finish time, and expected duration. During the comparison, if the planned start time of the child stage is earlier than the earliest possible start time derived from the parent stage, or the planned finish time of the child stage is earlier than the earliest possible finish time of the parent stage, it indicates that the child stage's schedule does not meet the preceding constraints of the parent stage, thus identifying a schedule inconsistency. In this way, contradictions between downstream planning and upstream actual conditions can be discovered, providing a basis for subsequent schedule adjustments.

[0075] It's important to further clarify that while the schedule structure model associates both parent and child nodes with planned and actual schedule data, the consistency check process uses the parent's actual schedule compared to the child's planned schedule. This choice is based on construction site management logic. The parent's planned schedule only represents the expected goal, while its actual schedule reflects the true completion status. Therefore, only the constraint time derived from the parent's actual schedule can accurately define the executable time of the child task. Simultaneously, the child's planned schedule represents its pre-implementation timeline target; the significance of the check lies in verifying whether this target contradicts the parent's actual state. The parent's planned schedule serves as a reference value for overall project schedule comparison and deviation analysis, measuring the degree of deviation between the parent task's completion and the original target. The child's actual schedule data is primarily used in subsequent stages; that is, when a child task has started or completed, it can be compared with the revised schedule to further identify any anomalies such as premature or delayed execution.

[0076] In summary, the schedule consistency detection operation of this invention goes beyond simple time comparison. It constrains the child-level schedule by using the parent's actual state, ensuring that the detection results promptly reveal discrepancies between the plan and the actual situation. By utilizing the predecessor-successor dependency relationship in the schedule structure model, dynamically collected actual data is matched with static plan data to determine if logical violations exist. This allows for early detection of schedule inconsistencies, preventing the blind commencement or delay of child tasks during construction. It also ensures that subsequent schedule corrections and visualizations are based on reliable fundamental data.

[0077] Furthermore, the schedule correction operations performed by the compensation calculation unit specifically include:

[0078] The first migration strategy is determined based on the strength of the dependency relationship between the parent and child construction stages.

[0079] The first migration strategy is adjusted based on the response type of the sub-level construction stage to obtain the second migration strategy;

[0080] The planned schedule of the child construction stage is modified according to the second migration strategy and the lag time of the parent construction stage; the migration strategy includes a full migration strategy, a partial migration strategy, and a delayed absorption strategy.

[0081] Furthermore, the response types of the sub-level construction stages are categorized into immediate response, partial response, and inert response types based on the task type, resource dependency, and time sensitivity of the sub-level construction stages; among them,

[0082] For sub-level construction processes that respond immediately, a full migration strategy is preferred when performing corrections; for sub-level construction processes that respond partially, a partial migration strategy is preferred; and for sub-level construction processes that respond lazily, a delayed absorption strategy is preferred.

[0083] Specifically, in this embodiment of the invention, the compensation calculation unit performs a progress correction process by first determining a first migration strategy based on the strength of the dependency relationship between the parent and child construction stages. The strength of the dependency relationship is an important indicator for measuring the degree of coupling between parent and child construction stages, describing the degree to which the child stage depends on the parent stage in terms of time scheduling.

[0084] The determination of dependency strength is not a fixed value setting, but a quantitative calculation considering multiple dimensions. Specifically, the basic constraint strength is determined based on the dependency type recorded in the directed connection edges. For example, the strength of a complete-start constraint is usually higher than that of a start-start constraint because the former has a stronger restriction on the initiation of the child task. Secondly, a time constraint factor is introduced based on the predecessor constraint condition. For example, if the child stage requires immediate initiation after the parent stage is completed, a higher strength value is assigned; if a certain delay is allowed, the strength value is reduced accordingly. As a further preferred approach, the resource coupling between the parent and child stages is also considered for correction. When the resources required by the child task are completely dependent on the output of the parent task, its dependency strength is further increased. Through the above operations, the final dependency strength value can quantitatively characterize the logical tightness between the parent and child construction stages.

[0085] In determining the first migration strategy, this embodiment employs a threshold-based segmentation approach. When the dependency strength exceeds a first threshold, the first migration strategy is determined to be full migration; when the dependency strength is between the first and second thresholds, the first migration strategy is determined to be partial migration; and when the dependency strength is below the second threshold, the first migration strategy is determined to be delayed absorption. This segmented determination method ensures clear boundaries for the correction strategies under different dependency strengths, avoiding ambiguity in the calculation of correction amounts.

[0086] After determining the first migration strategy, it is further constrained by the response type of the sub-level construction stage to obtain the second migration strategy. The response type of the sub-level construction stage reflects its sensitivity to schedule deviations during actual execution. This embodiment classifies them through three dimensions: task type, resource dependence, and time sensitivity. Specifically, tasks with strong process continuity, high resource dependence, and time sensitivity, such as large equipment hoisting, are classified as immediate response tasks; tasks with a certain buffer period but still needing to be completed within a limited time, such as cable laying, are classified as partial response tasks; and tasks with high flexibility and that can be executed in multiple time periods, such as non-critical supporting facility construction, are classified as inert response tasks. Based on this classification, different types of sub-level construction stages have their preferred migration strategies when performing corrections: immediate response tasks preferentially apply the full migration strategy, partial response tasks preferentially apply the partial migration strategy, and inert response tasks preferentially apply the delayed absorption strategy.

[0087] It should be noted that the first migration strategy and the second migration strategy are not always different. In some cases, the response type of the child construction stage is consistent with the result of the dependency strength determination between the parent and child stages, in which case the second migration strategy can be the same as the first migration strategy without additional adjustment. In other cases, if the response type of the child stage conflicts with the first migration strategy, the correction strategy for the child stage needs to be adjusted. For example, when the dependency strength determination between the parent and child stages indicates full migration, but the child construction stage belongs to the inert response type, the second migration strategy may be adjusted to delayed absorption to avoid excessive modification of the child stage's schedule. Through this mechanism, this embodiment ensures that the schedule modification operation not only considers the strength of the parent-child dependency relationship, but also takes into account the flexibility characteristics of the child task itself, making the modification result more consistent with the actual engineering logic.

[0088] After obtaining the second migration strategy, the compensation calculation unit adjusts the planned schedule of the child construction stage based on this strategy and the lag time of the parent stage. When the strategy is full migration, the lag time of the parent stage is fully added to the planned start and finish times of the child stage. When the strategy is partial migration, only a portion of the lag time of the parent stage is proportionally transferred to the child stage, with the remaining portion absorbed by a buffer period or resource scheduling. When the strategy is delayed absorption, the lag time of the parent stage is decomposed into multiple sub-time slices and gradually added to the planned schedule of the child stage. The purpose of these adjustments is to ensure that the schedule of the child stage remains logically consistent with the actual completion status of the parent stage, while avoiding unreasonable over-adjustments to the child tasks.

[0089] Through the above operations, this invention achieves layer-by-layer determination and dynamic adjustment from dependency strength to response type and then to correction strategy, ensuring the rationality and flexibility of schedule correction. By combining the logical dependencies between parent and child components with the attributes of child tasks, a schedule compensation system that conforms to the actual construction logic is constructed, improving the accuracy and adaptability of schedule correction results, so that the final schedule visualization results can truly reflect the progress of the project.

[0090] Furthermore, the process of constructing the disturbance analysis model includes:

[0091] The collected historical environmental disturbance data is constructed into a multidimensional disturbance factor time series; the environmental disturbance data includes, but is not limited to, climate data, equipment delivery data, and construction personnel attendance data;

[0092] Trend features, mutation features, and fluctuation amplitude features are extracted from the time series of the disturbance factor, and a feature vector of the disturbance factor is generated based on the extracted features;

[0093] The disturbance factor feature vector is fitted with the corresponding historical progress deviation data to obtain the disturbance analysis model; the historical progress deviation data represents the degree of deviation of the disturbance factor change from the actual construction progress.

[0094] Furthermore, the process of making a secondary adjustment to the first correction schedule based on environmental disturbance data using a disturbance analysis model specifically includes:

[0095] Based on the real-time collected environmental disturbance data, a real-time disturbance factor feature vector is generated;

[0096] The real-time disturbance factor feature vector is input into the disturbance analysis model to calculate the corresponding schedule deviation correction value;

[0097] The schedule deviation correction value is applied to the first corrected schedule to obtain the second corrected schedule.

[0098] Furthermore, the disturbance analysis model is dynamically updated using a rolling time window, specifically including:

[0099] Within the time window, when the detected mutation features of the combination of perturbation factors exceed a preset threshold, local model refitting is triggered.

[0100] Within the time window, when the difference between the predicted schedule deviation and the actual schedule deviation exceeds the preset tolerance, the time sensitivity parameter and factor coupling parameter in the disturbance analysis model are iteratively corrected based on the latest actual schedule deviation value. The time sensitivity parameter represents the degree of influence of each disturbance factor on the schedule at different time scales, and the factor coupling parameter represents the nonlinear coupling effect when multiple disturbance factors act together.

[0101] Specifically, in this embodiment of the invention, the construction of the disturbance analysis model first relies on the collection and processing of historical environmental disturbance data. Environmental disturbance data refers to external factors that may affect the progress of power plant construction. In this embodiment, the preferred main dimensions include climate data, equipment delivery data, and construction worker attendance data. Climate data includes continuous indicators such as temperature, rainfall, and wind speed; equipment delivery data includes the difference between the equipment delivery time and the planned delivery time; and construction worker attendance data includes the ratio of actual attendance to planned attendance. For ease of unified processing, these data are all constructed as multi-dimensional disturbance factor time series, enabling a complete representation of the evolution of each type of disturbance factor over time.

[0102] After obtaining the time series data, feature extraction is required to generate input vectors suitable for modeling. This embodiment extracts three types of features from the time series: trend features, abrupt change features, and volatility features. Trend features reflect the overall direction of change of the disturbance factor over time, such as a continuous decrease in temperature or a gradual reduction in attendance. Abrupt change features capture sharp changes occurring within a short period, such as sudden heavy rain or delays in the delivery of critical equipment. Volatility features describe the intensity of the disturbance factor's fluctuations, such as the range of attendance fluctuations between adjacent time periods. Based on the feature extraction results, a disturbance factor feature vector is generated as input to the disturbance analysis model.

[0103] Subsequently, the eigenvectors of the disturbance factors need to be fitted with historical schedule deviation data. Here, historical schedule deviation data refers to the difference between the actual and planned progress recorded in the early stages of construction projects or similar power plants, representing the degree of deviation caused by changes in the disturbance factors on the construction schedule. For example, in a certain historical period, when the temperature drops continuously for more than three days, the concrete curing process typically experiences a two-day delay; this difference constitutes the historical schedule deviation data. In this embodiment, the eigenvectors are used as independent variables, and the corresponding schedule deviation data are used as dependent variables. A disturbance analysis model is obtained through a fitting operation. The principle is that the fitting process learns the mapping relationship between changes in the disturbance factors and schedule deviations, enabling the model to provide reasonable deviation predictions under new inputs.

[0104] After the model is built, a secondary adjustment operation is performed on the schedule based on the real-time collected environmental disturbance data. Specifically, after new disturbance data is collected in real time at the construction site, a real-time disturbance factor feature vector is generated through a feature extraction step and input into the disturbance analysis model. The model outputs a schedule deviation correction value based on the mapping relationship learned during the model building phase. It is understood that this correction value is not equivalent to the historical schedule deviation data used during the model training phase, but rather the model's inference output under the current real-time data conditions. The relationship between the two can be understood as follows: the historical schedule deviation data is the model's learning object, while the schedule deviation correction value is the application result after the model learns the pattern. In this embodiment, this correction value is applied to the first corrected schedule to obtain the second corrected schedule, ensuring that the correction result can promptly reflect the actual impact of the on-site disturbance.

[0105] During model application, it is also necessary to ensure that the model can be continuously updated in response to dynamic changes in the construction environment. Therefore, this embodiment introduces a rolling time window mechanism for dynamic updates. A time window is a fixed-length sliding period that aggregates recent disturbance factor data and schedule deviation data. For example, it can be set to the most recent 7 days or the most recent 10 sampling periods. As time progresses, the earliest data is discarded, and the latest data enters the window, ensuring that the model is always updated based on recent data. Within this time window, when a sudden change in the combination of disturbance factors is detected exceeding a preset threshold, local refitting of the model is triggered to quickly adapt to the new disturbance environment.

[0106] Local refitting refers to re-estimating model parameters only for the dimension of the disturbance factor that has undergone a sudden change, while keeping the parameters of other disturbance factors unchanged. Taking meteorological data as an example, when continuous heavy rainfall causes the abrupt change characteristics of the rainfall factor to exceed a threshold, the model only updates the feature weights related to meteorology. In this way, the impact of sudden disturbances on the progress can be quickly reflected, while avoiding large-scale adjustments to the overall model structure, thereby reducing computational overhead and improving the real-time performance of field applications.

[0107] In addition, when the difference between the predicted schedule deviation and the actual observed schedule deviation exceeds the preset tolerance, a parameter calibration operation is triggered.

[0108] The core of parameter calibration lies in iteratively correcting the time-sensitivity parameters and factor coupling parameters in the model. Time-sensitivity parameters represent the degree of impact of each disturbance factor on the schedule at different time scales. For example, weather factors may affect construction on a daily scale, while personnel attendance may accumulate and cause deviations on a weekly scale. Factor coupling parameters describe the nonlinear coupling effect when multiple disturbance factors act together. For instance, when equipment delivery delays are combined with rainfall, it may cause a complex schedule deviation exceeding the effect of a single factor. By iteratively correcting these parameters based on the latest actual schedule deviation values, the model can maintain a high degree of consistency with the actual situation at the construction site.

[0109] In this embodiment, the schedule deviation prediction result is derived from the trend characteristics and fluctuation amplitude characteristics extracted by the disturbance factor sequence within the time window using a disturbance analysis model. The continuity of the trend characteristics can reflect the potential delay or advancement of future progress, while the fluctuation amplitude characteristics are used to estimate the possible deviation range in the future. Therefore, the prediction result can provide early warning for managers, allowing them to adjust the construction plan in advance before the deviation may exceed the tolerance.

[0110] In summary, the disturbance analysis model in this embodiment achieves dynamic correction and prediction of schedule deviations through historical data fitting, real-time inference, and rolling update mechanisms. This not only improves the accuracy and adaptability of the correction results but also provides a scientific early warning basis for construction management.

[0111] Furthermore, the visualization unit is specifically used for:

[0112] Map the second revised schedule to the corresponding construction component positions in the 3D construction model;

[0113] Based on the multi-level schedule structure model, the progress transmission path between the parent and child construction stages is displayed in a link tracing manner, highlighting nodes with schedule anomalies and / or delays.

[0114] Specifically, in this embodiment of the invention, the visualization unit is used to intuitively display the power plant construction progress. Its basic function is to compare and display the second revised progress (corrected by the disturbance analysis model and compensation mechanism) with the original planned progress on a unified timeline and in a hierarchical view, thereby generating a visual management interface for the power plant construction progress. The unified timeline means that all construction stages, regardless of their level, use the same timeline as a reference, allowing managers to observe time differences between construction stages at different levels in a single view. The hierarchical view is a progress display method based on a multi-level progress structure model. In this view, parent-level and child-level construction stages unfold sequentially according to their dependencies, allowing managers to clearly see the progress of upstream stages and the connection status of downstream stages within the hierarchical structure. Through the combined display of the unified timeline and the hierarchical view, the differences between the revised progress and the original plan can be intuitively compared, and the locations of deviations at different levels can be identified.

[0115] Furthermore, the visualization unit in this embodiment can also map the second corrected progress to the corresponding construction component positions in the 3D construction model. It should be noted that the 3D construction model can be a 3D building and equipment model generated based on a BIM platform in the prior art, and it does not constitute the innovation of this invention. The innovation of this invention lies in using this 3D model as a carrier to associate time progress information with spatial component positions. For example, when a delay occurs in the installation of a certain unit, the installation position of the unit can be directly located in the 3D model and displayed intuitively by color marking or animated highlighting. In this way, managers do not need to search for abnormal links in an abstract progress table, but can directly observe the specific physical location corresponding to the deviation in 3D space, greatly improving the visualization effect and actual management efficiency.

[0116] Furthermore, the visualization unit, based on a multi-level schedule structure model, displays the progress transmission path between parent and child construction stages using a link tracing approach. Link tracing here refers to the ability to track the transmission path of a delay in the dependency chain when a delay in a parent stage causes a change in the revised schedule of a child stage, and then visually identify this delay. In practical demonstrations, directed connections on the dependency chain are highlighted, and prominent prompts are placed at delay nodes, allowing managers to quickly see how schedule anomalies propagate from upstream to downstream. For nodes with schedule anomalies and / or delays, this embodiment highlights them with special colors, flashing markers, or warning icons, guiding managers to quickly locate the source of the anomaly and its affected scope.

[0117] Through the above-described display method, the visualization unit in this embodiment achieves a triple fusion of time dimension, hierarchical structure, and spatial location. In the time dimension, a unified timeline ensures a direct comparison between the corrected progress and the original plan. In the hierarchical dimension, the hierarchical view reveals the dependency logic and connection between parent and child stages. And in the spatial dimension, the 3D construction model provides an intuitive mapping between progress deviations and the location of construction entities. Combined with a link tracing mechanism, it can simultaneously display the time difference, logical path, and spatial location of abnormal deviations, thereby greatly improving the intuitiveness of progress control and decision-making efficiency.

[0118] Example 2

[0119] The second aspect of this invention discloses a method for visually controlling the construction progress of a power plant, the method comprising:

[0120] Obtain planned and actual progress data for each construction phase during the power plant construction process;

[0121] A multi-level schedule structure model is established based on the construction stages; the schedule structure model is used to represent the dependency relationship between parent and child construction stages.

[0122] Based on the aforementioned schedule structure model, the actual progress of each parent construction stage is compared with the planned progress of the child construction stage to identify whether the progress is consistent.

[0123] When a schedule inconsistency is identified, the planned schedule of the child construction stage is adjusted based on the dependency relationship between the parent and child construction stages and the lag time of the parent construction stage, resulting in the first adjusted schedule.

[0124] The environmental disturbance data of the construction site is obtained, and the first revised schedule is adjusted a second time based on the environmental disturbance data through the disturbance analysis model to obtain the second revised schedule;

[0125] The revised schedule is compared and displayed with the original schedule on a unified timeline and in a hierarchical view, generating a visual management interface for the power plant construction progress.

[0126] It should be noted that the specific implementation process of Embodiment 2 is similar to that of Embodiment 1, and will not be repeated in this embodiment.

[0127] Finally, it should be noted that the above-described embodiments include multiple parallel implementations of the present invention. Deleting or otherwise adjusting one or more implementations will not affect the implementation of the solution. Furthermore, the power plant construction progress visualization and control system and method disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention, used only to illustrate the technical solutions of the present invention, and not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A power plant construction progress visualization and control system, characterized in that, The control system includes: The progress data acquisition unit is used to acquire the planned progress data and actual progress data of each construction stage during the power plant construction process. A hierarchical modeling unit is used to establish a multi-level schedule structure model based on the construction stages; the schedule structure model is used to represent the dependency relationship between parent construction stages and child construction stages. The consistency detection unit is used to compare the actual progress of each parent construction stage with the planned progress of the child construction stage based on the progress structure model, and identify whether the progress is consistent. The compensation calculation unit is used to correct the planned schedule of the child construction stage based on the dependency relationship between the construction stages of the parent and child stages and the lag time of the parent construction stage when a schedule inconsistency is identified, so as to obtain the first corrected schedule. The disturbance analysis unit is used to acquire environmental disturbance data at the construction site, and to make a second adjustment to the first revised schedule based on the environmental disturbance data through the disturbance analysis model to obtain the second revised schedule; The visualization unit is used to compare and display the second revised progress with the original planned progress in a unified timeline and hierarchical view, generating a visual management interface for the power plant construction progress.

2. The power plant construction progress visualization and control system according to claim 1, characterized in that, The process of establishing a multi-level progress structure model based on the construction stages includes: Each construction stage is constructed as a node, and the corresponding planned progress data and actual progress data are associated with each node. A directed connection edge is established between the parent construction stage node and the child construction stage node that have a dependency relationship; the directed connection edge records the dependency type and the predecessor constraint condition. A multi-level progress structure model is formed based on the directed connecting edges and nodes.

3. The power plant construction progress visualization and control system according to claim 2, characterized in that, The process by which the consistency detection unit performs the recognition progress consistency operation specifically includes: Based on the actual progress data of the parent construction stage node of the progress structure model, the earliest start time and / or the earliest completion time corresponding to the parent construction stage are derived. Compare the earliest possible start time and / or earliest possible completion time with the planned progress data of the sub-level construction stage nodes; When the comparison result does not meet the predecessor constraint condition, it is identified as a progress inconsistency.

4. The power plant construction progress visualization and control system according to claim 1, characterized in that, The progress correction operation performed by the compensation calculation unit specifically includes: The first migration strategy is determined based on the strength of the dependency relationship between the parent and child construction stages. The first migration strategy is adjusted based on the response type of the sub-level construction stage to obtain the second migration strategy; The planned schedule of the child construction stage is modified according to the second migration strategy and the lag time of the parent construction stage; the migration strategy includes a full migration strategy, a partial migration strategy, and a delayed absorption strategy.

5. The power plant construction progress visualization and control system according to claim 4, characterized in that: The response types of the sub-level construction stages are categorized into immediate response, partial response, and inert response types based on the task type, resource dependency, and time sensitivity of the sub-level construction stages; among them, For sub-level construction processes that respond immediately, a full migration strategy is preferred when performing corrections; for sub-level construction processes that respond partially, a partial migration strategy is preferred; and for sub-level construction processes that respond lazily, a delayed absorption strategy is preferred.

6. The power plant construction progress visualization and control system according to claim 1, characterized in that, The process of constructing the disturbance analysis model includes: The collected historical environmental disturbance data is constructed into a multidimensional disturbance factor time series; the environmental disturbance data includes climate data, equipment delivery data, and construction personnel attendance data; Trend features, mutation features, and fluctuation amplitude features are extracted from the time series of the disturbance factor, and a feature vector of the disturbance factor is generated based on the extracted features; The disturbance factor feature vector is fitted with the corresponding historical progress deviation data to obtain the disturbance analysis model; the historical progress deviation data represents the degree of deviation of the disturbance factor change from the actual construction progress.

7. The power plant construction progress visualization and control system according to claim 6, characterized in that, The process of making a secondary adjustment to the first correction progress based on environmental disturbance data using a disturbance analysis model specifically includes: Based on the real-time collected environmental disturbance data, a real-time disturbance factor feature vector is generated; The real-time disturbance factor feature vector is input into the disturbance analysis model to calculate the corresponding schedule deviation correction value; The schedule deviation correction value is applied to the first corrected schedule to obtain the second corrected schedule.

8. The power plant construction progress visualization and control system according to claim 7, characterized in that, The disturbance analysis model is dynamically updated through a rolling time window, specifically including: Within the time window, when the detected mutation features of the combination of perturbation factors exceed a preset threshold, local model refitting is triggered. Within the time window, when the difference between the predicted schedule deviation and the actual schedule deviation exceeds the preset tolerance, the time sensitivity parameter and factor coupling parameter in the disturbance analysis model are iteratively corrected based on the latest actual schedule deviation value. The time sensitivity parameter represents the degree of influence of each disturbance factor on the schedule at different time scales, and the factor coupling parameter represents the nonlinear coupling effect when multiple disturbance factors act together.

9. The power plant construction progress visualization and control system according to claim 1, characterized in that, The visualization display unit is specifically used for: Map the second revised schedule to the corresponding construction component positions in the 3D construction model; Based on the multi-level schedule structure model, the progress transmission path between the parent and child construction stages is displayed in a link tracing manner, highlighting nodes with schedule anomalies and / or delays.

10. A method for visually controlling the construction progress of a power plant, wherein the method is applied to the system described in any one of claims 1-9, characterized in that, The method includes: Obtain planned and actual progress data for each construction phase during the power plant construction process; A multi-level schedule structure model is established based on the construction stages; the schedule structure model is used to represent the dependency relationship between parent and child construction stages. Based on the aforementioned schedule structure model, the actual progress of each parent construction stage is compared with the planned progress of the child construction stage to identify whether the progress is consistent. When a schedule inconsistency is identified, the planned schedule of the child construction stage is adjusted based on the dependency relationship between the parent and child construction stages and the lag time of the parent construction stage, resulting in the first adjusted schedule. The environmental disturbance data of the construction site is obtained, and the first revised schedule is adjusted a second time based on the environmental disturbance data through the disturbance analysis model to obtain the second revised schedule; The revised schedule is compared and displayed with the original schedule on a unified timeline and in a hierarchical view, generating a visual management interface for the power plant construction progress.

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